INTEGRATED RESERVOIR CHARACTERIZATION OF KAILASHTILA …

INTEGRATED RESERVOIR CHARACTERIZATION

OF KAILASHTILA GAS FIELD

MD. MIZANUR RAHMAN

MASTER OF SCIENCE IN PETROLEUM ENGINEERING

DEPARTMENT OF PETROLEUM AND MINERAL RESOURCES ENGINEERING

BANGLADESH UNIVERSITY OF ENGINEERING AND TECHNOLOGY

DHAKA-1000, BANGLADESH

NOVEMBER 2015


OF KAILASHTILA GAS FIELD

A Thesis

by

MD. MIZANUR RAHMAN

Roll No.: 0412132025

Submitted to the Office of Graduate Studies of

Bangladesh University of Engineering & Technology

in partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE

DEPARTMENT OF PETROLEUM AND MINERAL RESOURCES ENGINEERING

November 2015

DECLARATION

It is hereby declared that this thesis or any part of it has not been submitted elsewhere for the award of any degree or diploma.

.

.………… ……………. Md. Mizanur Rahman

DEDICATION

This work is dedicated to my beloved parents who have supported me at every moment in

every possible way.

i

ABSTRACT

An integrated reservoir characterization technique is used to integrate the geological,

engineering and reservoir performance data to describe the reservoir and to develop an

appropriate reservoir management plan. This study has developed an approach using

geological and engineering data to characterize the hydraulic flow unit. It has tabulated

reservoir characteristics for each hydraulic flow unit and reevaluated the reserves for each gas

sands in the field.

A new correlation was developed following Amaefule et.al approach. This new relationship

includes the effect of shale volume, Vsh as a parameter in the porosity permeability

correlation for shaly sand reservoir. This will overcome the limitation of identifying the

hydraulic flow unit of pure sandstone by the present method. The new formula is capable of

accommodating shaly sand as well.

This thesis evaluated reservoir performance potential of Kailashtila Gas Field located at

Sylhet, Bangladesh using the production history; well test data, core data and openhole well

log data. At first, hydraulic flow units were delineated using the core data and openhole well

log data. Then, reservoir parameters like permeability, porosity, skin factor, average reservoir

pressure and absolute open flow potential (AOFP) were estimated by analyzing well test data.

The values of these parameters were compared with the parameters obtained from core and

well log analysis as well as previous study results. Identifying the aquifer type and its effect

on gas production is also a major concern of this study. Finally, updating Gas Initially In-

Place, optimizing field production and prediction of reservoir future performance were done.

ii

ACKNOWLEDGEMENT

At the Beginning, I would like to acknowledge the blessing of Almighty Allah, the

beneficent and the merciful for enabling me to successfully complete my thesis work.

I am highly indebted to my honorable thesis supervisor, Dr. Mohammad Tamim,

Professor and Head of the Department of Petroleum and Mineral Resources Engineering

(PMRE) at Bangladesh University of Engineering& Technology (BUET), Dhaka-1000,

Bangladesh, for the allocation of his valuable time in formulating the thesis design,

correcting and revising the write-up of the thesis. Without his academic guidance, active help

and sincere cooperation it would not have been possible for me to complete this thesis in

time.

I wish to express my sincere appreciation to Dr. Mohammed Mahbubur Rahman, associate

professor of the Department of PMRE at BUET, for his invaluable guidance and help in

every aspect of this thesis.

I am highly grateful to Mohammad Mojammel Huque, assistant professor of the Department

of PMRE, BUET and Afifa Tabassum Tinni, assistant professor of the Department PMRE,

BUET for their moral and technical support during the preparation of this thesis.

My special thanks to Farhana Akter, honorable lecturer of the Department of PMRE, BUET

for her valuable advice, inspiration and important suggestion regarding the study.

I would also like to pay my special thanks to my friends and family.

Finally, I want to thank the Department of Petroleum and Mineral Resources

Engineering of Bangladesh University of Engineering& Technology, Dhaka-1000,

Bangladesh.

iii

TABLE OF CONTENTS

ABSTRACT ............................................................................................................................................. i

ACKNOWLEDGEMENT ...................................................................................................................... ii

LITS OF FIGURES ............................................................................................................................... vi

LISTS OF TABLES ................................................................................................................................ x

NOMENCLATURE .............................................................................................................................. xi

CHAPTER I ............................................................................................................................................ 1

INTRODUCTION .................................................................................................................................. 1

1.1 Introduction to Integrated Reservoir Characterization ............................................................ 1

1.2 Introduction to Kailashtila Gas Field ...................................................................................... 2

1.3 Objectives ............................................................................................................................... 5

1.4 Methodology ........................................................................................................................... 6

CHAPTER II ........................................................................................................................................... 7

INTEGRATED RESERVOIR CHARACTERIZATION ANALYSES AND TECHNIQUES ............. 7

2.1 Introduction ............................................................................................................................. 7

2.2 Core Analysis .......................................................................................................................... 7

2.3 Interpretation of Openhole Well Logs .................................................................................... 8

2.3.1 Shale Volume .................................................................................................................. 8

2.3.2 Formation Water Resistivity ........................................................................................... 9

2.3.3 True Resistivity (RT) .................................................................................................... 10

2.3.4 Estimating Water Saturation (Sw) ................................................................................ 10

2.3.6 Permeability .................................................................................................................. 12

2.4 Delineation of Hydraulic Flow Units .................................................................................... 13

2.4.1 Modification of Amaefule et.al Method ........................................................................ 16

2.5 Reservoir Management ......................................................................................................... 17

CHAPTER III ....................................................................................................................................... 18

STRUCTURE, STRATIGRAPHY AND PETROLEUM SYSTEM .................................................... 18

3.1 General Geology ................................................................................................................... 18

3.2 Structure ................................................................................................................................ 20

3.3 Stratigraphy ........................................................................................................................... 27

3.4 Petroleum System ................................................................................................................. 27

3.4.1 Traps ............................................................................................................................. 27

3.4.2 Source Rocks ................................................................................................................ 28

3.4.3 Vertical Seal .................................................................................................................. 28

iv

3.4.4 Timing and Migration ................................................................................................... 28

3.4.5 Reservoirs ..................................................................................................................... 28

CHAPTER IV ....................................................................................................................................... 29

INTEGRATION OF THE GEOLOGICAL AND PETROPHYSICAL MODELS .............................. 29

4.1 Introduction ........................................................................................................................... 29

4.2 Description of Hydraulic Flow Units of Kailashtila Gas Field ............................................. 29

4.2.1 Description of Hydraulic Flow Unit Upper Gas Sand (HU- UGS) ............................... 29

4.2.2 Description of Hydraulic Flow Unit Middle Gas Sand (HU- MGS) ............................ 34

4.2.3 Description of Hydraulic Flow Unit Lower Gas Sand (HU- LGS) ............................... 38

4.2.5 Application of Modified Approach of Amaefule et.al Method .................................... 42

4.3 Deliverability Test Analysis.................................................................................................. 44

4.3.1 Kailashtila Well KTL-01 .............................................................................................. 44



4.3.4 Comparison of Deliverability Test Analysis Results with Previous Study ....................... 54

4.4 Pressure Transient Analysis .................................................................................................. 55




4.4.4 Comparison of Pressure Transient Analysis Results with Previous Study ................... 60

CHAPTER V ........................................................................................................................................ 62

WELL PERFORMANCE AND INDIVIDUAL WELL MODELING ................................................ 62

5.1 Well and Reservoir Data ......................................................................................................... 62

5.2 Prosper Models ....................................................................................................................... 62

5.2.1 Reservoir Pressure......................................................................................................... 63

5.2.2 Inflow Performance Relationship (IPR) ........................................................................ 63

5.2.3 Tubing (Outflow) Performance (TPC) and Tubing Size Optimization ......................... 64

5.2.4 Well Liquid Loading Rate Predictions .......................................................................... 65

5.3 Field Summary ...................................................................................................................... 66

5.4 Kailashtila Well Model Study – Predictions Using Prosper™ ............................................. 67

5.4.1 Kailashtila Well KTL-01 Study (Middle Gas Sand) ..................................................... 67

5.4.2 Kailashtila Well KTL-02 Study (UPPER GAS SAND) ............................................... 78

5.4.3 Kailashtila Well KTL-03 Study (UPPER GAS SAND) ............................................... 88

5.4.4 Kailashtila Well KTL-04 Study (MIDDLE GAS SAND) ............................................ 98

5.4.5 Kailashtila Well KTL-06 Study (UPPER GAS SAND) ............................................. 108

v

CHAPTER VI ..................................................................................................................................... 118

HISTORY MATCHING AND PRODUCTION PREDICTION ........................................................ 118

6.1 MBAL Material Balance Tool ............................................................................................ 118

6.2 History Matching for Upper Gas Sand ............................................................................... 119

6.3 History Matching for Middle Gas Sand (MGS) .................................................................. 127

6.4 History Matching for Lower Gas Sand (LGS) .................................................................... 131

6.5 Predicting the Future Performance ....................................................................................... 135

6.5.1 Production Prediction for Upper Gas Sand ................................................................. 136

6.5.2 Production Prediction for Middle Gas Sand ............................................................... 141

6.5.3 Production Prediction for Lower Gas Sand ................................................................ 144

CHAPTER VII .................................................................................................................................... 147

CONCLUSION AND RECOMMENDATION .................................................................................. 147

REFERENCE ...................................................................................................................................... 150

APPENDIX-A..................................................................................................................................... 153

Core Data for Case Study ............................................................................................................... 153

APPENDIX-B ..................................................................................................................................... 154

CORE DATA OF KAILASHTILA GAS FIELD ............................................................................... 154

Upper Gas Sand .............................................................................................................................. 154

Middle Gas Sand ............................................................................................................................. 156

Lower Gas Sand .............................................................................................................................. 159

APPENDIX-C ..................................................................................................................................... 160

WELL LOGGING DATA OF KAILASHTILA GAS FIELD ........................................................... 160

Upper Gas Sand .............................................................................................................................. 160

Middle Gas Sand ............................................................................................................................. 161

Lower Gas Sand .............................................................................................................................. 162

vi

LITS OF FIGURES

CHAPTER I Figure 1.1: Integrated Reservoir Characterization Approach for Kailashtila Gas Field ........................ 3

Figure 1.2: Location Map of Kailashtila Gas Field ................................................................................ 4

CHAPTER III

Figure 3.1: Regional Tectonic Map of Bangladesh ............................................................................. 19

Figure 3.2: General Stratigraphy and Petroleum System of Bangladesh ............................................. 19

Figure 3.3: Depth Structure Map of Upper Gas Sand and Well Locations ........................................... 21

Figure 3.4: Depth Structure Map of Sand A and Well Locations ......................................................... 22

Figure 3.5: Depth Structure Map of Sand B and Well Locations ......................................................... 23

Figure 3.6: Depth Structure Map of HRZ and Well Locations ............................................................. 24

Figure 3.7: Depth Structure Map of MGS and Well Location .............................................................. 25

Figure 3.8: Depth Structure Map of LGS and Well Locations ............................................................. 26

CHAPTER IV

Figure 4.1: RQI and NPI Correlation for HU-UGS .............................................................................. 30

Figure 4.2: Permeability and Porosity Correlation for HU-UGS .......................................................... 31

Figure 4.3: Water Saturation as a Function of Capillary ...................................................................... 31

Figure 4.4: Comparison between continuous Porosity from Core and Well Log Data ........................ 32

Figure 4.5: Well Log Porosity versus Core Porosity ........................................................................... 32

Figure 4.6: Permeability versus Porosity for HU-UGS ....................................................................... 33

Figure 4.7: Cross Plot of Porosity versus Irreducible Water ................................................................ 33

Figure 4.8: RQI and NPI Correlation for HU-MGS ............................................................................ 35

Figure 4.9: Water Saturation as a Function of Capillary pressure for HU-MGS ................................. 35

Figure 4.10: Comparison between continuous Porosity from Core and Well Log Data....................... 36

Figure 4.11: Well Log Porosity versus Core Porosity ......................................................................... 36

Figure 4.12: Permeability versus Porosity for HU-MGS ...................................................................... 37

Figure 4.13: Cross plot of porosity versus irreducible water ................................................................ 37

Figure 4.14: RQI and NPI Correlation for HU-LGS ............................................................................ 39

Figure 4.15: Water Saturation as a Function of Capillary pressure for HU-LGS ................................ 39

Figure 4.16: Comparison between continuous Porosity from Core and Well Log Data....................... 40

Figure 4.17: Well Log Porosity versus Core Porosity ......................................................................... 40

Figure 4.18: Permeability versus Porosity for HU-LGS ...................................................................... 41

Figure 4.19: Cross plot of porosity versus irreducible water ................................................................ 41

vii

Figure 4.20: RQI and NPI Correlation generated using Ameafule et.al. Method ................................. 43

Figure 4.21: RQI and NPI (1-Vsh) Correlation generated using modified approach ........................... 43

Figure 4.22: The Flow after Flow Test for Kailashtila Well KTL-01................................................... 45

Figure 4.23: Flow after Flow Test C&N Plot to Estimate the AOF for Kailashtila Well KTL-01 ....... 46





Figure 4.28: Semilog Plot for Kailashtila Well KTL-01....................................................................... 56

Figure 4.29: Type Curve Analysis, Homogeneous Reservoir with Wellbore Storage and Skin Effects

for Kailashtila Well KTL-01 ................................................................................................................. 56

Figure 4.30: Semilog plot for Kailashtila Well KTL-02 ....................................................................... 58


for Kailashtila Well 02 .......................................................................................................................... 58

Figure 4.32: Semi log plot for Kailashtila Well KTL-04 ...................................................................... 59


for Kailashtila Well KTL-04 ................................................................................................................. 60

CHAPTER V

Figure 5.1: Tubing Outflow Performance Basics4 ................................................................................ 66

Figure 5.2: KTL-01 Middle Gas Sand Production History ................................................................... 68

Figure 5.3: KTL-01 November 2007 Test Inflow Performance Relationship31 .................................... 69

Figure 5.4: Downhole configuration for KTL-01 ................................................................................. 70

Figure 5.5: KTL-01 Gradient Matching (November Test 2007) .......................................................... 71

Figure 5.6: KTL-01 Dec 2012 Gradient Curve (13.9937 MMscfd @ 2,455 Psig) ............................... 72

Figure 5.7: IPR/VLP Matching for KTL-01 ......................................................................................... 73

Figure 5.8: KTL-01 Rate Sensitivities to Reservoir and First Node Pressure ...................................... 75

Figure 5.9: KTL-01 Model Sensitivities to Reduced Tubing Diameter to 3 ½ inches ......................... 76

Figure 5.10: KTL-01 Model Sensitivities to Water Gas Ratio (3181 Psig Reservoir Pressure and First

Node Pressure 2675 Psig) ..................................................................................................................... 77

Figure 5.11: KTL-02 Upper Gas Sand Production History .................................................................. 78

Figure 5.12: KTL-02 November 2007 Test Inflow Performance Relationship .................................... 79

Figure 5.13: Downhole configuration for KTL-02 ............................................................................... 80

Figure 5.14: KTL-02 Gradient Matching (November Test 2007) ........................................................ 81

Figure 5.15: KTL-02 Dec 2012 Gradient Curve (18.0315 MMscfd @ 2,355 Psig) ............................. 82

viii

Figure 5.16: IPR/VLP Matching for KTL-02 ....................................................................................... 83

Figure 5.17: KTL-02 Rate Sensitivities to Reservoir and First Node Pressure .................................... 85

Figure 5.18: KTL-02 Model Sensitivities to Increase Tubing Diameter to 4 ½ inches ........................ 86

Figure 5.19: KTL-02 Model Sensitivities to Water Gas Ratio (3181 Psig Reservoir Pressure ............ 87

Figure 5.20: KTL-03 Upper Gas Sand Production History .................................................................. 88

Figure 5.21: KTL-03 November 2007 Production Inflow Performance Relationship ......................... 89

Figure 5.22: Downhole configuration for KTL-03 ............................................................................... 90

Figure 5.23: KTL-03 Gradient Matching (November Test 2007) ........................................................ 91

Figure 5.24: KTL-03 Dec 2012 Gradient Curve (15.2414MMscfd @ 2,630 Psig) .............................. 92

Figure 5.25: IPR/VLP Matching for KTL-03 ....................................................................................... 93

Figure 5.26: KTL-03 Rate Sensitivities to Reservoir and First Node Pressure .................................... 95

Figure 5.27: KTL-03 Model Sensitivities to Increased Tubing Diameter to 4 ½ inches ...................... 96

Figure 5.28: KTL-03 Model Sensitivities to Water Gas Ratio (3,291 Psig Reservoir Pressure) .......... 97

Figure 5.29: KTL-04 Middle Gas Sand Production History ................................................................. 98

Figure 5.30: KTL-04 November 2007 Test Inflow Performance Relationship .................................... 99

Figure 5.31: Downhole configuration for KTL-04 ............................................................................. 100

Figure 5.32: KTL-04 Gradient Matching (November Test 2007) ...................................................... 101

Figure 5.33: KTL-04 Dec 2012 Gradient Curve (16.6264MMscfd @ 2,860 Psig) ............................ 102

Figure 5.34: IPR/VLP Matching for KTL-04 ..................................................................................... 103

Figure 5.35: KTL-04 Rate Sensitivities to Reservoir and First Node Pressure .................................. 105

Figure 5.36: KTL-04 Model Sensitivities to Increased Tubing Diameter to 4 ½ inches .................... 106

Figure 5.37: KTL-04 Model Sensitivities to Water Gas Ratio (3,709 Psig Reservoir Pressure and 2650

Psig Top Node Pressure) ..................................................................................................................... 107

Figure 5.38: KTL-06 Middle Gas Sand Production History ............................................................... 108

Figure 5.39: KTL-06 November 2007 Test Inflow Performance Relationship .................................. 109

Figure 5.40: Downhole configuration for KTL-06 ............................................................................. 110

Figure 5.41: KTL-06 Gradient Matching (November Test 2007) ...................................................... 111

Figure 5.42: KTL-06 Dec 2012 Gradient Curve (22.3811MMscfd @ 2,600 Psig) ............................ 112

Figure 5.43: IPR/VLP Matching for KTL-06 ..................................................................................... 113

Figure 5.44: KTL-06 Rate Sensitivities to Reservoir and First Node Pressure .................................. 115

Figure 5.45: KTL-06 Model Sensitivities to Reduced Tubing Diameter to 3 ½ inches ..................... 116

Figure 5.46: KTL-06 Model Sensitivities to Water Gas Ratio (3,176 Psig Reservoir Pressure) ........ 117

ix

CHAPTER VI

Figure 6.1: Cole Plot for Upper Gas Sand ......................................................................................... 120

Figure 6.2: Ratio of Different Drive Mechanism for Upper Gas Sand ............................................... 121

Figure 6.3: Analytical Method for Upper Gas Sand .......................................................................... 122

Figure 6.4: Analytical Method Comparison with and without Aquifer Influx Model ........................ 123

Figure 6.5: History Matching of Gas Production and Pressure of Upper Gas Sand ........................... 124

Figure 6.6: History Matching of Water Production and Pressure of Upper Gas Sand ....................... 125

Figure 6.7: Determination of GIIP in a Water Drive Gas Reservoir................................................... 126

Figure 6.8: Ratio of Different Drive Mechanism for MGS ................................................................ 127

Figure 6.9: Analytical Method Comparison with and without Aquifer Model for MGS ................... 128

Figure 6.10: Gas Production History Matching for MGS ................................................................... 129

Figure 6. 11: Water Production History Matching for MGS .............................................................. 129

Figure 6.12: Selecting Correct Water Model and Determination of GIIP in Water Drive Reservoir . 130

Figure 6.13: Ratio of Different Drive Mechanism for LGS ................................................................ 131

Figure 6. 14: Analytical Method Comparison with and without Aquifer Model for LGS.................. 132

Figure 6.15: Gas Production History Matching for LGS .................................................................... 133

Figure 6.16: Water Production History Matching for LGS ................................................................ 134

Figure 6.17: Selecting Correct Water Model and Determination of GIIP in Water Drive Reservoir . 134

Figure 6.18: Fw flow matching curve for determining of water breakthrough30 ................................ 136

Figure 6.19: Predicted Water and Gas Saturation with Reservoir Pressure for UGS ......................... 137

Figure 6.20: Predicted Cumulative Water Production for UGS up to 2050 ....................................... 137

Figure 6. 21: Predicted Cumulative Gas Production and Reservoir Pressure for UGS ...................... 138

Figure 6. 22: Predicted Gas Recovery Factor and Reservoir Pressure for UGS ................................. 138

Figure 6. 23: Predicted Cumulative Gas Production and Reservoir Pressure for UGS with two more

new wells ............................................................................................................................................ 139

Figure 6. 24: Predicted Gas Recovery Factor and Reservoir Pressure for UGS with two more new

wells .................................................................................................................................................... 139

Figure 6.25: Fw (fractional flow of water) Matching for MGS .......................................................... 141

Figure 6.26: Predicted Cumulative Gas Production for MGS ............................................................ 142

Figure 6.27: Predicted Gas Recovery Factor for MGS ....................................................................... 142

Figure 6.28: Fw (fractional flow of water) matching for LGS ........................................................... 144

Figure 6. 29: Predicted water saturation with reservoir pressure for LGS .......................................... 144

Figure 6.30: Predicted Cumulative Gas Production for LGS up to 2035 ........................................... 145

Figure 6.31: Predicted Gas Recovery Factor for LGS ........................................................................ 145

x

LISTS OF TABLES

Table 4.1: Discretization of Hydraulic Flow Units for Kailashtila Gas Field ....................................... 29

Table 4.2: Reservoir Properties for HU-UGS ....................................................................................... 34

Table 4.3: Reservoir properties for HU-MGS ...................................................................................... 38

Table 4.4: Reservoir properties for HU-LGS ........................................................................................ 42

