History matching Report

2015

MASTER SRE-HGM Yan Shan CHEONG Sergey USMANOV

[HISTORY MATCHING OF NANCY FIELD] This report will give some brief information on geology of the exploration field and more detailed information on the workflow of history matching.

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Table of contents

1. Introduction ................................................................................................................................2

2. Geological review of Nancy field..................................................................................................2

a. Nancy field Petroleum System .................................................................................................3

3. Production history.......................................................................................................................5

4. MBAL Simulation .........................................................................................................................5

a. Objectives ...............................................................................................................................5

b. Fluid properties .......................................................................................................................6

c. Tank properties .......................................................................................................................6

5. History matching (MBAL).............................................................................................................9

a. Without aquifer .......................................................................................................................9

b. Bottom aquifer ........................................................................................................................9

c. Closed radial aquifer.............................................................................................................. 10

d. Conclusion............................................................................................................................. 11

6. ECLIPSE Model Review .............................................................................................................. 11

a. Grid properties ...................................................................................................................... 11

b. Rock & Fluid properties ......................................................................................................... 13

c. Original volume in place ........................................................................................................ 15

7. Production history match .......................................................................................................... 16

a. Aquifer permeability ............................................................................................................. 16

b. Aquifer size ........................................................................................................................... 16

c. Faults transmissibility ........................................................................................................... 18

8. Production forecast ................................................................................................................... 23

9. History matching workflow ....................................................................................................... 25

10. Conclusion............................................................................................................................. 27

11. References ............................................................................................................................ 27

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1. Introduction

This report is dedicated to the course Nancy Field Case: Dynamic Evaluation which is given by Mr

Etienne Moreau and Ms Irina Panfilova. The main objectives of this course work are:

Understand the main issues related to reservoir simulation.

Understand and able to use MBAL and ECLIPSE for reservoir simulation.

Understand the workflow of history matching.

Generate the production forecast and provide the location for in fill well.

In the following sections, geological information of the field will be given. Then, the reservoir model

would be first discussed by using MBAL simulation. After that, there will a detailed workflow on

history matching of the reservoir model and discussion on the matching parameters. There will be a

summary of the history workflow to end the report.

2. Geological review of Nancy field

NANCY field is located in the SE Segment of the Euphrates graben in Syria. The Euphrates graben

system in southeastern Syria is an aborted continental rift that holds significant petroleum reserves

(over one billion barrels of proven reserves have been found in the Euphrates area since the mid

1980's) (Figure1).

Figure 1 Location of area investigated [1]

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The Euphrates graben system was primarily active in late Cretaceous. Following Lower Cretaceous

deposition of the Rutbah Formation, extension began during the Coniacian with block faulting,

development of a regional unconformity, and limited deposition of continental; however, the main

phase of deformation occurred during the CampanianMaastrichtian, with extensive normal faulting

and graben formation (Figure 2).

Figure 2 Schematical NE-SW geological cross section

Faulting essentially ceased by the Paleocene; Paleogene thermal sag basin overlies the graben

system. An additional phase of deposition in the upper Miocene overlies part of the Euphrates

graben. Minor late Neogene transpression reactivated some of the structures in response to the

Zagros-Bitlis continental collision. The area appears to be tectonically inactive at present.

The total amount of extension is minimal, not more than 6 km, but deformation is extremely

widespread and complex considering the amount of extension. Two distinct fault populations are

noted: west-northweststriking normal faults with relatively large throws in the northwestern part of

the study area, and steeply dipping, northwest-striking flexures and strike-slip faults nearer to the

Iraq border. SE Segment, contained Nancy field represents deep graben with widespread listric faults.

Due to the presence of several unconformities, the completeness of the Cretaceous section differs

greatly from well to well. The late Campanian Maastrichtian Shiranish formation is present

throughout the area, although its thickness varies dramatically. This formation primarily consists of

marl interbedded by limestone or sandstone. The Shiranish formation overlies either the Upper

Cretaceous Soukhne or Judea, the Lower Cretaceous Rutbah, the Triassic Serjelu (Mollussa), or the

Carboniferous Markada formations. The Coniacian Derro Formation, unconformably bounded at both

top and base, and rarely presented in wells. The base Coniacian unconformity exhibits the most

pronounced discordance of any Cretaceous unconformity in the study area and interpreted as the

synrift/postrift boundary.

a. Nancy field Petroleum System

The Euphrates Graben harbors the most important hydrocarbon plays in Syria. More than 400,000

barrels of light, sweet crude are estimated to be produced daily from the graben, out of a national

average of 540,000 barrels (Oil & Gas Journal, December, 1999). The bulk is from the Lower

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Cretaceous Rutbah sandstone, a high porosity (up to 20%) fluvio-deltaic sandstone with well-

maintained permeability, that was deposited during the Neocomian transgression in eastern Syria.

Alternating carbonates and evaporites of the transgressing Triassic have created a series of potential

reservoir / seal pairs, and the widespread Serjelu (Mulussa F) could be reservoir quality sandstone

(heterogeneous clastic sediments, channelized delta plain). Minor production comes from other

levels and trapping is most commonly in fault blocks.

Rutbah sandstone forms the reservoir that is both charged and sealed by Upper Cretaceous marly

limestone of the Shiranish formation (Figure 3). The Shiranish, deposited under widespread

extension in eastern Syria, has been juxtaposed against the Rutbah by the Latest Cretaceous normal

faulting that created the rotated fault block trap. The migration processes appeared through the

fault system (Figure 3).

Figure 3 Chronostratigraphic chart and Play elements

While appreciable structural inversion in the northwest of the system may have breached some

reservoirs, further southeast trapping has been enhanced by the very mild folding resulting from the

Cenozoic compression.

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3. Production history

The field is started to produce through natural depletion in 03/1992. The initial reservoir pressure is

80 bars above the bubble pressure (median STOIIP = 276 MMbbls). The water-oil contact was defined

as horizontal in all the blocks 2693 mTVD (Figure 4). Water injection is started in 11/1997.

Figure 4 EW Geological Cross Section

At the first phase of production, the main drive mechanisms are solution gas drive and aquifer drive.

Nevertheless, the aquifer contribution is weak. Therefore, 2 producing wells are converted into the

water injectors at the second phase of production. At the moment, there are 11 sub-vertical wells

(but 503 G): 9 producers and 2 injectors.

Median OHIP (Previous study):

Static : 251 MMbbls (39.9 MMm3)

Dynamic : 276 MMbbls (after history match)

Upper Rutbah (4% OIP)

Lower Rutbah (83% OIP)

Mulussa ( 13 % OIP)

4. MBAL Simulation

a. Objectives

Getting some general ideas of the reservoir properties.

Identify the pressure support of the reservoir.

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Identify the type of aquifer (if present).

b. Fluid properties

Figure 5 Data input and correlations

In order to have the fluid properties such as bubble point pressure, solution gas oil ratio, formation

volume factor and oil viscosity, correlations are used. As the result of the analysis of standard

deviations (through the matching function), Standing and Petrosky et als correlations are chosen for

the fluid studies (Figure 5).

Initial state

Reservoir pressure 308 bars

Oil volume factor 1