Table 4.5: Flow after Flow Test Analysis Results for Kailashtila Well KTL-01 ................................. 45



Table 4.8: Various parameters for deliverability test analysis obtained from current study and Al

MansooriWireline Services study for all three wells KTL-01, KTL-02 and KTl-04 ........................... 54

Table 4.9: Results of Horner‟s Analysis for Kailashtila Wells KTL-01, KTL-02 and KTl-04 ............ 55

Table 4.10: Results of Type Curve Analysis, Homogeneous Reservoir with wellbore Storage and Skin

Effects for Kailashtila Wells KTL-01, KTL-02 and KTl-04 ................................................................ 55

Table 4.11: Pressure Transient Analysis Results for Kailashtila Well KTL-01 ................................... 55



Table 4.14: Various parameters for well test analysis obtained from current study and Al Mansoori

Wireline Services study for all three wells KTL-01, KTL-02 and KTl-04 ........................................... 60

Table 5.1: Summary of Kailashtila Well Production ........................................................................... 67

Table 5.2: KTL-01 December 2012 Well Performance Model Prediction (Reservoir Pressure

Calculation) ........................................................................................................................................... 72

Table 5.3: KTL-02 December Well Performance Model Prediction (Reservoir Pressure Calculation)

.............................................................................................................................................................. 82

Table 5.4: KTL-03 November 2007 Backpressure Equation Calculations ........................................... 89

Table 5.5: KTL-03 December Well Performance Model Prediction (Reservoir Pressure Calculation)92


............................................................................................................................................................ 102

Table 5.7: KTL-06 December 2012 Well Performance Model Prediction (Reservoir Pressure

Calculation) ........................................................................................................................................ 112

Table 6.1: Production prediction results for UGS ………………………………...……………………. 140

Table 6. 2: Production prediction results for MGS ……………………………………………….... 143

Table 6.3: Production prediction result for LGS ……………………………………………….…... 146

xi

NOMENCLATURE

As = Surface area of flow medium

a = tortuosity factor

AOFP = Absolute open flow potential

Bg = Gas Formation volume factor (Rbbl/scf or Rbbl/MMscf)

BVW = Bulk volume water

BHP = Bottom hole pressure, Psia

CD = Dimensionless wellbore storage constant

C = Wellbore storage constant (MMscf/psi)

Cg = Gas compressibility (1/psia)

Co = Oil compressibility (1/psia)

Cw = Water compressibility (1/ psia)

Ct = Total compressibility (1/ psia)

DST = Drill stem test

FBHP = Flowing bottomhole pressure

Fs = Shape factor

ft = Feet

FZI = Flow zone indicator

GR = Gamma ray

HC = Hydrocarbon

HU = Hydraulic flow unit

IPR = Inflow performance relationship

k = Permeability (md)

KTL = Kailashtila

LGR = Liquid gas ratio

LGS = Lower Gas Sand

LIT = Laminar inertial turbulent

LPG = Liquefied petroleum gas

m = Cementation factor

mD = Mille Darcy

MGS = Middle Gas Sand

N = North

n = Saturation exponent

xii

NaCl = Sodium Chloride

NEN = North Eastern North

NNE = North northern east

NPI = Normalized porosity index

PVT = Pressure-Volume-Temperature

Pi = Initial reservoir pressure (psia)

Pi (syn) = Synthetic initial reservoir pressure (psia)

P* = Extrapolated pressure (psia)

Pm = Measured pressure (psia)

PPd = Dimensionless anomalous pressure

Pr = Average reservoir pressure

Pb = Base pressure (14.696)

Pw = Wellbore pressure (psia)

PwD = Dimensionless wellbore pressure

Pwf =Wellbore Flowing pressure (psia)

Pwfo =Final flowing pressure (psia)

Pws = Shut-in pressure (psia)

qg = Gas rate (MMscf/d)

qo = Oil rate (stbbl/d)

qw = Water rate (bbl/d)

RFT = Repeat formation test

Rmf = Mud filtrate resistivity

Rmfe = Equivalent mud filtrate resistivity

rmh = Mean hydraulic radius

Rt = True resistivity

RQI = Rock quality index

rw = Wellbore radius (ft)

rD = Dimensionless wellbore radius

Rw = Water resistivity

Rwe = Equivalent water resistivity

S = Skin

SP = Spontaneous potential

SSP = Static spontaneous potential

Sgv = Surface area per unit grain volume

xiii

Sgt = Total surface area per unit grain volume

Sw = Water saturation

SWS = South western south

SSW = South southern south

Swirr = Irreducible water saturation

TPC = Tubing performance curve

UGS = Upper Gas Sand

VLP = Vertical lift performance

Vgs = Grain volume of sand

Vgt = Total grain volume

Vsh = Shale volume

WGR = Water gas ratio

Xe = Reservoir length

Ye = Reservoir width

Ф = Total porosity (fraction)

фN = Porosity from Neutron log

фD = Porosity from Density log

фnsh = Porosity of shaly sandstone from Neutron log

фDsh = Porosity of shaly sandstone from Density log

фz = Normalized porosity index

T = Reservoir temperature ( )

R = Gas constant (10.73 ft3psia / lbmol °R)

Z = Gas compressibility factor

h = Formation thickness (ft)

t = Time (hr)

tc = Effective producing time (hr)

tD = Dimensionless time

tp = Producing time (hr)

ΔPs = Pressure drop due to skin

1

CHAPTER I

INTRODUCTION

1.1 Introduction to Integrated Reservoir Characterization

The proper management of a petroleum reservoir requires considerable efforts in geologic

and engineering characterization to adequately define and exploit the reservoir, and thus to

maximize its economic recovery. In this sense, one must carefully consider both the volume

of available data and the analysis and interpretation of geologic and engineering data in order

to generate an appropriate and realistic reservoir description. The focus of this work is to

develop a detailed reservoir characterization study for the Kailashtila Gas Field, Sylhet,

Bangladesh. The main goal is to incorporate the core, well log and reservoir performance data

into a working reservoir description that can be used for production optimization of the

current field configuration and to use this reservoir description to plan future reservoir

developments.

Geological interpretations are used to understand and describe the depositional sequences

within reservoir systems. The theory of oil and gas migration together with the growth of

faults is also a matter for discussion in the development of a geological interpretation. The

objective in the study of depositional environments is to predict the size and shape of a

reservoir sequence. The textural changes and the composition of the reservoir rock may help

to confirm the interpretation of the processes as well as to indicate the controls on the

distributions of porosity and permeability. The interpretation of the reservoir environment

from cores is correlated with the well logs to map and predict reservoir morphology and

continuity.

The development of petrophysical model provides information about the reservoir rock

properties, such as porosity, permeability, water saturation and lithology. Core data and well

log data provide essential information to construct the petrophysical model. Evaluation of the

initial reservoir pressure is one of the most important tasks in developing a well performance

model. Pressure-Volume-Temperature (PVT) analysis provides information about the

reservoir fluid, initial reservoir pressure, which should be correlated with the other available

tests, such as pressure transient test and repeat formation test (RFT) data. Pressure transient

test data and RFT data provide correlation with PVT data which helps to establish initial

reservoir pressure.

2

Analysis of pressure transient test provides information about formation permeability and the

production potential of the sand. Well test analyses also indicate reservoir boundaries

(presence of faults and no-flow boundaries) and provide an understanding of near-well

phenomena, including the skin factor and harmonic permeability. In contrast, well log and

core analyses provide permeability as a function of depth, and the method of averaging

vertical permeability is useful for interpreting the log and core analysis and integrating with

well test analysis.

Reservoir performance is evaluated based on the production data, well test analysis, and

changes in water saturation. The drill stem test (DST) data and repeat formation test data are

correlated with the production data and pressure surveys. A DST is run under openhole

conditions and provides information as to whether a formation can sustain production. A DST

provides information about the fluid type, formation pressure, and formation permeability

and DST‟s can be used to collect formation fluids for laboratory analysis (PVT, water salinity

etc.). Similarly, an RFT is also run under openhole conditions and can provide information

about reservoir pressure, reservoir fluid and permeability.

To understand the hydraulic conductivity and continuity of a particular reservoir, it uses

“hydraulic flow units”1 which are defined by the reservoir geometry, pore-throat size

distribution and a variety of petrophysical properties. These “flow units” are developed from

and correlated to the available well log and core data for the field. Hydraulic flow units are

defined by their net and gross pays, water saturations, porosity and permeability values.

These data are used to estimate the reserves using isopach-type maps. Considering all the

practical aspects of geological, petrophysical and the reservoir engineering models, the

integrated characterization approach helps to identify the problems critical to the reservoir.

Figure 1.1 shows the schematic flow chart representing the current approach to reservoir

description.

1.2 Introduction to Kailashtila Gas Field

The Kailashtila field is located about 15 km east of the town of Sylhet in north eastern

Bangladesh (Figure 1.2). The field structure is 10 km long by 5 km wide and trends SWS to

NEN. The field was discovered in 1962 by Pakistan Shell, developed by the Bangladesh

National Company and is now operated by Sylhet Gas Fields Limited (SGFL). Gas

production with condensate started in 1983. Sales gas is delivered to a pipeline network after

treatment through a gas plant.

3

Figure 1.1: Integrated Reservoir Characterization Approach for Kailashtila Gas Field2

Integrated Reservoir Characterization

Geological Model Petrophysical Model

Openhole Logs

Core

Data

Depositional Environment Oil and Gas Migration

Openhole Logs

Core

Data

Presence of HC Porosity

Permeability Water Saturation

Lithology

Flow Unit Delineation

Well Performance Model

Production Data

Well Test Data

Sand Performance Well Performance

Hydraulic Connectivity Reserve Estimation

Recommendation for Recompletion Pressure Maintenance

4

Figure 1.2: Location Map of Kailashtila Gas Field3

5

The Kailashtila structure is in the Northeast Surma basin of Bangladesh. The Surma Basin

contains almost exclusively clastic sequences of deltaic, fluvial, and to a lesser degree of

marine sandstones, siltstones, shale and clay stones. These sediments thicken to the West and

to the Southwest. Tectonically the Surma Basin has been subjected to two major forces, a

westward compressional force which resulted in the formation of the Indo-Burma fold belt

and a northern component associated with movement along the Dauki fault parallel with the

Shillong Massif 4.

The gas producing reservoirs are sand layers of early to late Miocene age and are about 7,000

to 9,000 feet (ft) deep. Three main sand reservoirs are confirmed in this field. Gas and

condensate are being produced from six wells. The Kailashtila field reserves are primarily

contained within three distinct horizons that were discovered by well KTL-014:

1. Upper Gas Sand (UGS) 7,483 to 7,662 ft KB (7,422 to 7,601 ftss)

2. Middle Gas Sand (MGS) 9,665 to 9,734 ft KB (9604 to 9673 ftss)

3. Lower Gas Sand (LGS) 9,808 to 9,990 ft KB (9,747 to 9,929 ftss)

A New Gas Sand was identified as being present in all of the wells. The new gas sand thins

out in the region of KTL-03 as it dips below the gas-water contact identified by the KTL-02

logs at 8,908 ftss. Drill stem testing of two deep sands in KTL-02 reported oil production in

association with gas and water4, 5.

1.3 Objectives

The main objectives of this study are to:

1. Characterize the reservoir, Kailashtila Gas Field, Bangladesh, based on geological,

petrophysical and engineering data analyses.

2. Describe the continuity and connectivity of the net pay sand by delineating the

hydraulic flow units for the formation members present in Kailashtila Gas Field.

3. Evaluate the reserves from isopach-type maps and investigate the prospects to

estimate reserves from material balance.

4. Evaluate well performances and optimization of the production strategy.

5. Locate potential sites for infill drilling in order to exploit untapped areas.

6

1.4 Methodology

The Kailashtila Gas Field has been chosen for this study because of its extensive database of

openhole logs, core data, PVT analysis, well test data and production history.

Methodology for this work followed this sequence:

1. Develop a geological model based on the openhole well logs and core information.

The main information of the depositional environment will be based on the openhole

well logs and core data.

2. Developing a petrophysical model depending on the openhole well logs and core data.

The correlation between the openhole well logs and core data will be used for the

determination of porosity, permeability and water saturations. The identification of

lithology and shale content will be based on the correlation of core and openhole well

log information.

3. Delineate hydraulic flow units based on the analyses of the well log and core data,

where flow units represent the continuity and the hydraulic connectivity of the net

sand in the reservoir.

4. Evaluate well performance based on the production data, PVT analysis, and well test

data.

5. Estimate movable reserves using net pay maps.

7

CHAPTER II


ANALYSES AND TECHNIQUES

2.1 Introduction

The main goal of reservoir characterization is to comprehend the reservoir in terms of its

geological, petrological and reservoir performance data. In this chapter, the theory of

integrated reservoir characterization will be discussed. The following techniques will be

discussed in detail:

Core analysis

Openhole well log analysis

Hydraulic unit delineation

Production optimization technique

2.2 Core Analysis

Although there are several new techniques available (advanced seismic processing and cross

well tomography) to assist geologists and petroleum engineers in the evaluation of oil and gas

reservoirs, core analysis still remains the most basic tool for obtaining reliable information on

the reservoir rock. Core analysis provides the direct measurement of many important

formation properties, in particular porosity, permeability, grain size distribution, fluid

saturations, capillary pressure, relative permeability and wettability.

Porosity6 is the measure of the void space or storage capacity of a reservoir material and is normally expressed as a percentage of the bulk volume. The void volume is usually determined on a previously cleaned and dried sample by one of the following procedures:

Extraction of gas or air content

Saturation with liquid

Calculation from Boyle‟s law (upon compression or expansion of gas in the pore

space of the sample)

The permeability7 of a formation is a measure of its ability to conduct fluid. The

determination of permeability involves the measurement of the rate of flow of a fluid of

known viscosity through a cylindrical sample under a pressure differential. Air or nitrogen is

the fluid normally used because of its convenience, availability and relative inertness with

respect to the reservoir rock.

8

Information obtained from the core analysis is extensively used in the development of the

geological and petrophysical model. Lithological descriptions are based on the combination

of core and well log data and the relation of porosity and permeability is often used to

delineate the reservoir flow units. Core data can also be used to determine the irreducible

water saturation by plotting the core porosity and water saturation.

2.3 Interpretation of Openhole Well Logs

Only openhole well logs can provide a continuous record of various formation properties by

recording electrical resistivity, bulk density, natural and induced radioactivity, and hydrogen

content versus depth. These measurements can be used to estimate a continuous record of

formation properties such as porosity, water saturation and rock type versus depth. The

following procedures are used in analyzing the openhole well logs for Kailashtila Gas Field.

2.3.1 Shale Volume

Shale is a mixture of clay minerals and silt laid down in a low energy environment. Clays

have an ability to bind water onto their surface, which complicates the evaluation of water

saturation. Silt is fine grained particles, mostly consisting of silica and small amounts of

carbonates and other non-clay minerals. Silt is difficult to identify since on average it has

nearly the same Neutron and Density log properties as matrix quartz and is also electrically

non-conductive. In analysis involving shaly sands, use the shale volume to correct the values

of the water saturation. These volumes are lower than the values calculated if shale or clay

effects are ignored.

Over-correction of shale effects by computing to a large shale volume will tend to reduce the

water saturation7 and will make a water-producing zone. Using data from the Gamma Ray

log, the Gamma Ray Index relationship can be calculated to determine the shale volume8:

………………………………………………………………. (1)

Where, Ish = Gamma Ray index

GR = Gamma Ray log reading

GRmin = Gamma Ray log reading of the clean sand

GRmax = Gamma Ray log reading of the shaly sand

9

The shale volume is calculated by the Bates9 correlation as:

For consolidated rock,

( ) ………………………………………….……………….. (2)

For unconsolidated rock,

( ) ………………………………….…………………….. (3)

Shale volume can be calculated from Density and Neutron logs as8

..………………………………………….…………..……….. (4)

Where is the shale volume, N and D are the Neutron and Density log readings, and

nsh and dsh are the Neutron and Density log readings in the shaly sand.

Vsh can also be calculated from Spontaneous Potential (SP) logs by using following equation8:

……………...………..….………………………………..……. (5)

Where SP is the normal log reading, SPcl is the SP log reading in clean sand, and SPsh is the SP log reading in the shaly sand.

2.3.2 Formation Water Resistivity

Formation water resistivity, Rw, calculated using the maximum spontaneous potential, SP log

response in clean water sand. Fresh water mud was used in Kailashtila Gas Field.

The static SP (SSP) value in the clean formation is related to the equivalent resistivity Rwe

and Rmfe. Rwe is the equivalent formation water resistivity and Rmfe is the equivalent mud

filtrate resistivity. The relationship between SSP and the equivalent resistivity (Rwe and

Rmfe) can be expressed as8,

..…………………………..………………...……….……..… (6)

Where K is a constant, which depends upon the formation temperature as follows8: ……………………………………..……………………..… (7)

We can solve the resistivity ratio

using the SSP in a porous and permeable, non-shaly

formation.

10

Arranging Equation (6) it can solve for resistivity ratio as

…………………………………………………………………….. (8)

Rmfe can be determined by correcting the mud filtrate resistivity (Rmf), which is measured

from a sample of mud filtrate. This is done by using chart SP-2, from Schlumberger‟s Chart-

Book.9 Chart Gen-9 is then used for the temperature correction. Knowing Rmfe, Rwe is

calculated from Equation (6).

After calculating Rwe, it can estimate for total NaCl salinity. It found that the original

formation water for the Kailashtila Gas Field is very saline, with NaCl reading of about

237,000 ppm. This value was used for environmental correction of the neutron porosity logs.

2.3.3 True Resistivity (RT)

The tornado charts9 for the resistivity tool is used to correct the shallow, medium and deep

resistivity into an equivalent true resistivity. In the highly permeable and porous pay zones,

invasion should be extremely shallow; thus, the deep resistivity could be assumed as Rt. The

true resistivity is used in calculation of water saturation.

2.3.4 Estimating Water Saturation (Sw)

There are several models10, 11, 12 available for the calculation of openhole water saturation, and

each of these models depends on the availability of well log and formation data and the type

of formation. The Saturation-Ratio method and Bulkwater-Saturation method require the

resistivity data and information of the formation water resistivity, Rw. The main advantage of

the Saturation-Ratio method is that it is independent of the porosity and lithology. However,

the accuracy of this method depends on the resistivity devices. The Bulk water-Saturation

method is also independent of porosity measurements but requires accurate estimate of

formation resistivity.

The Resistivity-Overlay method is an easy and quick procedure for determining water

saturation from openhole well logs. The analysis is independent of porosity but does require

accurate estimates of resistivity. The method assumes the porosity is constant and that water

salinity is the water bearing zone. The interpretation is accurate in thick, homogeneous sands

with a distinct oil-water contact.

11

The modified Simandoux13 and Dual-Water11 models are used for accurate analysis in the

shaly sands.

Archie‟s equation is used for accurate analysis in the clean sands. Because of the clean sand,

the Archie‟s equation was used to determine water saturations from openhole well logs for

Kailashtila Gas Field.

Water saturation calculation procedure using Archie equation is described below in a step by

step. This procedure is adapted from George Asquith8.

Data required:

1. Read resistivity (Rt), porosity values from Density and Neutron logs (ɸD, ɸN) in the

sand of interest.

2. Read Rw from log header.

Where,

Rt = True resistivity

ɸD= Porosity from Density log

ɸN = Porosity from Neutron log

Rw = Resistivity of formation water

The procedure for calculating openhole water saturation is as follows:

1. Porosity calculation from the combination Density-Neutron log:

√

……………………..……………………………….….……. (9)

2. Calculation of formation resistivity factor:

……………………………………………….…………………..……… (10)

Where, a = tortuosity factor

m = cementation factor

3. Calculation of water saturation of the clean sand, Sw:

(

)

………………………………………..………….….………….. (11)

Where, n = saturation exponent

12

2.3.6 Permeability

In many cases, there exists a relationship between the values of porosity and permeability, but

such correlations usually are empirical and limited to a given formation in a given area. The

general expression relating porosity and permeability proposed by Wyllie and Rose14 is given

as:

( ) …………………..………………..….……………….……….. (12)

Several investigations15, 16, 17 have proposed various empirical relationships with which

permeability can be estimated from porosity and irreducible water saturation derived from the

well logs. Some of the expressions are as follows:

Based on 230 core reports, Tixier18 proposed C=250, x=3, and y=1, which results in

…………………………………………………………………. (13)

Based on 155 sandstone cores from Gulf Coast, Colorado and California, Timur16 proposed a

similar model with C=100, x=2.25 and y=1, whish yields

..…………………...…………………………….…………… (14)

Coates and Dumanior17 presented a modified form of the general equation, in which they

used w, an empirical parameter related to the cementation and saturation exponents m and n.

…………………………………….……………….……...…….. (15)

The permeability for Kailashtila Gas Field was calculated using Coates19 Equation by using

irreducible water saturation. This value was estimated from bulk volume water at transition

zone.

Permeability: ( )

…...……………………..…..………………… (16)

Where, Kcoef = 62500, EXP = 6.0

13

2.4 Delineation of Hydraulic Flow Units

The key to improved reservoir description and exploitation is developing and understanding

the complex variations in pore geometry within different lithofacies. Core data provides

information on the various depositional and diagenetic controls on pore geometry. Variations

in the pore geometrical attributes in turn define the existence of distinct zones, classified as

flow units, similar reservoir structure and fluid flow characteristics. The discrimination of the

rock type is based on subjective geological observations and on empirical relationships

between the log permeability and porosity. However, for a given rock type, permeability can

vary by several orders of magnitude, which coupled with reservoir structure and other

reservoir properties indicates the existence of several flow units.

Hydraulic flow units are related to the distribution of geologic facies, but do not necessarily

coincide with facies boundaries. Therefore, a hydraulic unit may not be necessarily vertically

contiguous. Hydraulic units are often defined by the following:

Geological attributes off texture (which includes mineralogy, sedimentary structure,

bedding contacts, and permeability barriers)

Petrophysical properties of porosity, permeability and capillary pressure

Knowledge of permeability and permeability distributions20, 21 is critical to developing an

effective reservoir description. Although the distributions of permeability are usually

determined from core data, most wells are not cored. In the case of Kailashtila Gas Field,

only one well was cored. As a result, permeability of the uncored well is estimated from the

permeability and porosity relationship developed from well logs as well as core data. The

general expression for the porosity-permeability relationship can be written as

( ) ………………….………………………...……………………. (17)

There is no rigorous theoretical basis to support the traditional cross plot of the logarithm of

permeability versus porosity, but some analogy can be made with the Kozeny-Carmen22

equation. The general rationale for plotting the logarithm of permeability as a function of

porosity is that permeability is assumed to be log-normally distributed. However, correlation

of two normally distributed parameters does not necessarily establish causality, and because

porosity is generally independent of grain size and porosity and permeability may or may not

be directly proportional. Several investigators17, 19-21, 1 have noted the inadequacy of this

classical approach and proposed alternative models for relating porosity, permeability and

irreducible water saturation.

14

It can conclude from the classical approach that for a given rock type, the different porosity-

permeability relationships are evidence of the existence of different hydraulic units. Several

investigators1, 20, 21, have arrived at similar conclusions about porosity-permeability

relationships.

The mean hydraulic radius is the key to interpreting the hydraulic units and relating porosity,

permeability and capillary pressure. Amaefule, at al.1 considered the role of hydraulic mean

radius in defining hydraulic flow units and correlating permeability from the core data. This

approach is essentially based on a modified Kozeny-Carmen22 equation coupled with the

concept of mean hydraulic radius.

……………………………………………….. (18)

Where r is the pore throat radius in µm and rmh is mean hydraulic radius in µm.

Kozeny23 and Carmen22 considered the reservoir rock to be composed of a bundle of capillary tubes. They used Poisseulle‟s and Darcy‟s laws to derive the following relationship between porosity and permeability:

(

)

………………………………...……………… (19)

Where k is permeability and is effective porosity and τ is tortuosity.

The mean hydraulic radius can be related to the surface area per unit grain volume, Sgv, and the effective porosity, , by Equation (20).

*

+ ………………………….…………..……………………….. (20)

Combining Equation 19 and 20,

*

( ) +

………………..………….……………………………… (21)

Where k is in µm2 and is a fraction. A more generalized form of the Kozeny-Carmen22

relationship is presented as equation (21), where Fs is the shape factor (2 for circular

cylinder). The term Fsτ2 has classically been referred to as Kozeny‟s constant. For uniform

and unconsolidated rock, Carmen22 and Leveratte24 computed the value of Fsτ2 to be 5.

However, Rose and Bruce25 showed that the Fsτ2 could vary from 5 to 100 in real reservoir

rocks.

15

Amaefule et al.1 addressed the variability of Kozeny‟s constant in terms of dividing Equation

(21) by effective porosity, .

√

*

( )+

√ ……………..….……………………………………… (22)

Where, k is in µm2.

For a permeability expressed in md, the following parameter representing the measure of pore

throat size radius of a particular hydraulic unit is defined as

√

………………….……….……….…..……………………….. (23)

Where RQI is the reservoir quality index expressed in µm and 0.0314 is the conversion factor

from milidarcy to µm.

Normalized porosity index ɸz, or NPI, can be defined as

[

( )

] ……………………………………………...…………………. (24)

Amaefule et.al.1 defined another term FZI (µm), designated as Flow Zone Indicator, and

expressed as

√ ………………………..……………………………..……….….. (25)

In an attempt to develop a unified theory to correlate data, Amaefule et.al.1 tried to define a

single constant; this could replace the surface grain volume and the Kozeny constant. They

combined Equation (22) and (25), which results in

√

*

( )+ ……………………………….....….…….…………………… (26)

In Equation 26 the unit for k is µm2 and if k is expressed in milidarcies, then Equation (26)

becomes

√

*

( )+ …………………..………….……………...………… (27)

16

Amaefule et.al.1 combined Equation (23), (24), and (27) and developed the relationship

between RQI, ɸz, and FZI which was expressed as

.

Taking logarithm of both sides of this relation yields

Log RQI = log ɸz + log FZI …………………………….….…………..…………. (28)

According to Amaefule et.al.1 Equation (28) indicates that for any hydraulic unit, log-log plot

of the “Reservoir Quality Index” (RQI) versus the “Normalized Porosity Index” (ɸz) should

yield a straight line of unit slope.

The authors showed that all samples with similar FZI values will lie on the straight line with

unit slope. Sample with different FZI values lie on other parallel lines.

The value of the FZI constant can be determined from the intercept of the unit slope line at

NPI = 1. Samples that lie on the straight line have similar pore throat attributes and thereby

constitute a unique hydraulic flow unit.

This approach was used directly for Kailashtila Gas Filed as most of the core data fall on the

unit slope line.

2.4.1 Modification of Amaefule et.al Method

As the applicability of Amaefule et.al method is limited to shaly sandstones, it necessary to

modify this method in order to account for the preseence of shale.

According to the definition of the surface area for clean sandstones , Sgv, is given by;

……………….……...…………. (32)

Where, Vgs is the grain volume for clean sandstones, but in general, in shaly sands it can

define a total grain volume (shale + sandstone) which can be expressed by Vgt.

It can define the total surface area per unit grain volume Sgt, including shale volume as,

or

.....…………………………..………………………….. (33)

17

Again, including the shale volume in the Sgv parameter it can get,

( ) ……………………………………………………...… (34)

Substituting equation (33) into equation (34) gives,

…………………………………………………….………………. (35)

The original Amaefule et.al equation is,

√

*

( )+

√ ….…………………...……………….……… (36)

Now, the Equation (35) substitute into equation (36),

√

*

( )+

√

or, √

*

( )+

√

or, RQI = NPI*FZI(1-Vsh) …...…………….…………..………………..……..……. (37) Where,

RQI = Rock Quality Index = 0.0314√

NPI = Normalized Porosity Index = *

( )+

FZI = Flow zone Indicator =

√

Taking the logarithm of both sides of Equation (37) gives

Log (RQI) = log [NPI(1-Vsh)] + log (FZI) ………………………………………. (38)

On a log-log plot of RQI versus NPI(1-Vsh) all points with equal FZI values will lie on a

straight line.

2.5 Reservoir Management

After establishing a basic geological and petrophysical model, the reservoir performance is evaluated using the production data.

18

CHAPTER III

STRUCTURE, STRATIGRAPHY AND PETROLEUM SYSTEM

3.1 General Geology

In relation to regional tectonic history, the Kailashtila structure has developed in the foredeep

located west and south of massive orogenic uplifts. It is a north-south trending elongated

anticline with the axis on the north swinging gently towards east like other structures in this

Fold Belt. The Kailashtila structure is considered to be quite young and formed during Late

Pliocene-Early Pleistocene time 3, 5.

The depositional environment of these fields was one of prolific, younger, Tertiary clastics

accumulation along a mobile delta front, developing in a sinking basin, which affected the

lower reaches of the continental slope. However, these main directions of sedimentary flow

are not always reflected in the local thickness trends encountered in the Kailashtila

succession.

The sediments making up the reservoirs are composed of sandstone and shale and considered

to have deposited in the delta or delta front environment. These sediments were subjected to

the later phases of the Himalayan/Arakan orogeny, resulting in the formation of the relatively

gentle folds of the frontal folded belt (Figure 3.1)3.

The stratigraphy of the Kailashtila area is related to the stratigraphy of the Surma Basin and is

based on lithological correlation with rocks in the Assam oil fields (Figure 3.2)3. The

formations that have been reached by wells in the Surma Basin are the DupiTila, Tipam,

BokaBil and Bhuban. Sediments deposited in the later stages of the Indian Plate collision

include the Upper Bhuban and BokaBil units and are overlain by the Tipam and DupiTila.

This stage is represented by sedimentation contemporaneous with the major phase of

continental collision (Late Miocene Recent), when the main uplift Himalayan and Indo-

Burma ranges occurred. Deposition occurred in fluvial-deltaic to estuarine environments

during the Miocene Pliocene, accompanied by extensive channeling and sediment reworking.

19

Figure 3.1: Regional Tectonic Map of Bangladesh3

Figure 3.2: General Stratigraphy and Petroleum System of Bangladesh3

20

3.2 Structure

The Kailashtila field is located in the Surma basin which is a gas prolific Tertiary basin in the

northeastern part of Bangladesh. Actually the Surma basin is in fact the northern extension of

the Bengal basin. The deposition in the Surma basin was almost exclusively clastic sequences

of deltaic to fluvial and to the lesser extent marine sandstone, siltstone and shale.

The Surma basin was formed structurally by the contemporaneous interaction of two major

tectonic elements, i.e. the emerging Shillong Massif to the north and the westward moving

mobile Indo-Burma fold belt. The tectonic movement is considered to have occurred during

Neogene to the present age with the strongest period of crustal disturbance during the middle

Miocene. The primary result of this tectonics is a series of almost N-S oriented asymmetrical

anticlines.

The Kailashtila field is an elongate asymmetrical anticline with a simple four way dip

closure. The structural trend main axis lies almost N–S with about 10 degree tilts towards

northeast-southwest. Structural maps are shown in Figure (3.3 to 3.8)3. The structure lies on

the northeast part of the Surma Basin. The structural dip at the Kailashtila closure is quite

steep estimated to be about 11-15 degrees. This indicates the strong and long duration of

compression had occurred in Kailashtila. The structure was first mapped by Shell in 1960

with a single fold seismic grid which acquired in the late 1950‟s.

No fault was observed from the 2D seismic data at the Kailashtila structure and vicinity. This

is probably due to the low resolution of the variable quality 2D seismic data and probably

more faults can be expected to be seen in a higher resolution 3D seismic data set.

21

Figure 3.3: Depth Structure Map of Upper Gas Sand and Well Locations

22

Figure 3.4: Depth Structure Map of Sand A and Well Locations

23

Figure 3.5: Depth Structure Map of Sand B and Well Locations

24

Figure 3.6: Depth Structure Map of HRZ and Well Locations

25

Figure 3.7: Depth Structure Map of MGS and Well Location

26

Figure 3.8: Depth Structure Map of LGS and Well Locations

27

3.3 Stratigraphy

The stratigraphic sequence of Kailashtila structure is mainly represented by sandstone and

shale of Miocene to Plio-Pleistocene age. As the results of drilling activities following

sedimentary sequences are confirmed in the Kailashtila structure:

DUPI TILA (Plio-Pleistocene), dominated by loosely consolidated sand with occasional clay

stone intercalation, containing lignite and wood fragments.

TIPAM Group consists of Girujan Clay and Tipam Sandstone.

Girujan Clay: composed of clay stone containing traces of carbonaceous debris, interbedded

with sandstone.

Tipam Sandstone: consists of massive sandstone units with interbedded clay stone horizons.

BOKABIL Formation (Middle–Late Miocene), this formation mainly consists of sandstones,

shale and siltstones. The shales are light to medium gray, occasionally dark gray with minor

coal inclusion, soft, silty, micromicaceous and calcareous. The sandstones are light gray, very

fine to fine grained, generally calcareous. The siltstone is light to medium gray with thin

argillaceous lamination, slightly calcareous and sandy. Depositional environment: lower delta

plain.

BHUBAN Formation (Middle Miocene), this zone mainly consists of very fine to medium

grained, well sorted, and sub-angular to sub-rounded, calcareous sandstone. Interbedded gray

shales are common with laminations of siltstone and lignite beds. Paleo-environment seems

to be of persistent marine influence.

3.4 Petroleum System

Regionally, Kailashtila area is a part of the Hatia Petroleum System that located in the south

of the Tangail-Tripura High. The hydrocarbon system is characterized by Plio-Pleistocene

traps in sandstone reservoirs of upper Miocene to Pliocene age. Gas with little or no

condensate is produced. The hydrocarbon source is probably from Miocene Bhuban shale,

which has generated primarily natural gas with minimal condensate.

3.4.1 Traps

Elongate asymmetrical anticline with trending almost NNE-SSW is the trap type for

Kailashtila Gas Field. This compression of structure took place from Miocene to Recent.

28

3.4.2 Source Rocks

It has been mentioned above that all the Kailashtila wells penetrated the Bhuban shale. The

Miocene Bhuban Shale is widely developed over the Bengal Basin, including the Eastern

Fold belt, and is probably the youngest source rock unit capable of generating gas. The

formation, deposited under a wide range of environmental regimes, from shallow marine

deltaic to fluvio-deltaic, has been characterized by different proportions of alternating shale,

silts and sands, with an overall increase of shale content southwards. The sequence is poor to

lean in terms of source rock potential, with TOC values averaging from 0.2 to 0.7 %.

3.4.3 Vertical Seal

The Upper Marine Shale (late Miocene-early Pliocene) is clearly recognized from seismic

and supposed to be a regional vertical seal in Kailashtila area. Intra-formational seal also

recognized both from well and seismic section.

3.4.4 Timing and Migration

In the Kailashtila as a part of Hatia area, the rapid sedimentation rates during the Miocene

pushed the Oligocene and earlier source rocks through the oil and gas windows well before

the formation of the structural traps in the Pliocene to Recent. The most likely gas source is in

shaly sections of the middle to lower Miocene. The migration pathway is probably a

combination of vertical migration from earlier Miocene through flanking faults and lateral

migration form upper Miocene in basinal, "kitchen" areas.

3.4.5 Reservoirs

Proven reservoir rocks in Kailashtila areas are sandstones of the Upper Gas Sand, New Sand

A, High Resistivity Zone, New Sand B, Middle Gas Sand & Lower Gas Sand. The reservoirs

sandstones are Middle to Late Miocene of age3.

29

CHAPTER IV

INTEGRATION OF THE GEOLOGICAL AND PETROPHYSICAL

MODELS

4.1 Introduction

In this chapter, a modified approach is used for the identification and characterization of

hydraulic flow units within a particular geological unit. The technique is based on the theory

described in Chapter II. Hydraulic units can be thought of as depositional sequences with

unique geological and Petrophysical properties. In a particular hydraulic unit, there should

exist a unique relationship between the RQI (reservoir quality index) and NPI (normalized

porosity index) 23. This relationship can be derived from the core data and can be used to

estimate permeability and irreducible water saturation. All figures for different correlation in

this chapter were generated by „Microsoft Exel‟ software.

This chapter deals with the definition and characterization of hydraulic flow units for

Kailashtila Gas Field, the inter-connectivity of these units and evaluation of flow properties

based on the irreducible water saturation and pore throat size distribution.

4.2 Description of Hydraulic Flow Units of Kailashtila Gas Field

Kailashtila Gas Field is one of the gas bearing sands in Surma Basin. It was deposited within

a fluvial/distributaries channel and the major composition consists mainly of clastic quartz

arenite. The hydraulic flow units for Kailashtila Gas Sands are listed in Table 4.1. The

description of each flow unit is presented in the following sections.

Table 4.1: Discretization of Hydraulic Flow Units for Kailashtila Gas Field

Sand Flow unit Interval (feet) Upper Gas Sand UGS 7422-7601 Middle Gas Sand MGS 9604-9673 Lower Gas Sand LGS 9747-9929

4.2.1 Description of Hydraulic Flow Unit Upper Gas Sand (HU- UGS)

The hydraulic flow unit UGS was deposited in a clastic sequence of deltaic, fluvial and to a

lesser degree marine sandstones, siltstones, shale and clay stones. The sands in this flow unit

are mainly fine to medium grained occasionally coarse.

30

Figure 4.1 shows the log-log correlation of NPI and RQI based on the well log data for this

unit. The relationship between RQI and NPI was obtained by regression analysis, and

represented by the equation shown within Figure 4.1. The square of the residuals (R2) for

NPI and RQI is 0.90, which indicates a good correlation between the NPI and RQI functions.

According to Figure 4.1, all the RQI values for HU-UGS are between 0.1 and 1, which is

indicative of smaller pore throat size with fine-grain, uniformly distributed sand. After

establishing the relationship between NPI and RQI from the well log data, permeability was

estimated using Equation 28,

*

+ *

( )

+

…………....……………………… (29)

All data points of RQI and NPI formed a straight line with unit slope on Figure 4.1 which is indication of single hydraulic flow unit of HU-UGS.

The well log permeability is shown as k-Computed in Figure 4.2. Well log data were used to estimate the values for ɸe and NPI. Recall that NPI is defined by Equation (24) as

*

( )+…………………………………...…………………...……. (24)

Hydraulic flow units are characterized by their distributions of reservoir properties, most notably:

Porosity Permeability Composition and texture Pore throat size distributions Irreducible water saturations

y = 32.881x2.3475 R² = 0.9059

0.1

1

10

0.1 1

RQ

I, µm

NPI, fraction

Figure 4.1: RQI and NPI Correlation for HU-UGS

31

In particular, RQI represents the pore throat size of a flow zone, whereas the irreducible

water saturation strongly depends upon the pore throat size. The permeability distribution of a

hydraulic flow unit also depends on the irreducible water saturation present in that particular

unit. Irreducible water saturation for each hydraulic flow unit estimated using capillary

pressure data.

To check the estimate of irreducible water saturation, water saturation was plotted as a

function of capillary pressure obtained from core analysis. Figure 4.3 gives an estimate of

irreducible water saturation, which appears 10 percent.

1

10

100

1000

10000

0.1 1

Perm

eabi

lity,

mD

Porosity, Fraction

K-Core K-Computed

0

50

100

150

200

250

0 50 100 150

Cap

ilary

Pre

ssur

e

Water Saturation %

Capilary Pressure at7536 ft

Capillary pressure at7560 ft

Capilary Pressure at7615

Figure 4.2: Permeability and Porosity Correlation for HU-UGS

Figure 4.3: Water Saturation as a Function of Capillary pressure for HU-UGS26

32

The matches between core and well log porosity for HU-UGS are shown in Figure 4.4 and

4.5. Figure 4.4 shows the comparison of porosity values from core and porosity values

calculated from well logs. Figure 4.5 represents a log-log plot of well log porosity versus core

porosity, with negligible deviations. Figure 4.5 appears a good correlation between well log

porosity and core porosity and near about all data points lie on straight line. Which approved

the data were from a single hydraulic flow unit.

2240

2260

2280

2300

2320

2340

2360

0 0.1 0.2 0.3 0.4

Dep

th(m

)

Porosity, fraction

Porosity-Core

Porosity-Log

0.01

0.1

1

0.01 0.1 1

Log

Poro

sity

, fra

ctio

n

Core Porosity, fraction

Good Correlation

Figure 4.4: Comparison between continuous Porosity from Core and Well Log Data

Figure 4.5: Well Log Porosity versus Core Porosity27

33

To find a correlation between permeability and porosity for HU-UGS the log of permeability

is plotted versus porosity and a power trend line is fitted through the data points, as shown in

Figure 4.6. The square of the residuals (R2) 0.46 indicates a poor match between porosity and

permeability but all data points created a single trend line. A single trend line is proving of

single hydraulic flow unit.

Figure 4.7 shows a correlation between irreducible water saturation and porosity which is

used to determine bulk volume water. When values of bulk volume water plot along

hyperbolic lines the formation is homogeneous. Figure 4.7 shows that all points are near

about along the hyperbolic line. So the formation of hydraulic flow unit HU-UGS may

homogeneous.

0

0.05

0.1

0.15

0.2

0 0.1 0.2 0.3

(Sw

)irr,

frac

tion

Porosity, fraction

y = 525826x4.5012 R² = 0.4605

1

10

100

1000

10000

0 0.1 0.2 0.3 0.4 0.5

Perm

eabi

lity,

mD

Porosity, fraction

Figure 4.6: Permeability versus Porosity for HU-UGS28

Figure 4.7: Cross Plot of Porosity versus Irreducible Water Saturation used to Determine Bulk Volume Water8

34

Table 4.2 lists the geological and petrophysical properties for HU-UGS and the analyses

shows that this unit is uniform. This Table also shows the difference between well log

anslyses values and core analyses values. Though analyses section of well log analysis and

core analysis were not same.

Table 4.2: Reservoir Properties for HU-UGS

Properties Well log Analysis Core Analysis Interval, ft 7366-7700 7476-7665

Gross Sand, ft 334 189 Net Sand, ft 268 189 Net/Gross 0.802 1.0 ɸ, fraction 0.21 0.24

K, md 501 909 Sw, fraction 0.44 0.30

Swirr, fraction 0.10 0.10 BVW, fraction 0.09 0.07

4.2.2 Description of Hydraulic Flow Unit Middle Gas Sand (HU- MGS)

The hydraulic flow unit HU- UGS is defined in a similar manner as HU-UGS, but it was

found that the porosity and permeability distributions in this flow unit are lower than that of

HU-UGS.




NPI and RQI is 0.99, which indicates an excellent correlation between the NPI and RQI

functions. According to Figure 4.8, all the RQI values for HU-UGS are between 0.1 and 0.4,

which is considerably lower than HU-UGS. The relationship between NPI and RQI indicates

that HU-MGS is lower quality than HU-UGS. After establishing the relationship between

NPI and RQI from the well log data, permeability was estimated using Equation 30,

*

+ *

( )

+

…………….…...………….……… (30)

All data points of RQI and NPI formed a straight line with unit slope on Figure 4.8 which is indication of single hydraulic flow unit of HU-UGS.

35

To estimate the irreducible water saturation, water saturation was plotted as a function of

capillary pressure obtained from core analysis. Figure 4.9 gives an estimate of irreducible

water saturation, which appears 10 percent.

Figure 4.9: Water Saturation as a Function of Capillary pressure for HU-MGS26

0

50

100

150

200

250

0.00 20.00 40.00 60.00 80.00 100.00

Cap

ilary

Pre

ssur

e, P

si

Water Saturation, %

Pc at 9613 ft

Pc at 9639 ft

Pc at 9655 ft

Pc at 9673 ft

Pc at 9701 ft

Pc at 9725 ft

Pc at 9726 ft

y = 75.258x2.8812 R² = 0.9991

0.1

1

10

0.1 1

RQ

I, µm

NPI, fraction

Figure 4.8: RQI and NPI Correlation for HU-MGS28

36

The matches between core and well log porosity for HU-UGS are shown in Figure 4.10 and


calculated from well logs. Figure 4.11 represents a log-log plot of well log porosity versus

core porosity, with negligible deviations. Figure 4.11 appears a good correlation between

well log porosity and core porosity and near about all data points lie on straight line. Which

approved the data were from a single hydraulic flow unit.

0.01

0.1

1

0.01 0.1 1

Log

Poro

sity

, fra

ctio

n


2910

2920

2930

2940

2950

2960

2970

2980

0 0.1 0.2 0.3 0.4

Dep

th, m

Porosity, fraction

Porosity-Core

Porosity-Log



Good Correlation

37

To find a correlation between permeability and porosity for HU-UGS the log of permeability


Figure 4.12. The square of the residuals (R2) 1.0 indicates an excellent match between

porosity and permeability and all data points created a single trend line. A single trend line is

proving of single hydraulic flow unit.

Figure 4.12: Permeability versus Porosity for HU-MGS




about along the hyperbolic line. So the formation of hydraulic flow unit HU-MGS may

homogeneous.

y = 2E+08x8 R² = 1

1

10

100

1000

10000

0.1 0.15 0.2 0.25 0.3

Perm

eabi

lity,

mD

Porosity, fraction

y = 0.0201x-1 R² = 1

0

0.05

0.1

0.15

0.2

0 0.1 0.2 0.3

(Sw

)irr,

frac

tion

Porosity, fraction

Figure 4.13: Cross plot of porosity versus irreducible water saturation used to determine bulk volume water

38

Table 4.3 lists the geological and petrophysical properties for HU-MGS obtained from

current analysis and the analyses shows that this unit is uniform. This Table also shows the

difference between well log anslyses values and core analyses values. Though analyses

section of well log analysis and core analysis were not same.

Table 4.3: Reservoir properties for HU-MGS

Properties Well Log Analysis Core Analysis

Interval, ft 9560-9740 9600-9734

Gross Sand, ft 180 134

Net Sand, ft 180 134

Net/Gross 1.0 1.0

Porosity, fraction 0.19 0.21

K, md 531 753

Sw, fraction 0.29 0.27

Swirr, fraction 0.11 0.10

BVW, fraction 0.05 0.056

4.2.3 Description of Hydraulic Flow Unit Lower Gas Sand (HU- LGS)

The hydraulic flow unit HU-UGS is defined in a similar manner as HU-UGS, but it was

found that the porosity and permeability distributions in this flow unit are lower than that of

HU-UGS.




NPI and RQI is 0.99, which indicates an excellent correlation between the NPI and RQI

functions. According to Figure 4.14, all the RQI values for HU-LGS are between 0.1 and 0.3,

which is considerably lower than that of HU-MGS and HU-UGS. The relationship between

NPI and RQI indicates the HU-LGS is lower quality than HU-UGS and HU-MGS. After

establishing the relationship between NPI and RQI from the well log data, permeability was

estimated using Equation 31,

k *

+ *

( )

+

……………...……….…………… (31)

39

All data points of RQI and NPI formed a straight line with unit slope on Figure 4.14 which is indication of single hydraulic flow unit of HU-LGS.

Figure 4.14: RQI and NPI Correlation for HU-LGS28

To estimate the irreducible water saturation, water saturation was plotted as a function of

capillary pressure obtained from core analysis. Figure 4.15 gives an estimate of irreducible

water saturation, which appears 9 percent.

Figure 4.15: Water Saturation as a Function of Capillary pressure for HU-LGS26

The matches between core and well log porosity for HU-LGS are shown in Figure 4.16 and


y = 86.486x2.9683 R² = 0.9997

0.1

1

10

0.1 1

RQ

I, µm

NPI, fraction

0

50

100

150

200

250

0.00 20.00 40.00 60.00 80.00 100.00

Cap

ilary

Pre

ssur

e, P

si

Water Saturation, %

Pc at 9903 ft Pc at 9919

40

calculated from well logs. Figure 4.17 represents a log-log plot of well log porosity versus

core porosity, with negligible deviations. Figure 4.17 appears a good correlation between

well log porosity and core porosity and near about all data points lie on straight line. Which

approved the data were from a single hydraulic flow unit.

To find a correlation between permeability and porosity for HU-LGS the log of permeability


Figure 4.18.The square of the residuals (R2) 1.0 indicates an excellent match between

0.01

0.1

1

0.01 0.1 1

Log

Poro

sity

, fra

ctio

n


3015

3020

3025

3030

3035

3040

0 0.1 0.2 0.3

Dep

th, m

Porosity, fraction

Porosity-Core

Porosity-Log



41

porosity and permeability and all data points created a single trend line. A single trend line is

proving of single hydraulic flow unit.




about along the hyperbolic line. So the formation of hydraulic flow unit HU-UGS may

homogeneous.

y = 2E+08x8 R² = 1

1

10

100

1000

0.1 0.15 0.2 0.25

Perm

eabi

lity,

mD

Porosity, fraction

y = 0.0201x-1 R² = 1

0

0.05

0.1

0.15

0.2

0 0.05 0.1 0.15 0.2 0.25

(Sw

)irr,

frac

tion

Porosity, fraction

Figure 4.18: Permeability versus Porosity for HU-LGS

Figure 4.19: Cross plot of porosity versus irreducible water saturation used to determine bulk volume water

42

Table 4.4 lists the geological and petrophysical properties for HU-LGS obtained from

current analysis and the analyses shows that this unit is uniform. This Table also shows the

difference between well log anslyses values and core analyses values. Though the total height

of analyses section of well log analysis and core analysis were not same.

Table 4.4: Reservoir properties for HU-LGS

Properties Well Log Analysis Core Analysis Interval, ft 9910-9970 9899-9928

Gross Sand, ft 60 29 Net Sand, ft 60 29 Net/Gross 1 1.0

Porosity, fraction 0.17 0.20 K, md 206 847

Sw, fraction 0.37 0.26 Swirr, fraction 0.12 0.09 BVW, fraction 0.06 0.05

4.2.5 Application of Modified Approach of Amaefule et.al Method

Porosity and permeability data generated on a typical South American clastic rock were used

to compute RQI, NPI and FZI. The Figure 4.20 and 4.21 are plotted using of these data

functions. Figure 4.20 is generated using Amaefule et.al method without considering shale

volumes and all data points did not lie on straight line. Figure 4.21 is plotted using modified

approach with considering shale volumes and all data points well positioned on a straight

line. So, the modified approach approved that the data are taken from a single hydraulic flow

unit in a shaly sand reservoir as the same value of “flow zone indicator (FZI)” obtained from

both plot (Figure 4.20 and Figure 4.21). Thus the modified approach may apply to identify

the hydraulic flow unit for shaly sand reservoir.

43

Figure 4.20: RQI and NPI Correlation generated using Ameafule et.al. Method

Figure 4.21: RQI and NPI (1-Vsh) Correlation generated using modified approach

0.01

0.1

1

10

100

0.01 0.1 1

RQ

I, µm

NPI, fraction

0.01

0.1

1

10

100

0.01 0.1 1

RQ

I, µm

NPI (1-Vsh), fraction

44

4.3 Deliverability Test Analysis

There are two types of deliverability analysis available as the simplified analysis or the

laminar-inertial-turbulent (LIT) analysis. LIT analysis is more rigorous than simplified

analysis and is usually only used in tests where turbulence is dominant and the extrapolation

to the AOFP is large. However, in most cases the simplified analysis is sufficient to

determine the AOFP and deliverability. For both of the simplified and LIT analysis, two

pressure options are available, the pressure squared or the pseudo-pressure approach. Here

simplified analysis is used in terms of Pseudo-pressure and Pressure squared method to

obtain the actual open flow potential (AOFP) for Kailashtila well KTL-01, KTL-02 and KTL-

04.

4.3.1 Kailashtila Well KTL-01

The Kailashtila well no. KTL-01 was drilled in 1961 to 13577 ft. The well was dually

completed in the lower (9810 ft to 9870 ft) and upper gas sands (7487 ft to 7547 ft). The well

completion had a packer at 8740 ft and a tailpipe at 8785 ft. The KTL-01 well produced from

the lower gas sand which was subsequently shut in November 1997 having produced 43 BCF

of gas. On February 28, 1998, a tubing bridge plug was set above the lower gas sand

perforations and 10.5 feet of cement was dumped on top and tested. Intervals in the middle

gas sand were perforated from 9652ft to 9722 ft. The current KTL-01 tubing string is a 4 ½”

API string landed 8783.78 feet (869 feet above the midpoint of perforations).

A flow after flow survey was conducted in Well KTL-01 of Kailashtila Gas field on 24th Nov

2007 to 26th Nov2007. The survey was conducted by Al Mansoori Wireline Services using

quartz memory gauges S/No. 20468 lower and 20389 upper and the sample rate for each

gauge was 30 second. The gauges were calibrated to 10K Psi pressure and 350 0F

temperature. The pressure accuracy is 0.02% of full scale and resolution is 0.00006% of full

scale. The temperature accuracy is 0.45 0F and resolution is <0.009 0F. The gauges were

hanged at a depth of 9300 ftWzl. The gauge recorded complete survey data successfully and

the data quality is excellent. Figure 4.22 shows the flow-after-flow test for well KTL-01. The

flow-after-flow test involved many sequences of drawdown followed by a build-up. It was

observed that the rates were not stabilized in all the flow periods, except for the last

drawdown just before the build-up. The production test was carried out by Al Mansoori

Production services. The well was flowed for approximately 6 hrs in different chokes and

shut in for approximately 24 hrs. The Test Summary is based on the average on specified

choke during the test. The test utilized a surface shut-in.

mk:@MSITStore:G:/WellTest.chm::/Pseudo-Pressure.htm

45

Figure 4.22: The Flow after Flow Test for Kailashtila Well KTL-01

Based on the 3 draw-down periods of the flow-after-flow test, it analyzed the well for the

Absolute Open-Flow-Potential (AOFP). Using the C&N plot shown in Figure 4.23, the

parameter N and C are computed and extended the line to a theoretical bottom-hole flowing

pressure of 1 4.7 Pisa, which will give the theoretical maximum AOFP. The results from the

current study analysis of the C&N IPR plot in Figure 4.23 are given in Table 4.5.

Table 4.5: Flow after Flow Test Analysis Results for Kailashtila Well KTL-01

Parameters Pseudo-Pressure Method Pressure Squared Method

Pavg(Pisa) 3499.3 3499.3

AOF (mmscfd) 336.961 293.10

C[mmscfd/(106psi2/cp)n] 1.80 8.50*102

n 0.778 0.781

Company: SYLHET GAS FIELD LIMITED.

Field Name : KAILASTILLA

Well Name : KTL-1

Well Type: GAS PRODUCER

Formation name: MIDDLE GAS SAND

Type of survey: FLOW AFTER FLOW TEST

Survey Date : 24-Nov-2007 TO 26-Nov-2007

Country: BANGLADESH

3200

3220

3240

3260

3280

3300

3320

3340

3360

3380

3400

3420

3440

3460

3480

3500

3520

Pre

ss

ure

(p

si(

a))

0

4

8

12

16

20

24

28

32

36

40G

as

Ra

te (M

Mscfd

)

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52

Time (h)

pdata

qgas

46

Figure 4.23: Flow after Flow Test C&N Plot to Estimate the AOF for Kailashtila Well KTL-01

47


The Kailashtila well no. KTL-02 was spud on August 6, 1988 and drilled to a total depth on

October 19, 1988. The well was drilled as a straight hole but deviated slightly to a total depth

of 10600ft (3230 m) with a measure depth of 10780 ft (3285 m). Two zones below the lowest

proven gas sand were identified but were not production tested due to project constraints. In

addition to four expected gas sands in the lowest zone, a fifth production zone was discovered

capable of producing more than 25 mmscfd with 150 bpd of condensate. The well was tested

across various intervals and was completed in the Upper Gas Sand from 7390 ft to 7430 ft

with 88.9mm tubing and a packer at 7280ft. The tailpipe has a 2.67‟‟ internal diameter that

was landed at 7316 ft. The rig was released on October 23, 1988.

The KTL-02 well was placed on production in February of 1995 from the upper gas sand at

reported rates of 6 mmscfd with 104 bpd of condensate and no reported water. Latest reported

production from March 2009 is at 21 mmscfd of gas with 255 bpd of condensate and 3.28

bpd of water at a flowing tubing pressure of 2320 psig.


2007 to 22nd Nov 2007. The survey was conducted by Al Mansoori Wireline Services using

quartz memory gauges S/No. 20468 lower and 20389 upper and the sample rate for each

gauge was 30 sec. The gauges were calibrated to 10K Psi pressure and 350 0F temperature.

The pressure accuracy is 0.02% of full scale and resolution is 0.00006% of full scale. The

temperature accuracy is 0.45 0F and resolution is <0.009 0F. The gauges were hanged at a

depth of 7290 ftWzl. The gauge recorded complete survey data successfully and the

dataquality is excellent. Figure 4.24 shows the flow-after-flow test for well KTL-02. The

flow-after-flow test involved 4 periods of increasing draw-down followed by a build-up. The

production test was carried out by Al Mansoori Wireline services. The well was flowed for

approximately 6 hrs in different chokes and shut in for approximately 24 hrs. The test utilized

a surface shut-in.

48





analysis of the C&N IPR plot in Figure 4.25 are given in Table 4.6.



Pavg(psia) 3222.4 3222.4

AOF 1824.36 1552

C[mmscfd/(106psi2/cp)n] 4.53 6.48*102

n 0.908 0.909

3170

3175

3180

3185

3190

3195

3200

3205

3210

3215

3220

3225

3230

Pre

ss

ure

(p

si(

a))

0

5

10

15

20

25

30

35

40

45

50

55

60

Ga

s R

ate

(MM

scfd

)

0 5 10 15 20 25 30 35 40 45 50 55 60 65

Time (h)

pdata

qgas


49


50


The Kailashtila well no. KTL-04 was spud as a vertical appraisal well on 7th August 2006 and

reached the target depth 10,909 ft. on November 27, 1996. Two zones were tested with DST

#1 from 10,260 ft (3,127 m) – 10,274 ft (3,131 m) tested 8.6 mmscfd with 53 bpd

Condensate and 124 bpd water and DST#2 from 9,882 ft (3,012 m) – 9,932 ft (3,027 m)

tested 11.8 mmscfd with 102.6 bpd condensate and 11.4 bpd water. A completion was

run which consisted of a permanent packer at 9,714 ft on a 3 ½” tubing with a 3 ½”

tailpipe to 9,761 ft. The KTL-04 well was placed on production from the Lower Gas Sand in

March 1997 at initial reported rates of 19.2 mmscfd gas with 200 bpd of condensate. Rates

continued until November 2006.

A work over was initiated in September, 2006 and the Lower Gas Sand was

abandoned with a cement plug, and select intervals were perforated in the Middle Gas

Sand from 9,612.9 ft (2,930 m) to 9,675.2 ft (2,949 m); 9,698.2 ft (2,956 m) to 9,704.7 ft

(2,958 m). The well was flow tested after an initial buildup pressure recorded a

surface pressure of 2,730 psi. The Middle Gas sand was put on production in December

2006 at an initial rate of 12.55 mmscfd with 8.4 bbl/mmscf condensate and 0.56 bb/mmscf

measured water. Current production from the Upper Gas sand is 14 mmscfd of gas, 169

bpd of condensate and 3.27 bpd of water at 2,660 psig.


2007 to 18th Nov 2007. The survey was conducted by Al Mansoori Wireline Services

using quartz memory gauges S/No. 20468 lower and 20389 upper and the sample rate for

each gauge was 30sec. The gauges were calibrated to 10K Psi pressure and 350‟F

temperature. The pressure accuracy is 0.02% of full scale and resolution is 0.00006% of full

scale. The temperature accuracy is 0.45‟F and resolution is <0.009‟F. The gauges were

hanged at a depth of 8750 ftWzl. The gauge recorded complete survey data successfully and

the data quality is excellent. Figure 4.26 shows the flow-after-flow test for well KTL-04.

The flow-after-flow test involved 2 periods of increasing draw-down followed by a build-up.

The production test was carried out by Al Mansoori Production services. The well was

flowed for approximately 9 hrs in different chokes and shut in for approximately 24hrs. The

Test Summary is based on the average on specified choke during the test. The test utilized a

surface shut-in.

51

Data Chart

3430

3440

3450

3460

3470

3480

3490

Sa

nd

fac

e P

res

su

re (

psi(

a))

0

2

4

6

8

10

12

14

16

18

Gas R

ate

(MM

scfd

)

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46

Time (h)

Pressure Data

Gas Rate


52





analysis of the C&N IPR plot in Figure 4.27 are given in Table 4.7.



Pavg(psia) 3491 3491

AOF 199.86 179

C[mmscfd/(106psi2/cp)n] 2.63 4.73*103

n 0.644 0.646

53


54

4.3.4 Comparison of Deliverability Test Analysis Results with Previous

Study

Table 4.8 compares the value of various parameters obtained from the deliverability analysis

between current study and Al Mansoori Wireline Services study.

The calculated values of n for all three wells KTL-01, KTL-02 and KTL-04 from current

study are 0.78, 0.91 and 0.64 respectively. These values indicate that the flow condition for

KTL-01 is in between laminar and turbulent, for KTL-02 is laminar dominant and for KTL-

04 is turbulent dominant. On the other hand, the obtained value of „n‟ from Al Mansoori

Wirelines Services study is 1.15 for KTL-01 which is not possible because the value of „n‟

generally in between 0.5 and 1.0. Al Mansoori Wirelines Services acknowledged about this

error but they did not give any explanation behind this. This erroneous result was might be

due to negligence in calculation or data inputting were wrong.

The calculated values of AOF for KTL-01 and KTL-04 from current study are reasonable but

for KTL-02 is unrealistically high with respect to highest production rate of 21 mmscfd. This

is because; it was not possible to record the production test appropriately for KTL-02 due to

malfunction of the process flow separator gas flow meter and also condensate flow rate was

not possible to measure individually. On the other hand, the values of AOF obtained from Al

Mansoori Wirelines Services analysis for all three wells KTL-01, KTL-02 and KTL-04 are

unrealistically high with respect to production rate 22 mmscfd, 21 mmscfd and 14 mmscfd

respectively.

So it can be supposed that current analysis is better than previous analysis.

Table 4.8: Various parameters for deliverability test analysis obtained from current study and Al Mansoori Wireline Services study for all three wells KTL-01, KTL-02 and KTL-04

Well No.

Current Study Al Mansoori Wireline Services Pavg (Psia)

AOF (mmscfd)

C [mmscfd/ (106psi2/cp)n] n

Pavg (Psia)

AOF (mmscfd)

C [mmscfd/ (106psi2/cp)n] n

KTL-01 3499.3 336.96 1.80 0.78 3515 852.2 486 1.15 KTL-02 3222.4 1824.36 4.53 0.91 3221 3575 7.99e-2 0.638 KTL-04 3491 199.86 2.63 0.64 3489 2490 1.03e-2 0.72

55

4.4 Pressure Transient Analysis There are three well tests available for the analysis of Kailashtila wells KTL-01, KTL-02 and KTL-04 and Table 4.9 shows a summary of the well test analysis for these wells using the Horner29 analysis and the results of type curve30 analyses are shown in Table 4.10.

Table 4.9: Results of Horner‟s Analysis for Kailashtila Wells KTL-01, KTL-02 and KTL-04

Well K, mD S P* KTL-01 283 9.8 3485 KTL-02 3207 35 3322 KTL-04 331 18.1 3487.7

Table 4.10: Results of Type Curve Analysis, Homogeneous Reservoir with wellbore Storage and Skin Effects for Kailashtila Wells KTL-01, KTL-02 and KTL-04

Well K, mD S KTL-01 280 6.5 KTL-02 3400 38 KTL-04 330 19

It is noted from Table 4.9 and 4.10 that the estimated permeability and skin from the two different analysis methods are quite close. 4.4.1 Kailashtila Well KTL-01

Pressure transient analysis was carried out for Kailashtila Well KTL-01. A permeability of

283 md as estimate was determined from semilog plot Figure 4.28, then a pressure match is

forced to determine the reservoir properties and final type curve match is shown in Figure

4.29.

The current study results of well test data are presented in Table 4.11 in details.

Table 4.11: Pressure Transient Analysis Results for Kailashtila Well KTL-01

Parameters Value

Remarks Semi Log Type Curve

K(mD) 283 280 Permeability S 9.8 6.5 Skin factor

C(bbl/Psia) - 0.72 Wellbore Storage Coefficient CD - 314221 Dimensionless Wellbore Storage constant

Pi (Psi) 3515 3515 Initial Reservoir Pressure P* (Psia) 3485 3516.5 Extrapolated Pressure Pavg(Psia) - 3506 Average reservoir pressure ∆Ps (Psia) 22.9 15.3 Pressure drop due to skin

Xe (ft) - 60874 Reservoir length Ye (ft) - 6800 Reservoir width

56

For derivative analysis the model chosen a homogeneous, vertical well to analyze the

build-up response with changing wellbore storage in an elongated rectangular reservoir.

The late-time positive ½ slope line in Figure 4.29 is indicative of a well in a channel

system, bounded on either side by parallel faults or low permeability features. Also

the pressure response continues to rise and there is a steep drop in the derivative response

at the end, indicating that there is a communication with some other source of pressure,

and it is assumed a constant pressure boundary on the far ends of the channel.

Derivative

10-1

1.0

2

4

2

4

2

/q / D

eri

va

tiv

e (

(10

6p

si2

/cP

)/M

Mscfd

)

10-3 10-2 10-1 1.0 101 1022 3 4 5 6 7 2 3 4 5 6 7 2 3 4 5 6 7 2 3 4 5 6 7 2 3 4 5 6 7

Pseudo-Time (h)

/qdata

/qmodel

Derivativedata

Derivativemodel

Figure 4.29: Type Curve Analysis, Homogeneous Reservoir with Wellbore Storage and Skin Effects for Kailashtila Well KTL-01

Figure 4.28: Semilog Plot for Kailashtila Well KTL-01

Radial

810

820

830

3440

3460

3480

3500

p (p

si(a

))

1.0101102103104 234567234567234567234567

Radial Horner Pseudo-Time ([(tc + t) / t]a) (h)

data

model

pavg

Ext. model

57



3207 md as estimate was determined from semilog plot Figure 4.30, then a pressure match is


4.31.

For derivative analysis the model chosen was a vertical well in a channel, bounded by 2

sealing faults on either side. The response of the derivative curve, Figure 4.31 with an upward

+1/2 slope is indicative of a well within a channel. The channel could be a high permeability

feature within a low permeability background or it might be a channel bounded by two

sealing faults on either side. The late time upward +1/2 slope line on the derivative is

indicative of a well bounded on 2 sides by the channel boundaries or 2 sealing faults.

The current study results of well test data are presented in details in Table 4.12.


Parameters Values


K(mD) 3207 3400 Permeability S 35 38 Skin factor


Pi (Psi) 3221 3221 Initial Reservoir Pressure P* (Psia) 3222.4 3223.4 Extrapolated Pressure Pavg(Psia) - 3222.5 Average reservoir pressure ∆Ps (Psia) 14.9 15.3 Pressure drop due to skin


58

Derivative

10-5

10-4

10-3

10-2

10-1

1.0

3

3

3

3

3

/q / D

eri

va

tiv

e (

(10

6p

si2

/cP

)/M

Mscfd

)

10-3 10-2 10-1 1.0 101 1022 3 4 5 6 7 2 3 4 5 6 7 2 3 4 5 6 7 2 3 4 5 6 7 2 3 4 5 6 7

Pseudo-Time (h)

/qdata

/qmodel

Derivativedata

Derivativemodel

Figure 4.31: Type Curve Analysis, Homogeneous Reservoir with Wellbore Storage and Skin Effects for Kailashtila Well 02

Figure 4.30: Semilog plot for Kailashtila Well KTL-02

Radial

732

734

736

738

740

3205

3210

3215

3220

p (p

si(a

))

1.0101102103104 234567234567234567234567


data

Semi Log Analysis Result

kh 1.3e+05 md.ft

k 3207.1487 md

s' 34.970

p* 3222.4 psi(a)

pskin 14.9 psi(a)

m 0.1857 (106psi2/cP)/cycle

59



3207 md as estimate was determined from semi log plot Figure 4.32, then a pressure match is


4.33.

The current study results of well test data are presented in details in Table 4.13.


Parameters Values


K(mD) 330.5 330 Permeability S 18.1 19 Skin factor


Pi (Psi) 3491 3491 Initial Reservoir Pressure P* (Psia) 3487.7 3491 Extrapolated Pressure Pavg(Psia) - 3488.5 Average reservoir pressure ∆Ps (Psia) 32.8 34.4 Pressure drop due to skin


For derivative analysis the model chosen was a vertical well in a channel, bounded by 2

sealing faults on either side. The response of the derivative curve with an upward +1/2 slope

in Figure 4.33 is indicative of a well within a channel. The channel could be a high

Radial

824

828

832

3460

3470

3480

3490

p (p

si(a

))

1.0101102103104 234567234567234567234567


data

Analysis

kh 22808.57 md.ft

k 330.5590 md

s' 18.117

p* 3487.7 psi(a)

sd 18.117

pskin 32.8 psi(a)

m 0.8193 (106psi2/cP)/cycle

Figure 4.32: Semi log plot for Kailashtila Well KTL-04

60

permeability feature within a low permeability background or it might be a channel bounded

by two sealing faults on either side. The late time upward +1/2 slope line on the derivative is

indicative of a well bounded on 2 sides by the channel boundaries or 2 sealing faults.

4.4.4 Comparison of Pressure Transient Analysis Results with Previous Study

This section presents the comparison and discussion for various parameters obtained from the

current study and Al Mansoorib Wireline Services for all three wells KTL-01, KTL-02 and

KTL-04.

Table 4.14: Various parameters for well test analysis obtained from current study and Al Mansoori Wireline Services study for all three wells KTL-01, KTL-02 and KTL-04

Properties KTL-01 KTL-02 KTL-04

Current Study

*Previous Study Current Study

*Previous Study

Current Study

*Previous Study

K(mD) 280 147 3400 4700 330 342 S 6.5 3 38 25 19 20.6

C(bbl/Psia) 0.72 0.154 1.01 1.5 0.23 0.179 Pi (Psi) 3515 3515 3221 3221 3491 3491 P* (Psia) 3516.5 N/A 3223.4 N/A 3491 N/A Pavg(Psia) 3506 N/A 3222.5 N/A 3488.5 N/A ∆Ps (Psia) 15.3 N/A 15.3 N/A 34.4 N/A

Xe (ft) 60874 N/A 130000 N/A 70360 N/A Ye (ft) 6800 N/A 35000 N/A 25280 N/A

*Al Mansoori Wireline Services N/A = Not available

Derivative

10-4

10-3

10-2

10-1

1.0

101

3

3

3

3

3

/q /

De

riv

ati

ve

((1

06p

si2

/cP

)/M

Mscfd

)

10-3 10-2 10-1 1.0 101 1022 3 4 5 6 7 2 3 4 5 6 7 2 3 4 5 6 7 2 3 4 5 6 7 2 3 4 5 6 7

Pseudo-Time (h)

/qdata

/qmodel

Derivativedata

Derivativemodel

Figure 4.33: Type Curve Analysis, Homogeneous Reservoir with Wellbore Storage and Skin Effects for Kailashtila Well KTL-04

61

From Table 4.14 it is obtained that the total skin effects are positive for all three wells. The

derived skin factor for well KTL-01, KTL-02 and KTL-04 are 6.5, 38 and 19 respectively.

With the exception of KTL-01 the values of skin for other two wells might seem excessive.

These high skin values may be due to plugged perforation or formation damage.

The calculated values of permeability, skin and wellbore storage for all three wells obtained

from current study are slightly differed from the results obtained from Al Mansoori Wireline

Services. This may due to the selection of either calculation methods or used software.

Pressure is the main energy or driving force of a reservoir for producing hydrocarbon. So, it

is essential to know the average reservoir pressure for describing reservoir conditions. But Al

Mansoori Wireline Services did not estimate average reservoir pressure. The average

reservoir pressures obtained from current study are very close to initial reservoir pressure for

all three wells though productions have been started in 1983 and data used here from the well

test made in 2007. This high average reservoir pressure after 24 years of production may be

due to external pressure support which is identified in Chapter VI from production history.

The reservoir areal extents are also important parameter to estimate reserve. Current study

anticipated the reservoir length and width those can be used to estimate reserve. On the other

hand, Al Mansoori Wireline Services did not calculate reservoir areal extents.

62

CHAPTER V

WELL PERFORMANCE AND INDIVIDUAL WELL MODELING

Through the development of wellbore models, well performance sensitivities reviewed the

effects of varying reservoir pressure, flowing tubing pressure, water gas ratio, and well

configurations. Recommendations have been made to assist in future operations and

completion design practices to optimize production and to help maximize reserve

recoveries.

5.1 Well and Reservoir Data

To assess the inflow performance characteristics and the tubing performance curves,

well models require a good understanding of well geometry along with the static and

flowing reservoir and surface pressures. Accurate stabilized well flow measurements

(gas, water, condensate, flowing temperatures) and fluid analyses are essential to the

development of reliable well models.

The quality of the collected data is variable and the resulting interpretations are highly

dependent on the accuracy of the measurements and data.

5.2 Prosper Models

Well models were constructed using collected well geometries. Well inflow performance

relationships were defined using the backpressure equation from data obtained during testing

operations. The simplified backpressure equation has limited ability to predict inflow

performance changes as a function of changing water gas ratio; however, the quality of the

data was such that a simplified approach was needed to assess current conditions. More

elaborate analytical methods that allow for evaluating the impact of increasing water/gas -

ratios and water influx on the reservoir gas inflow will require much higher quality

test data including more individual multi -point well testing and build-up analysis.

The current data allows review of the potential effects of changing well outflow

parameters such as wellhead pressure, water gas ratio, and tubing size on the well‟s ability to

sustain steady outflow rates.

63

5.2.1 Reservoir Pressure

In addition to the well flow measurements (gas, water, condensate, flowing pressures

and temperatures), the wellbore models require a reasonable estimate of the static

reservoir pressure. Some pressure histories of static reservoir pressure measurements that

were taken from various wells in Kailashtila are collected.

The reservoir pressure is best obtained via extrapolation from extended build up tests,

but accurate estimates can also be obtained if a well is shut in for sufficient time to

stabilize the bottomhole pressure . Decreases in reservoir pressure are anticipated from

natural depletion and lack of pressure support. In general, a much more complete set of

historical static pressure data is required.

5.2.2 Inflow Performance Relationship (IPR)

The backpressure equation is an inflow relationship for gas reservoirs based on the theory of

inflow data plotted as rate versus Pr2-Pwf

2 on log-log paper results in a straight line with slope

1/n and intercept C. The inflow equation developed from these observations is therefore

comprised of two empirical coefficients and is best suited for cases where a multi-rate test

is available. The empirical coefficient C is based on test data at a specific reservoir pressure

and water cut. Adjustments can be made for depletion and water encroachment

reflecting fluid property changes, saturation changes and the effect of the hydrocarbon

competing with the water for net pay. The backpressure equation was used to create the

IPR curves, although no changes were made in the “C” coefficient for changes in

reservoir pressure and water cut to simplify the task. More frequent well tests will allow

for better definition of how the well inflow performance is impacted by changing water or

condensate influx, and by changing reservoir pressure.

Each well was reviewed and well Inflow Performance Relationship (IPR) curves were

defined on the basis of the respective inflow performance relationship determined from

a multipoint test where surface and bottomhole flowing pressures, gas flowrates, and

static reservoir pressures were measured. It is possible in some cases that the flow

periods were not sufficient for stabilized flow which would affect the accuracy in the

model predictions. The reservoir pressure used in the determination of the IPR curve was the

static shut-in pressure from well-tests. The program uses the center of the producing interval

as the datum for reservoir pressure.

64

The Kailashtila well KTL-03 and KTL-06 did not have flowing test measurements with

bottomhole pressure and temperature gauges. Assessing the well performance in these

cases was somewhat more complex given the lack of information to calibrate the models and

more accurately define the IPR‟s. For these two cases, an attempt was made to define the

wells‟ inflow performances using well production data (simulated bottomhole flowing

pressures) at points in time where the reservoir pressure was known.

5.2.3 Tubing (Outflow) Performance (TPC) and Tubing Size Optimization

The well completions and Tubing Performance Curves (TPC) were characterized in the

PROSPER™ model using information obtained from the deviation surveys and the

available completion diagrams to describe the wellbore architecture . The schematics

generally outline the tubing and component sizes and depths. Pressure losses in the wellbore

are critical component of the total system pressure loss from static reservoir pressure to

separator pressure. The TPC‟s were calculated and compared to measured data, whenever

possible. Correction factors were applied to the correlations as required matching the

measured data.

Sensitivities were conducted for various tubing sizes and outflow pressures to address

well productivity predictions. Production performance tables with varying WGR,

Reservoir Pressure, and Surface flowing pressure detail the results of the various

configurations. A more detailed time dependent flow model could be investigated integrating

reservoir parameters with surface facilities to further help in assessing ultimate well

recoveries and economic viabilities.

Flowing Bottomhole Pressure Matching Process

Data from available multi-rate well-tests which included gas and liquid rate

measurement in addition to surface and bottomhole pressures was used to calibrate the

predicted pressure losses in the tubular. The accuracy in the models are a function of

the collected data (gas flow measurement, liquid flow measurement, tubular

specifications, gas and liquid compositional analyses). In cases were no flowing

bottomhole data exists, the vertical flow correlations are utilized without any corrections.

A) PVT Match:

Upon loading the data into the model, test and PVT data were reviewed through

model matching to help validate the test data and the wellbore configurations.

65

B) Matching Gradient Traverse / VLP (Quality Checks):

In matching the well pressure gradients, several vertical lift correlations were investigated to

identify which correlation most effectively matched the available test data. The best

suitable correlation was selected in each case based on the best fit to the measured data.

PROSPER™ suggests that if the gravity correction (Parameter 1) is found to exceed

10%, then there is an implied inconsistency in the PVT data. If the friction correction

(Parameter 2) multiplier is too high, it is an indicator that the equipment description may be

in error. In many cases, the statistical fits exceeded the recommended ranges, suggesting that

the reported gas rates and flowing pressures are not consistent.

C) BHP from Wellhead:

Once the correlation correction factors were assigned for a particular well, bottomhole

flowing pressures were calculated from the current producing well surface flowing

pressures and rate information to estimate the existing well IPR. Given the well

specific IPR, an estimated reservoir pressure was established and model sensitivities

were calculated from the resulting estimated reservoir pressure.

5.2.4 Well Liquid Loading Rate Predictions

Well outflow and decline rate is influenced by several factors including fluid

properties, reservoir and wellhead pressures, reservoir quality (permeability, net-pay,

drainage area, boundaries), as well as the producing liquid/gas ratios and the

configuration of the surface facilities (e.g. flow line pressures, compressors, etc .) The critical

gas rate to lift liquids is a function of the surface flowing pressure, bottomhole flowing

pressure, producing water gas ratio, and well geometry. Gas wells that produce significant

volumes of free water or condensate typically cease producing as reservoir pressure depletes

and the gas velocity within the tubing string decreases to critical gas rate that can no longer

transport liquids efficiently to surface. As the gas rate continues to decline and/or the LGR

increases, the completion can be flooded with fluid influx and liquid loading of the tubing

flow path continually increases until the well kills itself.

Well conditions can be modeled to simulate the conditions that lead to liquid loading

behavior. As the gas flow rates decline, there is a flow regime transition from

mist/annular flow to slug flow, and then ultimately, bubble flow. The overall result is an

increase in back-pressure on the reservoir and a reduction in gas production that causes the

well to cease producing if no intervention is implemented.

66

This study typically advocate the analysis of the intersection point of the Inflow

Performance Relationship (IPR) and Tubing Performance Curve (TPC) as well as the

internal flowing gas velocity to predict the minimum required flow rate required to lift the

produced water. In general, if the producing well conditions (wellhead backpressure)

cause the intersection point of the reservoir IPR and TPC to occur to the left of the TPC

minimum gas flow rate as shown in Figure 5.1 liquid loading will occur and eventually the

well will kill itself.

The model for calculating the minimum gas velocity for removing liquid droplets from

wells was presented by Turner et al in 1969. This used this model for liquid loading rate

prediction.

5.3 Field Summary

Table 5.1 outlines the historical well production characteristics over the produced

periods as reported by Petrobangla for the various sands in the designated wells. The

main sand groups produced to date are the Lower Gas Sand, the Middle Gas Sand, the Upper

Gas Sand and the High Resistivity Zone. Wells are producing at relatively high surface

operating pressures ranging from 2,320 psig to 2,675 psig. This suggests the potential

for increased well productivity and reserves recovery through the addition of more

compression capacity.

Figure 5.1: Tubing Outflow Performance Basics4

67

Historical gas production rates have been as high as 31.05 mmscfd (KTL-02) with water gas ratios ranging up to 82.70 bbl/mmscf (KTL-05) and condensate gas ratios up to 31.02 bbl/mmscf (KTL-03). The majority of the wells in Kailashtila have been completed with 88.9 mm tubing strings as noted in Table 5.1.

Table 5.1: Summary of Kailashtila Well Production

Wells Formation Tubing Size, inches

Perforation Interval, ft Production Period

KTL-01 LGS 2 7/8 9810-9870 June 83-Jan 98 KTL-01 MGS 4 ½ 9652-9722 Feb 98-Dec 13 KTL-02 UGS 3 ½ 7390-7430 Feb 95-Dec 13 KTL-03 MGS 3 ½ 10304-10440 Mar 95-June 06 KTL-03 UGS 3 ½ 7906.8-8050 Jul 06-Dec 13 KTL-04 LGS 3 ½ 9882-9932 Mar 97-Nov 06 KTL-04 MGS 3 ½ 9614-9704 Dec 06-Dec 13 KTL-05 HRZ 3 ½ 9522.6-9557 Sep 06-Mar 09 KTL-06 UGS 4 ½ 7929.8-8087.3 Aug 07-Dec 13

The future well performance will be dictated on the rate at which the reservoir

pressure drops or the WGR increases along with Petrobangla‟s ability to maintain the

lowest possible flowing wellhead pressure. It is possible to increase a gas wells ability to lift

water by reducing the tubing size, however, this also reduces the overall recovery as the

smaller tubing can have significantly increased friction drops that results in less overall

pressure drawdown at the reservoir interface. Most often the depletion of moderate to

high permeable reservoirs can be optimized through a reduction of the well delivery

pressure to impart higher drawdown‟s and an increased ability to carry liquids at lower TPC

pressures.

5.4 Kailashtila Well Model Study – Predictions Using Prosper™

The Kailashtila well performances were simulated using a PROSPER™ Model for each well.

5.4.1 Kailashtila Well KTL-01 Study (Middle Gas Sand)

Figure 5.2 illustrates the production history for the KTL-01 Middle Gas Sand which has

been on production in February 1998 at 24.8 mmscfd with 234 bpd of condensate and 5

bpd of water at 3,139 psig. The latest reported production in March of 2012 is 13.9937

mmscfd of gas with 99.16 bpd of condensate and 5.31 bpd of water at a flowing tubing

pressure of 2,455 psig. A notable increased gas rate decline since February of 2008 may be

related to liquid loading at the current flowing tubing pressures although no major

increase in the reported water or liquid rates is yet apparent. Liquid rates should be

68

validated with testing. The plots for “flowing wellhead pressure” and “water production rate”

are discontinuous this is because the recorded data were not found in particular times for

these two parameters.

5.4.1.1 Kailashtila Well KTL-01 Inflow Model

Figure 5.3 illustrates the KTL-01 well inflow performance relationship using the

November 2007 static and multipoint flowing data. An AOF of 170.06mmscfd was

calculated with a “C” value of 2.86177 and an “n” of 0.67345 generated from the test

points at the Mid-Point of Perforation.

0

5

10

15

20

25

30

35

0

500

1000

1500

2000

2500

3000

3500

Oct-95 Jul-98 Apr-01 Jan-04 Oct-06 Jul-09 Apr-12 Dec-14

Gas

Rat

e, M

Msc

fd

Wat

er R

ate,

bbl

/day

Wel

lhea

d Pr

essu

re, P

sig

Con

dens

ate

Rat

e, b

bl/d

ay

Date

KTL-01 Middle Gas Sand Production

Condesate Rate (bbld) Flowing Well Head Pressure (Psig)

Gas Rate (MMscfd) Water Rate(bbld)

Figure 5.2: KTL-01 Middle Gas Sand Production History

69

Figure 5.3: KTL-01 November 2007 Test Inflow Performance Relationship31

Once IPR is drawn the next step is to draw the downhole configuration. To do so, deviation

surveys, geothermal gradient, downhole equipment and tubing size are specified here.

Prosper drawn the downhole configuration as the Figure 5.4 shown below for KTL-01.

In prosper, several tubing correlations are available, here tubing correlation has been checked

and it is possible to choose the best one. PROSPER uses a non-linear regression technique to

adjust the VLP correlations to best match the measured data. Gradient match results of the

test points noted the best convergence using the “Gray” Equation shown in Figure 5.5.

70

Figure 5.4: Downhole configuration for KTL-01

C:\Documents and Settings\Admin\Desktop\KTL-1(mgs).Anl

Xmas TreeTVD :

MD :

0

0

(feet)

(feet)

Tubing

N80 VAM Tube

3.958 (inches)3.958 (inches)

TVD :

MD :

146.95

146.95

(feet)

(feet)

SSSV 3.958 (inches)3.813 (inches)

TVD :

MD :

146.95

147

(feet)

(feet)

Tubing

4-1/2" 12.5


TVD :

MD :

8503.9

8503.95

(feet)

(feet)

Restriction

Sliding Door


TVD :

MD :

8503.9

8504

(feet)

(feet)

Tubing

N80 VAM Tube


TVD :

MD :

8674.85

8674.95

(feet)

(feet)

Restriction

Landing nipp


TVD :

MD :

8674.85

8675

(feet)

(feet)

Tubing

N80 VAM Tube


TVD :

MD :

8750.8

8750.95

(feet)

(feet)

Restriction 3.958 (inches)2.992 (inches)

TVD :

MD :

8750.8

8751

(feet)

(feet)

Tubing

3-1/2" 9.2P


TVD :

MD :

8761.75

8761.95

(feet)

(feet)

Restriction

Landing nipp

2.992 (inches)2.75 ( inches)

TVD :

MD :

8761.75

8762

(feet)

(feet)

Tubing 2.992 (inches)2.992 (inches)

TVD :

MD :

8771.7

8771.95

(feet)

(feet)

Casing

9 5/8" 47 PPf

8.755 (inches)

TVD :

MD :

9299.7

9299.95

(feet)

(feet)

Casing

13 Casing

6.5 (inches)

TVD :

MD :

9687

9687

(feet)

(feet)

71

Figure 5.5: KTL-01 Gradient Matching (November Test 2007)

PROSPER™ was used to calculate a bottomhole flowing pressure of 3133 psia at the

reported Dec 2012 flowing conditions of 13.9937 mmscfd at the flowing wellhead

pressure of 2,2455 psig, condensate gas ratio CGR” of 7.09 bbl/mmscf, and water gas ratio

(WGR) of 0.38 bbls/mmscf. Figure 5.6 shows the well‟s flowing gradient curve.

72

Figure 5.6: KTL-01 Dec 2012 Gradient Curve (13.9937 MMscfd @ 2,455 Psig)

The November 2007 backpressure equation (“C” and “n”) was used to back calculate a

reservoir pressure of 3,181 psig from the PROSPER™ December 2012 calculated

flowing bottomhole pressure of 3,133 psig as shown in Table 5.2. It is recommended that a

current static reservoir pressure be measured to validate this estimation.

Table 5.2: KTL-01 December 2012 Well Performance Model Prediction (Reservoir Pressure Calculation)

Gas Rate,

MMscfd

Water Rate,

bbl/day

Condensate Rate,

bbl/day

FTP, Psig

Simulated BHFP,

Psig n C

Mscfd/Psi2

Calculated Reservoir Pressure,

Psig

AOF MMscfd

13.9937 5.31 99.16 2,455 3,133 0.67345 2.86177 3,181 170.06

73

5.4.1.2 Finding out the Solution Node for the Above System

Once the best correlation has been chosen, it can proceed for finding the solution node with

the best correlation found in previous steps. Prosper compare the calculated and measured gas

rate and bottomhole pressure. If the error is within 10%, it can choose the model as normal;

however, various steps tried to minimize the error by tuning the IPR curve. Figure 5.7 shows

the selected solution node.

Figure 5.7: IPR/VLP Matching for KTL-01

74

5.4.1.3 Sensitivity Analyses

Figure 5.8 illustrates the predicted KTL-01 December 2012 conditions with sensitivities to

top Node Pressure (wellhead pressure) and Reservoir Pressure. Using the calculated inflow

performance relationship for KTL-01, an acceptable range of flows up to 87mmscfd are

available up the current tubing string at a tubing pressure of 250 psig for the calculated

reservoir pressure of 3,181 psig. The IPR/VLP plot shows that 13 mmscfd could be

maintained from the well down to a reservoir pressure of 750 psig for the current reported

WGR and CGR.

On the other hand, if the tubing diameter is changed to 3 ½ inches the highest flow rate

remain about same as tubing diameter 4.5 inches at same reservoir and top node pressure.

The minimum gas rates will be 17 mmscfd at reservoir pressure 1000 psig and top node

pressure 500 psig shown in Figure 5.9.

Figure 5.10 illustrates the predicted Inflow / Outflow curve intersection points for the KTL-

01 well with varying water gas ratios (WGR) at current operated wellhead and

reservoir pressures. The predicted rates are affected considerably as the tubing lift curves

shift to the left at increased WGR‟s. At a very minimal LGR of 0.05bbls/mmscf no

intersection point is noted at current operating conditions, the well is predicted to load up and

stop producing. This illustrates the importance of measuring and tracking the individual well

gas and liquid rates on a consistent basis so as to be able to predict when each well will load

up.

75

Figure 5.8: KTL-01 Rate Sensitivities to Reservoir and First Node Pressure

Legend

First Node Pressure (Psig)

1=250 2=500 3=1000 4=1500 5=2000

6=2675

76

Figure 5.9: KTL-01 Model Sensitivities to Reduced Tubing Diameter to 3 ½ inches

Legend


1=250 2=500 3=1000 4=1500 5=2000

6=2675

77

Figure 5.10: KTL-01 Model Sensitivities to Water Gas Ratio (3181 Psig Reservoir Pressure and First Node Pressure 2675 Psig)

Legend

Water G

as Ratio (STB

/MM

scf) 1=1500 2=1000 3=800 4=400 5=200 6=100 7=10

8=0

78

5.4.2 Kailashtila Well KTL-02 Study (UPPER GAS SAND)

The KTL-02 well was placed on production in February of 1995 from the Upper Gas Sand

at reported rates of 6 mmscfd with 104 bpd of condensate and no reported water.

Latest reported production from December 2012 is at 18.015 mmscfd of gas with 153.22 bpd

of condensate and 3.25 bpd of water at a flowing tubing pressure of 2,355 psig. Figure 5.11

shows the KTL-02 production decline over the course of its life. Gas rates and wellhead

pressures have been relatively stable suggesting very gradual depletion of the reservoir

pressure. It may be possible to increase well off take dramatically at this location. The plots

for “flowing wellhead pressure” and “water production rate” are discontinuous this is because

the recorded data were not found in particular times for these two parameters

Figure 5.11: KTL-02 Upper Gas Sand Production History



November 2007 static and multipoint flowing data. An AOF of 580.204 mmscfd was



0

5

10

15

20

25

30

35

40

0

500

1000

1500

2000

2500

3000

Jan-93 Jul-98 Jan-04 Jul-09 Dec-14W

ater

Rat

e, b

bl/d

ay

Gas

Rat

e, M

Msc

fd

Wel

lhea

d Pr

essu

re, P

sig

Con

dens

ate

Rat

e, b

bl/d

ay

Date

KTL-02 Upper Gas Sand Production

wellhead Pressure, Psig Condensate Rate, bbl/day

Gas Rate, MMscfd Water Rate, bbl/day

79

Figure 5.12: KTL-02 November 2007 Test Inflow Performance Relationship







test points noted the best convergence using the “Petroleum Experts 3, Pressure”

equation shown in Figure 5.14.

IPR PlotPre

ssure

(Psig

)

3,200

3,100

3,000

2,900

2,800

2,700

2,600

2,500

2,400

2,300

2,200

2,100

2,000

1,900

1,800

1,700

1,600

1,500

1,400

1,300

1,200

1,100

1,000

900

800

700

600

500

400

300

200

100

0

Rate (MMscf/day)

550500450400350300250200150100500

AOF : 580.204 (MMscf/day)AOF : 580.204 (MMscf/day)

C : 1.2398 (Mscf/day/Psi2)C : 1.2398 (Mscf/day/Psi2)

n : 0.80821n : 0.80821

80


I:\Mizan_0412132025\M.Sc\KTL_02.Anl

Xmas Tree

TVD :

MD :

0

0

(feet)

(feet)

Tubing

3 1/2" New V 2.673 (inches)2.673 (inches)

TVD :

MD :

177.115

177.115

(feet)

(feet)

SSSV2.673 (inches)2.313 (inches)

TVD :

MD :

177.115

177.165

(feet)

(feet)

Tubing

3 1/2" New V2.673 (inches)2.673 (inches)

TVD :

MD :

7247.9

7247.95

(feet)

(feet)

Restriction2.673 (inches)2.313 (inches)

TVD :

MD :

7247.9

7248

(feet)

(feet)

Casing

7" 32ppf, 46.094 (inches)

TVD :

MD :

7390

7390

(feet)

(feet)

81


PROSPER™ was used to calculate a bottomhole flowing pressure of 3063 psig at the



(WGR) of 0.18bbls/mmscf. Figure 5.15 shows the well‟s flowing gradient curve.

82

Figure 5.15: KTL-02 Dec 2012 Gradient Curve (18.0315 MMscfd @ 2,355 Psig)






Gas Rate,

MMscfd

Water Rate,

bbl/day

Condensate Rate,

bbl/day

FTP, Psig

Simulated BHFP,

Psig n C

Mscfd/Psi2


Psig

AOF MMscfd

18.0315 3.25 153.22 2,355 3,040 0.80821 1.2398 3,063 580.204

83








84



first Node Pressure and Reservoir Pressure. Using the calculated inflow performance

relationship for KTL-02, an acceptable range of flows up to 44mmscfd are available up the

current tubing string at a tubing pressure of 250 psig for the calculated reservoir pressure of

3,063 psig. The IPR/VLP plot shows that 06mmscfd could be maintained from the well down

to a reservoir pressure of 750 psig for the current reported WGR and CGR.

On the other hand if the tubing diameter is changed to 4 ½ inches the highest flow rate

increased to 132 mmscfd at same reservoir and top node pressure. The minimum gas rates

will be 12mmscfd at reservoir pressure 500 psig and top node pressure 250 psig shown in

Figure 5.18.



reservoir pressures. No intersection points are noted for 50 bbls/mmscf of WGR as the

tubing lift curves shift upward at increased WGR‟s due to higher fluid densities. If WGRs

increase over time, the well could load up and stop producing if the flowing wellhead

pressure is not reduced.

85


Legend


1=250 2=500 3=750 4=1000 5=1500 6=2000 7=2320

86

Figure 5.18: KTL-02 Model Sensitivities to Increase Tubing Diameter to 4 ½ inches

Legend


1=250 2=500 3=750 4=1000 5=1500 6=2000 7=2320

87

Figure 5.19: KTL-02 Model Sensitivities to Water Gas Ratio (3181 Psig Reservoir Pressure and Top Node Pressure 2320 Psig)

Legend

Water G

as Ratio (STB

/MM

scf) 1=500 2=200 3=100 4=20 5=15 6=10 7=5 8=0

88


Figure 5.20 illustrates the production history for the KTL-03 Upper Gas Sand which has been

on production in July2006 at 6 mmscfd with 50 bpd of condensate and no measured water.

The latest reported production in December of 2012 is 5.1424 mmscfd of gas with 128.66

bpd of condensate and 1.82 bpd of water at a flowing tubing pressure of 2,630 psig. A notable

increased gas rate decline since February of 2008 may be related to liquid loading at

the current flowing tubing pressures although no major increase in the reported water

or liquid rates is yet apparent. Liquid rates should be validated with testing.


Without multi-rate test results a range of Absolute Open Flow Potential (AOFP) is possible

based on assumed “n” values between 0.5 and 1.0 as shown in Table 5.4. Based on the

prosper calculated bottomhole flowing pressure for November 2007 measured rates and the

extrapolated reservoir pressure 3,291 psig that was determined at that time from KTL-03,

calculated AOFs range from 58 mmscfd (n=0.5) to 240 mmscfd (n=1.0).

Figure 5.20: KTL-03 Upper Gas Sand Production History

0

5

10

15

20

25

30

0

500

1000

1500

2000

2500

3000

May-05 Oct-06 Feb-08 Jul-09 Nov-10 Apr-12 Aug-13G

as R

ate,

MM

scfd

W

ater

Rat

e, b

bl/d

ay

Wel

lhea

d Pr

essu

re,

Psig

C

onde

nsat

e R

ate,

bbl

/day

Date

KTL-03 Upper Gas Sand production

Wellhead Pressure, Psig Condensate Rate, bbl/day


89

Table 5.4: KTL-03 November 2007 Backpressure Equation Calculations

Gas

Rate

mmscfd

WGR

Bbls

/mmscf

CGR

bbls/

mmscf

FWHP

Psig

Reservoir

Pressure

Psig

BHFP

at

7978

ft, KB

Psig

C

(mmscfd)

/psi2

n=0.5

AOF

C

(mmscfd)

/psi2

n=0.7

AOF

C

(mmscfd)

/psi2

n=1.0

AOF

14.24 0.13 8.10 2490 3,232 3,135 0.018 58 1.26E-3 103 2.3E-5 240

Figure 5.21 illustrates the resulting 2007 KTL-03 well inflow performance relationship

derived from Prosper using the values form Table 5.4. An AOF of 190.792 mmscfd was

calculated with a “C” value of 0.11408 (mmscfd/psi2) and an “n” of 0.88671.

Figure 5.21: KTL-03 November 2007 Production Inflow Performance Relationship

IPR Plot

Pre

ssure

(Psig

)

3,200

3,100

3,000

2,900

2,800

2,700

2,600

2,500

2,400

2,300

2,200

2,100

2,000

1,900

1,800

1,700

1,600

1,500

1,400

1,300

1,200

1,100

1,000

900

800

700

600

500

400

300

200

100

0

Rate (MMscf/day)

180160140120100806040200

AOF : 190.792 (MMscf/day)

C : 0.11408 (MMscf/day/Psi2)

n : 0.88671

90







test points noted the best convergence using the “Gray” equation shown in Figure 5.23.



Xmas TreeTVD :

MD :

0

0

(feet)

(feet)

Tubing

3 1/2" New V


TVD :

MD :

176.936

177.115

(feet)

(feet)

Restriction

SSSV Landing


TVD :

MD :

176.936

177.165

(feet)

(feet)

Tubing

3 1/2" New V


TVD :

MD :

1064.92

1066

(feet)

(feet)

Tubing

3 1/2" New V


TVD :

MD :

1227.76

1230

(feet)

(feet)

Tubing

3 1/2" New V


TVD :

MD :

1542.01

1548

(feet)

(feet)

Tubing

3 1/2" New V


TVD :

MD :

7260.77

7767.96

(feet)

(feet)

Restriction

SSD


TVD :

MD :

7260.77

7768.01

(feet)

(feet)


TVD :

MD :

7267.86

7775.54

(feet)

(feet)

Casing

9 5/8" 43.5

8.681 (inches)

TVD :

MD :

7332.32

7844

(feet)

(feet)

Casing

9 5/8" 43.5

8.681 (inches)

TVD :

MD :

7391.44

7906.8

(feet)

(feet)

91


Table 5.5 shows the December reservoir pressure determination at KTL-03 well for the

Upper Gas Sand. A Prosper calculated flowing bottomhole pressure of 3,291 psig at the

flowing conditions of 15.1424 mmscfd was used to back calculate a 3,291.04 psig reservoir

pressure from the KTL-03 IPR backpressure equation. The calculated pressure is an increase

from the November 2007 measurement of 3,232 psia and is higher than the December 2012

calculated reservoir pressure from KTL-02 of 3,063 psig. Errors in the calculations can be

attributed to errors in flow measurement, an uncalibrated well model, and a lack of

multiple flow points to define the IPR effectively. Figure 5.24 shows the well‟s flowing

gradient curve.

92


Gas Rate,

MMscfd

Water Rate,

bbl/day

Condensate Rate,

bbl/day

FTP, Psig

Simulated BHFP,

Psig n C

Mscfd/Psi2


Psig

AOF MMscfd

15.1424 1.82 128.66 2,630 3,391 0.88671 0.11408 3,291.04 190.792

Figure 5.24: KTL-03 Dec 2012 Gradient Curve (15.2414MMscfd @ 2,630 Psig)

93








94






3,291 psig. The IPR/VLP plot shows that 7 mmscfd could be maintained from the well down


On the other hand if the tubing diameter is changed to 4 ½ inches the highest flow rate will be

75 at same reservoir and top node pressure. The minimum gas rates will be 12 mmscfd at

reservoir pressure 1000 psig and top node pressure 500 psig shown in Figure 5.27.




shift to the left at increased WGR‟s. No intersection point is noted at current operating

conditions for LGR 10bbls/mmscf, the well is predicted to load up and stop producing. This

illustrates the importance of measuring and tracking the individual well gas and liquid rates

on a consistent basis so as to be able to predict when each well will load up.

95


Legend


1=100 2=250 3=500 4=750 5=1000 6=1500 7=2000

8=2525

96

Figure 5.27: KTL-03 Model Sensitivities to Increased Tubing Diameter to 4 ½ inches

Legend


1=100 2=250 3=500 4=750 5=1000 6=1500 7=2000

8=2525

97

Figure 5.28: KTL-03 Model Sensitivities to Water Gas Ratio (3,291 Psig Reservoir Pressure)

Legend

Water G

as Ratio (STB

/MM

scf) 1=500 2=200 3=50 4=20 5=10 6=5 7=0

98

5.4.4 Kailashtila Well KTL-04 Study (MIDDLE GAS SAND)

Figure 5.29 illustrates the production history for the KTL-04 Middle Gas Sand which has

been on production in December 2006 at 12.55 mscfd with 8.4 bpd of condensate and 0.56

bb/mmscf measured water. The latest reported production in December of 2012 is 16.6264

mmscfd of gas with 173.96 bpd of condensate and 1.55 bpd of water at a flowing tubing

pressure of 2,860 psig. Flowing tubing pressures have declined slightly as have the gas rates.

The plots for “flowing wellhead pressure” and “water production rate” are discontinuous this

is because the recorded data were not found in particular times for these two parameters



November 2007 static and multipoint flowing data. An AOF of 208.099 mmscfd was




0

2

4

6

8

10

12

14

16

18

20

0

500

1000

1500

2000

2500

3000

May-05 Oct-06 Feb-08 Jul-09 Nov-10 Apr-12 Aug-13G

as R

ate,

MM

scfd

W

ater

Rat

e, b

bl/d

ay

Wel

lhea

d Pr

essu

re, P

sig

Con

dens

ate

Rat

e, b

bl/d

ay

Date

KTL-04 Middle Gas Sand Production



99








test points noted the best convergence using the “Gray” equation shown in Figure 5.32.

100

Figure 5.31: Downhole Configuration for KTL-04

I:\MSc Thesis\Prosper\Copy of KTL_04.Anl

Xmas Tree

TVD :

MD :

0

0

(feet)

(feet)

Tubing

3 1/2" 9.2


TVD :

MD :

157.863

157.863

(feet)

(feet)


TVD :

MD :

157.863

157.913

(feet)

(feet)

Tubing

3 1/2" 9.2


TVD :

MD :

8666.47

8666.52

(feet)

(feet)

Restriction

Sliding Door


TVD :

MD :

8666.47

8666.57

(feet)

(feet)

Tubing 2.97 ( inches)2.97 ( inches)

TVD :

MD :

8705.03

8705.13

(feet)

(feet)


TVD :

MD :

8740.01

8740.11

(feet)

(feet)

Casing

7" Liner 32P

6.094 (inches)

TVD :

MD :

9612.86

9612.86

(feet)

(feet)

101


PROSPER™ was used to calculate a bottomhole flowing pressure of 3666 psig at the



(WGR) of 0.09 bbls/mmscf. Figure 5.33 shows the well‟s flowing gradient curve.

102


Table 5.6 shows the December 2012 reservoir pressure determination of 3,709 psig for the

Middle Gas Sand from the KTL-04 IPR backpressure equation and the Prosper model

calculated flowing bottmhole pressure of 3,666 psig at the flowing conditions of 16.6264

mmscfd.


Gas Rate,

MMscfd

Water Rate,

bbl/day

Condensate Rate,

bbl/day

FTP, Psig

Simulated BHFP,

Psig n

C Mscfd/Psi2


Psig

AOF MMscfd

16.6264 1.55 173.96 2,860 3,666 0.69738 2.37422 3,709 208.099

103








104

4.4.4.3 Sensitivity Analysis



relationship for KTL-04, an acceptable range of flows up to 42 mmscfd are available up the



to a reservoir pressure of 1,000 psig for the current reported WGR and CGR.



The minimum gas rates will be 09mmscfd at reservoir pressure 1000 psig and top node





shift to the left at increased WGR‟s. At a very minimal LGR of 20 bbls/mmscf no




up.

105


Legend


1=250 2=500 3=750 4=1000 5=1500 6=2000 7=2650

106

Figure 5.36: KTL-04 Model Sensitivities to Increased Tubing Diameter to 4 ½ inches

Legend


1=250 2=500 3=750 4=1000 5=1500 6=2000 7=2650

107

Figure 5.37: KTL-04 Model Sensitivities to Water Gas Ratio (3,709 Psig Reservoir Pressure and 2650 Psig Top Node Pressure)

Legend

Water G

as Ratio (STB

/MM

scf) 1=500 2=200 3=50 4=20 5=10 6=5 7=0

108


The well was placed on production in August 2007 and initial reported rates were 14.9

mmscfd gases with 122 bpd of condensate and 4.8 bpd of water. Current production from the

Upper Gas Sand is 22.3811mmscfd of gas, 190.27 bpd of condensate and 2.91 bpd of

water production at the current wellhead operating pressure of 2,600 psig. Figure 5.38

shows the KTL-06 production from the Upper Gas Sand over the course of its life.


Figure 5.39 illustrates the KTL-06 well inflow performance relationship. An AOF of

331.303 mmscfd was calculated with a “C” value of 0.19106 and an “n” of 0.88755

generated from the test points at the Mid Point of Perforation.


0

5

10

15

20

25

30

0

500

1000

1500

2000

2500

3000

Oct-06 Feb-08 Jul-09 Nov-10 Apr-12 Aug-13

Gas

Rat

e, M

Msc

fd

Wat

er R

ate,

bbl

/day

Wel

lhea

d Pr

essu

re, P

sig

Con

dens

ate

Rat

e, b

bl/d

ay

Date

KTL-06 Upper Gas Sand



109








test points noted the best convergence using the “Petroleum Experts 4, Pressure”

equations shown in Figure 5.41.

110



Xmas TreeTVD :

MD :

0

0

(feet)

(feet)

Tubing

N-80 4 1/2"


TVD :

MD :

108.972

108.972

(feet)

(feet)


TVD :

MD :

108.972

109.022

(feet)

(feet)


TVD :

MD :

1722.44

1722.44

(feet)

(feet)


TVD :

MD :

1810.96

1811.02

(feet)

(feet)


TVD :

MD :

2193.34

2194.88

(feet)

(feet)


TVD :

MD :

7201.35

7634.89

(feet)

(feet)

Restriction

SSD


TVD :

MD :

7201.35

7634.94

(feet)

(feet)

Tubing

N-80 4 1/2"


TVD :

MD :

7236.64

7672.26

(feet)

(feet)

Tubing

3.5" 9.3 p


TVD :

MD :

7264.49

7701.72

(feet)

(feet)

Casing

7" Liner

6.094 (inches)

TVD :

MD :

7436.75

7883.86

(feet)

(feet)

111


The December 2012 flowing conditions of 22.3811mmscfd at 2,600 psig wellhead flowing pressure with a CGR of 8.50bbl/mmscf and a WGR of 0.13bbl/mmscf were modeled in Prosper to produce a bottomhole flowing pressure of 3,094 psia. Figure 5.42 shows the Prosper generated flowing gradient curve at these conditions.

112






Table 5.7: KTL-06 December 2012 Well Performance Model Prediction (Reservoir Pressure Calculation)

Gas Rate,

MMscfd

Water Rate,

bbl/day

Condensate Rate,

bbl/day

FTP, Psig

Simulated BHFP,

Psig n

C Mscfd/Psi2


Psig

AOF MMscfd

22.3811 2.91 190.27 2,600 3,094 0.88755 0.19106 3,176 331.303

113

5.4.5.2 Finding out the Solution Node for the above System







114










The minimum gas rates will be 05mmscfd at reservoir pressure 500 psig and top node





shift to the left at increased WGR‟s. At a very minimal LGR of 20bbls/mmscf no




up dictate.

115


Legend


1=250 2=500 3=750 4=1000 5=1500 6=2000 7=2650

116

Figure 5.45: KTL-06 Model Sensitivities to Reduced Tubing Diameter to 3 ½ inches

Legend


1=250 2=500 3=750 4=1000 5=1500 6=2000 7=2650

117

Figure 5.46: KTL-06 Model Sensitivities to Water Gas Ratio (3,176 Psig Reservoir Pressure)

Legend

Water G

as Ratio (STB

/MM

scf) 1=500 2=200 3=50 4=20 5=10 6=5 7=0

118

CHAPTER VI

HISTORY MATCHING AND PRODUCTION PREDICTION

The aim of this study is to find out or recalculate the Original Gas In Place (OGIP) for all the

three gas zones of Kailashtila Gas Field (namely Upper Gas Sand, Middle Gas Sand and

Lower Gas Sand) after quality checking of available data. The quality check is based on what

is physically possible and focused towards determining inconsistencies between data and

physical reality. It is now 31 years before production started from the Kailashtila Gas Field.

This study will try to check the existence of any aquifer support within the reservoir and its

consequences on gas reserve estimation and gas production. Once calculation of the OIGP

has been completed, then it will be compared with the reserve previously calculated by other

studies. Then it will prepare the history match model for forecasting (Fractional Flow

Matching) and production forecasting would be done by MBAL.

Material balance methods e.g Havlena-Odeh32 are important reservoir engineering tool for

estimating OGIP/OOIP and aquifer parameters for water drive reservoirs. A material balance

approach can also be used to predict reservoir pressure once OGIP/OOIP and aquifer

parameters are known. The results from procedure are however, only as accurate as the water

influx calculations for the reservoir.

Van Everdingen and Hurst29 presented a formula that is commonly used to calculate water

influx.

6.1 MBAL Material Balance Tool This incorporates the classical use of Material Balance calculations for history matching

through graphical methods (like Havlena-Odeh, Cambel, Analytical Method, Cole and so on).

Detailed PVT models can be constructed (black oil and compositional) for oils, gases and

condensates. Furthermore, predictions can be made with or without well models and using

relative permeabilites to predict the amount of associated phase productions.

In this study, workflow of Material balance Study given below.

1. Check for appropriate data availability

PVT

Production History

Reservoir Average Pressure history

All data of Reservoir and Aquifer

119

2. After entering the data, it can check the validity and consistency of all data in every

step.

3. Finding the possible match using the MBAL‟s non-linear regression, the „Analytical

Method‟.

4. Confirming the quality and correctness of the match, using the „Graphical Method‟.

5. Running a simulation to test the validity of the match.

6. Production prediction.

6.2 History Matching for Upper Gas Sand

After providing all necessary inputs in production history, next step is to proceed for the

history matching. In this section, the investigation of the behavior of the various plots such as

Cole plot, Energy plot and Analytical method.

Figure 6.1 is the “Cole plot33” for the Upper Gas Sand of Kailashtila Gas Field. The Cole plot

is a useful tool for distinguishing between water drive and depletion drive reservoirs. The plot

is derived from the Havlena-Odeh33 Equation, F = GEg+WeBw for water drive gas reservoir.

Where,

F = Production terms = GpBg + BwWp

G = Initial reservoir gas, scf

Eg = Expansion of gas = Bg- Bgi

Bg = Gas formation volume factor, ft3/scf

Wp = Cumulative produced water, STB

Bw = Water formation volume factor, bbl/STB

Gp = cumulative produced gas, scf

We = Water influx into reservoir, bbl

Rearranging the Equation F = GEg+WeBw becomes

. After constructing a

plot of F/Eg versus Gp (gas production), it should get a horizontal straight line intersecting

the Y-axis from the Cole plot and all data points should lie on that straight line for depletion

drive gas reservoir. This intersecting point gives the value of OIGP.

Here the input data points (11, 16, and 25) for the Upper Gas Sand of Kailashtila Gas Field

are not align to horizontal straight line and overestimated the OIGP value. It is an indication

of the presence of water drives.

120

Energy Plot: This plot shows the relative contributions of the main source of energy in the

reservoir and aquifer system. It does not in itself provide the user with detailed information,

but indicates very clearly which parameters and properties should be focused on (i.e. PVT,

Formation Compressibility, and Water Influx). The energy plot shows the relative importance

of each drive mechanism in the model35.

The energy plot (Figure 6.2) shows that there are three sources of energy for gas production

as Fluid Expansion, PV Compressibility and Water Influx. Among these three energy sources

the Pore Volume (PV) Compressibility is near about negligible, the Fluid Expansion is largest

one and the Water Influx has also a great contribution.

0 40000 80000 12000 0 16000 0

0

1.5e+ 6

3e+6

4.5e+ 6

6e+6

Metho d : Cole - No Aquife r (F/Et) - Kailashti la

Gp (M Mscf)

F/Et (MMscf)

T a n k Temperatur e 147.8 (deg F)Tank Pressure 3332 (psi g)Tank Porosity 0.28 (fra ction)

Conna te Water S aturation 0.15 (fra ction)Water Compressi bility Use C orr (1/p si)

Forma tion Compr essibility 3.206 15e-6 (1/p si)Gas i n Place 1.801 37e+6 (MMs cf)

Produ ction Star t 06/28 /1983 (dat e m/d/y)

Aquif er Model Hurst -van Everd ingen-Modi fiedAquif er System Radia l Aquifer

Outer /Inner Rad ius 14.74 12 Encro achment An gle 332.2 71 (deg rees)

Calc. Aquifer V olume 1.727 27e+6 (MMf t3)Aquif er Permeab ility 182.3 02 (md)

Tank Thickness 179 (fee t)Tank Radius 7900 (fee t)

1

11

16

25

Figure 6.1: Cole Plot for Upper Gas Sand34

121

Analytical Method: The analytical plot shows the Reservoir Pressure vs. Cum Production

from the historical data and the model .This method uses a non-linear regression engine to

assist in estimating the unknown reservoir and aquifer parameters. This method is plot based,

i.e. the response of the model is plotted against historical data. The parameters to select for

regression will be the ones least trusted or the ones for which values were assumed rather

than measured. At the end of regression the values for which the best match is achieved are

displayed36.

The analytical plot (Figure 6.3) is showing that there is a great variation between the straight

line of simulated data and real field history data points. This deviation may due to the effect

12/31/1983 07/01/1991 12/31/1998 07/01/2006 12/31/2013

0

0.25

0.5

0.75

1

Drive Mechanism - Kailashtila

Time (date m/d/y)

Tank Temperature 147.8 (deg F)Tank Pressure 3332 (psig)Tank Porosity 0.28 (fraction)

Connate Water Saturation 0.15 (fraction)Water Compressibility Use Corr (1/psi)

Formation Compressibility 3.20615e-6 (1/psi)Gas in Place 1.80137e+6 (MMscf)

Production Start 06/28/1983 (date m/d/y)

Aquifer Model Hurst-van Everdingen-ModifiedAquifer System Radial Aquifer

Outer/Inner Radius 14.7412 Encroachment Angle 332.271 (degrees)

Calc. Aquifer Volume 1.72727e+6 (MMft3)Aquifer Permeability 182.302 (md)

Tank Thickness 179 (feet)Tank Radius 7900 (feet)

Fluid ExpansionPV CompressibilityWater Influx

Figure 6.2: Ratio of Different Drive Mechanism for Upper Gas Sand

122

of aquifer acting. Therefore, a step tunes the analytical method with adding aquifer influx

model.

0 40000 80000 120000 160000

3200

3240

3280

3320

3360

Analytical Method

Calculated Gas Production (MMscf)

Tank

Pre

ssur

e (p

sig)





Aquifer Model NoneAquifer System Radial Aquifer

Match Points Status :OffHighMediumLow

Figure 6.3: Analytical Method for Upper Gas Sand34

123

An aquifer model is added to the tank and the regression is performed on the analytical plot

as shown in Figure 6.4. The selection of aquifer model was the trial and error method. The

best fitted aquifer model for Kailashtila Gas Field is Hurst-Van Everdingen model which is

applicable for radial and infinite acting aquifer system. This gives a GIIP approximately

1.8Tscf. The Figure 6.4 shows a great difference between the Analytical method with Aquifer

Influx and without Aquifer Influx which indicates an active aquifer model for the Kailashtila

Upper Gas Sand.

Figure 6.4: Analytical Method Comparison with and without Aquifer Influx Model

Hence, the above three methods (Cole plot, Analytical method and Energy plot) indicate the

existence of external water drives within the Kailashtila Gas field.

0 40000 80000 120000 160000

3200

3240

3280

3320

3360

Analytical Method - Kailashtila


Tank

Pre

ssur

e (p

sig)







Calc. Aquifer Volume 1.72727e+6 (MMft3)Aquifer Permeability 182.302 (md)


with Aquifer Influxwithout Aquifer Influx


124

The next step in MBAL is running a simulation. A simulation was run to check the validity of

the results obtained by Analytical and Graphical methods. The technique was used in MBAL

by calculating the average reservoir pressure, production history, and reservoir/aquifer model

parameters. Then, pressure and production histories were matched. The history matches are

shown in Figure 6.5 and Figure 6.6. Figure 6.5 shows the history matching of pressure and

gas production from the start in1983 to 2013 for Upper Gas Sand. Gas production history

excellently matched with simulated data. Pressure history also matched well with a slight

(negligible) deviation. This deviation may due to the lacking of enough pressure data. Figure

6.6 shows the history matching of water production and it is well matched between historical

data and simulated data.

Figure 6.5: History Matching of Gas Production and Pressure of Upper Gas Sand

125

Figure 6.6: History Matching of Water Production and Pressure of Upper Gas Sand

126

Once water drive has been identified, now it should examine whether the selected aquifer

model was correct or not. This can be done by a method described by Bruns et.al37. The

procedure of this method is explained below.

The depletion drive material balance Equation30

can be solved for determining

the apparent gas in place as

(

) …………………………………………...…….. (32)

For active water drive the successive calculated values of Ga will increase as the deviation of

P/Z above the depletion material balance line increases, due to the pressure maintenance

provided by the aquifer. The correct value of the gas in place can be obtained from

Equation30, ( ) . After rearranging this equation becomes,

(

)

………………………………………………..……………………… (33)

Subtracting equation 32 from equation 31 gives,

…..………………………………………………………………… (34)

If the calculated values of Ga, Equation (31) are plotted as a function of WeE/(1-E/Ei) the

result should be a straight line, provided the correct aquifer model has been selected.

Figure 6.7 shows the aquifer model selection process for Upper Gas Sand of Kailashtila Gas

Field. As the plot of (

) versus

yield a straight line on Figure 6.7, so the correct

aquifer model has been selected30.

0

1000000

2000000

3000000

4000000

5000000

6000000

7000000

0 200000 400000 600000 800000 1000000

Ga=

Gp

/(1-E

/Ei)

WeE/(1-E/Ei)

UGS

Figure 6.7: Determination of GIIP in a Water Drive Gas Reservoir by Selecting Correct Water Model30

127

6.3 History Matching for Middle Gas Sand (MGS)

For the Middle Gas Sand all procedures will not describe in details here like Upper Gas Sand

as before but showing the main features graphically.

The Figure 6.8 shows that there are three sources of energy for gas production as Fluid

Expansion, PV Compressibility and Water Influx. Among these three energy sources the PV

Compressibility is near about negligible, the Fluid Expansion is largest one and the Water

Influx is not so strong but it is active and has contribution to gas production.

12/31/1995 06/30/2000 12/30/2004 07/01/2009 12/31/2013

0

0.25

0.5

0.75

1

Drive Mechanism

Time (date m/d/y)

Tank Temperature 168 (deg F)Tank Pressure 4239 (psig)Tank Porosity 0.182444 (fraction)


Formation Compressibility 3.64334e-6 (1/psi)Gas in Place 716272 (MMscf)




Calc. Aquifer Volume 73703.1 (MMft3)Aquifer Permeability 22.7901 (md)

Tank Thickness 69.3098 (feet)Tank Radius 7114.48 (feet)


Figure 6.8: Ratio of Different Drive Mechanism for MGS

128

The Figure 6.9 shows a great difference between the Analytical method with Aquifer Influx

and without Aquifer Influx which indicates an active aquifer model for the Kailashtila Middle

Gas Sand.

0 50000 100000 150000 200000

3400

3675

3950

4225

4500

Analytical Method


Tank

Pre

ssur

e (p

sig)








Tank Thickness 69.3098 (feet)Tank Radius 7114.48 (feet)



Figure 6.9: Analytical Method Comparison with and without Aquifer Model for MGS

129

The history matches are shown in Figure 6.10 and Figure 6.11. Figure 6.10 shows the history

matching of pressure and gas production from the start in1995 to 2013 for Middle Gas Sand.

Both the Gas production history and pressure history are excellently matched with simulated

data. Figure 6.11 shows the history matching of water production and it is well matched

between historical data and simulated data.

Figure 6.10: Gas Production History Matching for MGS

Figure 6. 11: Water Production History Matching for MGS

130

Figure 6.12 shows the aquifer model selection process for Middle Gas Sand of Kailashtila

Gas Field. As the plot of (

) versus

yield a straight line on Figure 6.12, so the

correct aquifer model has been selected30.

700000

750000

800000

850000

900000

950000

1000000

0 10000 20000 30000 40000 50000

Ga=

Gp/

(1-E

/Ei)

(WeE)/(1-(E/E)

MGS

Figure 6.12: Selecting Correct Water Model and Determination of GIIP in Water Drive Reservoir

131

6.4 History Matching for Lower Gas Sand (LGS)

For the Lower Gas Sand all procedures have not been described in details here like Upper

Gas Sand as before but showing the main features graphically.

The Figure 6.13 shows that there are three sources of energy for gas production as Fluid

Expansion, PV Compressibility and Water Influx. Among these three energy sources the PV

Compressibility is near about negligible, the Fluid Expansion is largest one and the Water

Influx is not so strong but it is active and has contribution to gas production.

12/31/1983 09/30/1989 07/01/1995 03/31/2001 12/31/2006

0

0.25

0.5

0.75

1

Drive Mechanism - Kailshtilla

Time (date m/d/y)










Figure 6.13: Ratio of Different Drive Mechanism for LGS

132

The Figure 6.14 shows a great difference between the Analytical method with Aquifer Influx

and without Aquifer Influx which indicates an active aquifer model for the Kailashtila Lower

Gas Sand.

Figure 6. 14: Analytical Method Comparison with and without Aquifer Model for LGS

0 10000 20000 30000 40000

3800

4000

4200

4400

4600

Analytical Method - Kailshtilla


Tank

Pre

ssur

e (p

sig)











133

The history matches are shown in Figure 6.15 and Figure 6.16. Figure 6.15 shows the history

matching of pressure and gas production from the start in1983 to 2013 for Lower Gas Sand.

Both the Gas production history and pressure history are excellently matched with simulated

data. Figure 6.16 shows the history matching of water production and it is well matched

between historical data and simulated data.

A near about horizontal straight line is seen in both the Figure 5.15 and 5.16 this is because

gas production were about same in 1995 and 1996.

Figure 6.15: Gas Production History Matching for LGS

134

Figure 6.17 shows the aquifer model selection process. As the plot of (

) versus (

)

yield a straight line on Figure 6.17, so the correct aquifer model has been selected.

Figure 6.16: Water Production History Matching for LGS

190000

200000

210000

220000

230000

240000

250000

260000

3000 5000 7000 9000 11000

Ga=

Gp/

(1-E

/Ei)

(WeE)/(1-E/Ei)

LGS

Figure 6.17: Selecting Correct Water Model and Determination of GIIP in Water Drive Reservoir

135

6.5 Predicting the Future Performance

To predict the future performance with material balance, a procedure is followed using a

discrete time steps. By this time, MBAL optimizer will calculate a static reservoir pressure at

the end of the discrete time step. Once estimated reservoir has been established it will

proceed for new time steps and predicting the reservoir for next time step.

This study will discuss several field production strategies starting from 2014 to 2035over a

period of 22 years by MBAL. Predictions are run with a time steps of 4 per year.

Once the prediction has been completed for the current conditions for Upper Gas Sand and

Middle Gas Sand, then changing different production strategies, run the prediction for

different possible cases and try to investigate the behavior and difference between the

production strategies by different graphical results.

The different production plans are as follows.

Production prediction based on current plant conditions

Production prediction by two more infill drilling in the Upper Gas Sand

Factors Considered in Predicting Future Performance of the Reservoir:

i. Reservoir pressure only from production schedule

ii. Thumb Rule: total prediction time will be the half life of production history

iii. Condensate gas ratio (CGR) usually correlates considering the past reservoir

performance

In the following sections, the all possible results for the mentioned cases with graphical

representation are discussed.

136

6.5.1 Production Prediction for Upper Gas Sand

Before making prediction it should find out when water breakthrough will happen as it is

water drive reservoir. Water breakthrough can be determined from “Fractional Flow Curve

Matching (Fw matching)”. The purpose behind this tool was to generate a set of Corey

function parameters that would give the same fractional flows at given saturations while

running the simulation. Corey function assumes the wetting and non-wetting phase-relative

permeabilities to be independent of the saturations of the other phases and requires only a

single suite of gas/oil-relative permeability data. Fw matching curve generated using

fractional flow of water (Fw) versus water saturation.

The Figure 6.18 below indicates that the water breakthrough will happen at the water

saturation of 0.44. The Figure 6.19 below shows this water saturation (0.44) will be in 2034.

Figure 6.18: Fw flow matching curve for determining of water breakthrough30

0 0.25 0.5 0.75 1

0

0.25

0.5

0.75

1

Fw Matching - Tank

Water Saturation

Fractional Flow

Match Points Status :

Off High

Medium Low

Water Breakthrough

Water End Point 0.028591

Water Exponent 0.120352

Gas End Point 4.82787

Gas Exponent 19.8374

Breakthrough Sat 0.15

137

But from the Figure 6.20 it is seen that water production trend started to rapid upward

bending at a high rate after 2035. For this prediction of gas production are made up to 2035.

Figure 6.20: Predicted Cumulative Water Production for UGS up to 2050

Figure 6.19: Predicted Water and Gas Saturation with Reservoir Pressure for UGS

138

Production Prediction Based on Current Plant Conditions

Set average gas rate 66.5 (KTL-02: 16.07, KTL-03:13.42, KTL-05: 7.05 and KTL-06: 30)

MMscfd from UGS.

Figure 6.21 and Figure 6.22 show the cumulative gas production and gas recovery factor with

pressure respectively.

Figure 6. 21: Predicted Cumulative Gas Production and Reservoir Pressure for UGS

Figure 6. 22: Predicted Gas Recovery Factor and Reservoir Pressure for UGS

139

Production Prediction with Two more New Wells

Average gas rate are set 111 (22 for both two new wells) MMscfd.

Figure 6.23 and 6.24 show the cumulative gas production and gas recovery factor with

reservoir pressure respectively.

Figure 6. 23: Predicted Cumulative Gas Production and Reservoir Pressure for UGS with two more new wells

Figure 6. 24: Predicted Gas Recovery Factor and Reservoir Pressure for UGS with two more new wells

140

Summary and discussion for production prediction of UGS

Table 6.4: Production prediction results for UGS

Situation Set gas rate (MMscfd)

Producing time

Final Reservoir Pressure (Psig)

Recovery factor (%)

Current plant condition

66.5 2035 2920 45

Drilling Two more new wells

111 2035 2636 65

The Table 6.4 shows a comparative description for the Upper Gas Sand with current plant

condition and drilling two more new wells.

With current plant condition gas rate set by Gas Field Company it is seen that only 45%

ultimate gas recovery is possible as it is a water drive gas reservoir. So if it is wanted to

increase ultimate gas recovery new in fill drill is necessary. For this if two more new wells

are drilled then ultimate recovery can increase from 45% to 65%.

141

0 0.25 0.5 0.75 1

0

0.25

0.5

0.75

1

Fw Matching - Tank

Water Saturation

Fractional Flow


Off High

Medium Low

Water Breakthrough


Water Exponent 0.96

Gas End Point 0.8

Gas Exponent 1.4


6.5.2 Production Prediction for Middle Gas Sand

The Fw matching curve (Figure 6.25) shows that water breakthrough will not happen untill

the water saturation reach at about 85%. Before this water saturation it is possible to recover

the maximum amount.

Figure 6.25: Fw (fractional flow of water) Matching for MGS

142

Prediction

Gas rate are set at 30.5 (KTL-02: 14 and KTL-04: 16.5) MMscfd.

Figure 6.26 and Figure 6.27 show the cumulative gas production and recovery factor with


Figure 6.26: Predicted Cumulative Gas Production for MGS

Figure 6.27: Predicted Gas Recovery Factor for MGS

143

Summary and discussion for production prediction of MGS

Table 6.5: Production prediction results for MGS


Producing time


Recovery factor (%)


30.5 2035 2083 66

Table 6.5 shows that with current plant condition gas rate set by Gas Field Company 66%

ultimate gas recovery is possible. To recover this amount gas reservoir pressure will decline

from 3250 to 2120 psig. This means 1130 psig pressures will be decreased by 19 years which

is much greater than Upper Gas Sand. So, the aquifer strength for Middle Gas Sand is lower

than Upper Gas Sand. Gas recovery factor for Middle Gas Sand is high with existing wells,

so no new well is added.

144

6.5.3 Production Prediction for Lower Gas Sand

The Figure 6.28 below indicates that the water breakthrough will happen at the water

saturation of 0.40. The Figure 6.29 below shows this water saturation (0.40) will not be

reached by 2035. So the prediction up to 2035 may yield correct result.

0 0.25 0.5 0.75 1

0

0.25

0.5

0.75

1

Fw Matching - Tank

Water Saturation

Fractional Flow


Off High

Medium Low

Water Breakthrough


Water Exponent 8.50678

Gas End Point 0.000356425

Gas Exponent 10.3114


Figure 6.28: Fw (fractional flow of water) matching for LGS

0.3

0.31

0.32

0.33

0.34

0.35

0.36

2200

2300

2400

2500

2600

2700

2800

2900

3000

3100

5/28/05 11/18/10 5/10/16 10/31/21 4/23/27 10/13/32

Wat

er S

atur

atio

n, fr

actio

n

Pres

sure

(Psi

g)

Time (m/d/y)

Prediction: Tank Pressure Prediction: Water Saturation

Figure 6. 29: Predicted water saturation with reservoir pressure for LGS

145

PREDICTION

Gas rate is set at 2.7 MMscfd for Lower Gas Sand with one well only.

Figure 6.30 and Figure 6.31 show the cumulative gas production and recovery factor with


Figure 6.30: Predicted Cumulative Gas Production for LGS up to 2035

Figure 6.31: Predicted Gas Recovery Factor for LGS

146

Summary and Discussion for production prediction of LGS

Table 6.6: Production prediction result for LGS


Producing time


Recovery factor (%)


2.7 2035 2274 61

Table 6.6 shows that with current plant condition gas rate set by Gas Field Company 61%

ultimate gas recovery is possible. To recover this amount gas reservoir pressure will decline

from 2940 to 2274 psig. This means 666 psig pressures will be decreased which is much

greater than Upper Gas Sand. So, the aquifer strength for Lower Gas Sand is lower than

Upper Gas Sand. Gas recovery factor for Lower Gas Sand is high with existing wells, so no

new well is proposed to drill.

147

CHAPTER VII

CONCLUSION AND RECOMMENDATION

The accuracies of all analysis in this study are dependent on the quantity, reliability, and accuracy of the data collected.

Core and Well Logging Data Analysis

The Flow Zone Indicator methods developed by Amaefule et.al.1 was directly applied for

Kailashtila Gas field and this method worked explicitly for all Gas Sands of Kailashtila Gas

Field. So, the formation of Kailashtila Gas Field may be clean sandstone. Three reservoirs are

defined namely Upper Gas Sand, Middle Gas Sand and Lower Gas Sand and each reservoir

has only one hydraulic flow unit.

As Amaefule et.al methods is applicable for clean sandstones for shaly sand reservoir a

modification is added to Amaefule et.al equation by including shale volume. The modified

equation is tested using real field shaly sand reservoir‟s core data. The modified method is so

simple and easier than others developed method for identifying hydraulic flow unit for shaly

sand reservoirs till to date. But accuracy of new approach should be checked by comparing

with other methods using same data.

Well Test Data Analysis

The calculated values of “Absolute Open Flow Potential (AOFP)” for KTL-01 and KTL-04

from current study are 336.96 MMscfd and 199.86 MMscfd respectively which are

reasonable. But the AOFP for KTL-02 is 1824.36 MMscfd which is unrealistically high with

respect to highest production rate of 21 MMscfd. This is because; it was not possible to

record the production test appropriately for KTL-02 due to malfunction of the process flow

separator gas flow meter and also condensate flow rate was not possible to measure

individually.

The calculated values of inverse slope of back pressure equation „n‟ for all three wells KTL-

01, KTL-02 and KTL-04 from current study are 0.78, 0.91 and 0.64 respectively. These

values indicate that the flow condition for KTL-01 is in between laminar and turbulent, for

KTL-02 is laminar dominant and for KTL-04 is turbulent dominant.

The derived skin factor for well KTL-01, KTL-02 and KTL-04 are 6.5, 38 and 19

respectively. So, the total skin effects are positive for all three wells. With the exception of

148

KTL-01 the values of skin for other two wells might seem excessive. These high skin values

may be due to plugged perforation or formation damage.

The average reservoir pressures obtained from current study are 3506 Psia for KTL-01, 3222

Psia for KTL-02 and 3488 Psia for KTL-04, which very close to initial reservoir pressure for

all three wells though productions started in 1983 and data used here from the well test

performed in 2007. This high average reservoir pressure from buildup test after 24 years of

production may be due to external pressure support by water drive which is identified by

material balance simulation study.

Down-hole shut-in and down-hole flow measurements are necessary for a better analysis.

With down-hole flow measurements, it will be possible to deconvolve the pressure response

and analyze even the draw-down periods. It is recommended that the build-up test be

performed for a longer period to properly analyze the boundary effects. The flow rate should

be measured accurately with a flow measurement device. Production testing for KTL-02 was

not carried out due to malfunctions of the process plant separator gas flow meter at the time

of the test. Gas flow rates were not reported and the analysis is performed on the build-up

portion of the test. Consequently, all the data and results reported in this section may not be

very accurate or representative of the formation characteristics. It is recommended that

another production test could be run to infer formation characteristics.

History Matching and Production Prediction

An aquifer support is identified as an external driving force for gas production. Pressure

support by aquifer is comparatively high in Upper Gas Sand with respect to Middle Gas Sand

and Lower Gas Sand. The maximum reservoir void spaces are filled by encroached water for

Upper Gas Sand, Middle Gas Sand and Lower Gas Sand are about 74%, 20% and 22%

respectively. The prediction about reservoir abandonment pressure is not possible due to

aquifer support. For this gas production is predicted using rules of thumb “prediction time of

gas production should be half time of production history”. New total reserve is estimated at

about 2.71 Tcf, whereas the previous volumetric estimation by IKM was 1.62 Tcf. Significant

increase in gas reserves have been identified. In 2009, the recent study4 performed by

company also indicated a higher reserve than the volumetric estimation that is a good

harmony with reserve estimation in this study. Based on the performed scenarios a

recoverable volume of 1.41 TSCF gas is achievable for the field i.e. 52% recovery factor

using the existing wells. Recovery factor could be increased to 65% by drilling two more new

149

wells. However, the recovery factor could be increased by optimizing the well number and

well locations.

This study provides all the necessary information required for the reservoir simulation

studies. Reservoir simulation can be performed for history matching and future forecasting. It

can also be carried out to evaluate the coning performance in a particular well and establish

the pseudo relative permeability for a typical coning well.

150

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25. Rose, W. and Bruce, W.A: “Evaluation of Capillary Character in Petroleum Reservoir

Rock,” Trans., AIME (1949), 24, 127-142.

26. Crain‟s Petrophysical Handbook.

27. Cabral, Ricardo, J.P.: “A Reservoir Engineering Characterization of the North Study

Area of the C2/VLE-305 Reservoir, Lamar Field, Lake Maracaibo, Venezuela,” thesis

paper at Texas A&M University, 1994.

28. M. Fazel Alavi, Independent Consultant, IPTC Senergy and Kansas Geological

Survey; “Determination of Reservoir Permeability Based in Irreducible Water

Saturation and Porosity from Log Data and Flow Zone Indicator (FZI) from Core

Data, paper IPTC-17429.

152

29. Van Everdingen, A.F., and Hurst, W.: “The Application of the Laplace Transform to

flow Problems in Reservoir,” Trans., AIME (Dec. 1949) 305-324.

30. Dake, L.P.: “Fundamentals of Reservoir Engineering”, Elsevier, Amsterdam-London-

New York-Tokyo.

31. Economides, J. Michael; Hill, A., Daniel and Ehlig-Economides, Christine:

“Petroleum Production System”.

32. Havlena, D., and Odeh, A.S., “The Material Balance as an Equation of a straight

Line,” JPT (1963), 896-900.

33. Ahmed, Tareq and Mckinney, D., Paul: “Advanced Reservoir Engineering”, ISBN: 0-

7506-7733-3.

34. Petroleum Experts IPM Suite user manual.

35. http://www.petex.com/products/?id=60

36. Bruns, J.R., Fetkovitch, M.J and Meitzen, V.C.:“The Effect of Water Influx on P/Z-

Cumulative Gas production Curves”, J.Pet.Tech., March, 1965: 287-291.

153

APPENDIX-A

Core Data for Case Study

Depth,ft K, md Porosity, fraction GR, API Vsh, fraction

12358.3 2300 0.269 51.6 0.32

12363.4 610 0.247 59.2 0.4

12364.9 1100 0.267 55.6 0.36

12365.6 240 0.226 54 0.35

12366.8 450 0.254 48.1 0.29

12368.7 420 0.253 52.1 0.33

12369.9 170 0.244 54.1 0.35

12376.7 1700 0.269 56.8 0.37

12377.6 1100 0.26 55.1 0.36

12378.6 1000 0.25 50.9 0.32

12379.8 290 0.229 47.3 0.28

12381.1 1500 0.241 43.3 0.24

12382.1 1600 0.243 43.3 0.24

12383.9 180 0.228 47.9 0.29

12384.9 1100 0.263 48.1 0.29

12388.3 880 0.233 40.3 0.21

12390.2 1800 0.262 35.1 0.16

12391.6 2300 0.269 35.2 0.16

12392.6 1300 0.243 38.1 0.19

12394.7 940 0.245 44.5 0.25

12418 770 0.191 67.4 0.48

12421.4 240 0.216 62.7 0.43

12423.8 160 0.227 67 0.48

12428.1 0 0.021 65 46

12429.1 1 0.034 62 0.43

154

APPENDIX-B

CORE DATA OF KAILASHTILA GAS FIELD

Upper Gas Sand

Core Depth, ft K, (mD) Sw, percent Grain Density,(gm/cc) ɸ, fraction

7476 351.8 30.4 2.75 0.117

7479 496 27 2.72 0.309

7480 972 44.2 2.71 0.274

7482 1068 35.2 2.71 0.295

7483 1013 38.2 2.71 0.306

7503 683 24.7 2.74 0.204

7506 338 45.8 2.67 0.235

7507 436 28.2 2.68 0.233

7509 511 16 2.69 0.251

7513 1117 23.7 2.67 0.229

7515 688 31.6 2.73 0.22

7516 541 44.6 2.67 0.233

7520 1013 37.4 2.71 0.258

7527 1105.8 28.3 2.71 0.211

7531 1407 12.7 2.7 0.239

7536 1445 53.2 2.71 0.23

7537 1381 17 2.66 0.223

7541 1335 29.1 2.66 0.235

7545 822 46.2 2.66 0.243

7549 794 29.1 2.68 0.238

7550 1121 37.5 2.67 0.226

7555 973 29 2.69 0.215

7558 1055 21.1 2.63 0.226

7559 1093 32.2 2.65 0.245

7560 925 27.5 2.67 0.232

7561 648 34.6 2.69 0.306

7585 1239 52.6 2.71 0.283

155

7589 901 37.2 2.71 0.251

7590 1547 42.5 2.7 0.272

7598 1333 12 2.71 0.252

7600 1372 15.9 2.66 0.228

7601 1470 30.2 2.67 0.237

7602 1248 23.8 2.67 0.227

7603 1133 17 2.65 0.225

7604 768 19.1 2.7 0.201

7607 1379 34.9 2.67 0.234

7609 1462 24.4 2.66 0.227

7612 1546 29.6 2.67 0.221

7615 317 25.4 2.7 0.247

7629 434 13.4 2.67 0.201

7633 694 22 2.68 0.23

7634 861 20.9 2.67 0.232

7636 772 42.5 2.7 0.243

7638 710 19.3 2.68 0.228

7640 697 33.2 2.65 0.238

7643 1261 19.6 2.71 0.269

7647 587 24.8 2.7 0.229

7655 433 18.4 2.73 0.243

7657 389 38.2 2.69 0.236

7660 852 46.7 2.71 0.277

7662 327 50.3 2.69 0.235

7663 340 21.6 2.69 0.241

7665 797 36.7 2.74 0.303

156

Middle Gas Sand

Core Depth, ft K, (mD) Sw, Percent Grain Density (gm/cc) ɸ, fraction

9600 309 18.2 2.67 0.205

9601 492 27.7 2.69 0.221

9602 701 25.1 2.67 0.217

9603 894 37.5 2.71 0.229

9604 475 12.8 2.67 0.221

9605 707 39.1 2.7 0.227

9606 760 28.9 2.67 0.196

9608 826 24.8 2.7 0.253

9609 222 19.4 2.76 0.144

9610 890 31.1 2.66 0.21

9612 948 15.3 2.66 0.219

9613 622 18.6 2.67 0.211

9614 841 22.9 2.66 0.219

9615 776 22.7 2.66 0.218

9616 1080 24.7 2.68 0.223

9617 913 29.8 2.69 0.228

9618 1062 33.8 2.7 0.235

9619 773 30.7 2.65 0.21

9620 952 23.2 2.66 0.217

9621 844 30.4 2.66 0.222

9624 823 41.7 2.66 0.205

9625 1619 33.4 2.69 0.196

9626 639 25.7 2.66 0.211

9627 471 37.9 2.7 0.218

9628 453 11.2 2.8 0.223

9629 496 17.1 2.66 0.202

9634 1028 33.7 2.66 0.205

9635 1586 14.9 2.65 0.221

9636 1448 30.1 2.66 0.222

9637 716 21.1 2.67 0.209

9638 1591 17.5 2.67 0.224

157

9639 1294 24.3 2.66 0.219

9641 365.3 21.7 2.66 0.217

9643 1338 32.7 2.7 0.213

9644 890.3 27.4 2.7 0.216

9645 704 21.9 2.69 0.224

9646 839 11.4 2.66 0.222

9647 883 37.4 2.66 0.22

9648 1072 36.8 2.66 0.224

9650 774.8 14.2 2.72 0.2

9651 776 32.4 2.66 0.213

9652 602 27.1 2.72 0.237

9654 889 15.8 2.66 0.212

9656 1294 26.4 2.7 0.106

9657 957 17.8 2.65 0.213

9662 669 19.9 2.66 0.231

9663 910 28.2 2.68 0.242

9666 387 36.9 2.7 0.235

9667 122 15.4 2.73 0.082

9668 876 19.7 2.65 0.205

9669 856 28.4 2.67 0.228

9670 605.7 23.2 2.72 0.249

9671 518 41.5 2.66 0.215

9672 321.8 32.1 2.71 0.225

9673 1180 36.3 2.65 0.193

9674 485 28.7 2.78 0.193

9675 130 21.4 2.66 0.182

9677 460 30.8 2.65 0.205

9678 1048 41.9 2.67 0.228

9679 361 31.7 2.67 0.202

9680 1310 24 2.7 0.263

9681 266 32.9 2.66 0.195

9682 659 18.4 2.66 0.221

9687 1336 16.1 2.71 0.285

158

9688 701 37.5 2.72 0.283

9695 642 24.1 2.7 0.129

9697 766 11.6 2.7 0.297

9698 1275 37.2 2.66 0.194

9699 895 28.9 2.66 0.22

9701 884 31.6 2.66 0.217

9702 884 24.4 2.66 0.221

9703 869 21.5 2.66 0.217

9704 937 32.5 2.66 0.221

9706 909 12.9 2.69 0.219

9709 120 30.7 2.68 0.044

9715 533 27.8 2.66 0.205

9717 517 29.2 2.66 0.209

9718 328 40.2 2.67 0.214

9720 268 34.3 2.66 0.179

9721 427 24.2 2.68 0.216

9722 459 31.4 2.66 0.207

9724 220 23.2 2.7 0.186

9725 1540 36.2 2.71 0.206

9726 358 21.4 2.67 0.211

9727 454 28.5 2.72 0.22

9728 336 27.6 2.69 0.215

9729 308 27.1 2.71 0.191

9730 1165 30.7 2.71 0.247

9731 1107 31.9 2.71 0.247

9732 234 28.8 2.74 0.219

9734 247 24.2 2.68 0.203

159

Lower Gas Sand

Core Depth, ft K, (mD) Sw, Percent Grain Density (gm/cc) ɸ, fraction

9899 144 11.7 2.67 0.185

9901 230 31 2.7 0.097

9903 304 26.2 2.67 0.204

9904 584 21.7 2.65 0.214

9905 1276 31.6 2.65 0.213

9906 1761 32.4 2.65 0.224

9907 1099 16.2 2.65 0.206

9908 973 24.4 2.65 0.205

9909 1213 18.9 2.65 0.213

9911 1076 30.2 2.65 0.201

9912 482 32.4 2.66 0.206

9914 776.2 26.4 2.7 0.19

9915 841 22.1 2.65 0.211

9916 1131 22.5 2.65 0.224

9917 568 25.7 2.65 0.215

9918 562 31.2 2.66 0.212

9920 1103 30.7 2.64 0.213

9921 942 26.2 2.64 0.209

9922 1448 24.7 2.66 0.226

9923 676 29.1 2.64 0.2

9925 130 30.2 2.7 0.12

9926 1195 28.2 2.69 0.204

9928 971.7 30.2 2.7 0.25

160

APPENDIX-C

WELL LOGGING DATA OF KAILASHTILA GAS FIELD

Upper Gas Sand

Depth(ft) Rt фD фN ф, fraction F Swa, fraction

7366 31 27 18 0.2275137 19.54 0.63

7370 63 22 22 0.215 22.07 0.47

7374 62 24 19 0.2164486 21.75 0.47

7378 68 24 18 0.212132 22.71 0.459

7382 90 22 19 0.205548 24.31 0.412

7386 41 18 24 0.212132 22.71 0.591

7390 40 14 25 0.202608 25.07 0.628

7394 78 26 22 0.2408319 17.29 0.374

7398 53 23 21 0.2202272 20.96 0.499

7402 69 25 20 0.2263846 19.75 0.425

7406 82 25 18 0.2178302 21.46 0.406

7410 101 29 17 0.235929 18.07 0.336

7414 120 26 16 0.2158703 21.88 0.339

7418 118 25 17 0.2118077 22.79 0.349

7422 105 26 16 0.2158703 21.88 0.362

7426 82 22 18 0.2009975 25.5 0.443

7430 100 26 17 0.2196588 21.07 0.364

7440 118 24 18 0.212132 22.71 0.348

7450 40 25 23 0.2378287 17.76 0.529

7456 102 26 16 0.2158703 21.88 0.368

7460 95 25 17 0.2137756 22.34 0.385

7472 90 25 20 0.2263846 19.75 0.372

7480 70 22 20 0.2078762 23.72 0.462

7484 70 23 20 0.210535 23.09 0.456

7490 78 22 20 0.2076355 23.78 0.438

7500 67 20 18 0.190263 28.7 0.519

7510 89 22 20 0.2052438 24.38 0.415

7520 70 21 20 0.205061 24.43 0.469

161

7530 70 18 24 0.212132 22.71 0.452

7540 100 22 18 0.2009975 25.5 0.401

7550 82 20 20 0.2 25.78 0.445

7560 75 16 21 0.1866815 29.9 0.501

7570 81 20 19 0.1950641 27.2 0.46

7580 70 19 19 0.19 28.78 0.509

7592 78 20 20 0.2 25.78 0.456

7600 90 21 19 0.2002498 25.71 0.424

7606 101 21 19 0.2002498 25.71 0.4

7620 67 21 18 0.1955761 27.05 0.504

7630 52 20 22 0.210238 23.16 0.53

7640 70 19 20 0.1950641 27.2 0.495

7650 68 19 22 0.205548 24.31 0.475

7660 40 16 22 0.1923538 28.03 0.664

7670 40 19 22 0.205548 24.31 0.619

7700 16 22 27 0.2462722 16.48 0.806

Middle Gas Sand

Depth,(ft) Rt фD фN Ф,(fraction) F Swa, (fraction)

9560 17 25 27 0.26019 11.96 0.419

9574 48 6 16 0.12083 55.48 0.538

9582 30 6 19 0.14089 40.81 0.583

9596 100 21 18 0.19558 21.18 0.23

9608 160 22 18 0.201 20.05 0.177

9620 150 21 20 0.20506 19.26 0.179

9630 80 20 20 0.2 20.25 0.252

9640 68 19 22 0.20555 19.17 0.265

9650 120 20 22 0.21024 18.33 0.195

9660 80 19 21 0.20025 20.2 0.251

9670 17 12 22 0.1772 25.8 0.616

9680 62 19 19 0.19 22.44 0.301

9690 50 20 22 0.21024 18.33 0.303

162

9707 135 20 19 0.19506 21.29 0.199

9712 110 20 20 0.2 20.25 0.215

9720 70 20 19 0.19506 21.29 0.276

9730 74 21 19 0.20025 20.2 0.261

9740 57 17 23 0.20224 19.8 0.295

Lower Gas Sand

Depth(ft) Rt фD фN ф, (fraction) F Swa, (fraction)

9910 63 6 14 0.108 69.83 0.526

9916 82 22 16 0.192 21.89 0.258

9920 78 21 17 0.191 22.19 0.267

9924 75 21 17 0.191 22.19 0.272

9928 70 21 17 0.191 22.19 0.282

9934 110 15 14 0.145 38.48 0.296

9938 104 24 15 0.2 20.22 0.22

9940 70 23 16 0.198 20.64 0.271

9944 47 21 15 0.182 24.32 0.36

9950 31 16 21 0.187 23.24 0.433

9957 28 16 18 0.17 27.93 0.499

9964 24 15 20 0.177 25.92 0.52

9970 21 13 19 0.163 30.57 0.603

INTEGRATED RESERVOIR CHARACTERIZATION OF KAILASHTILA …

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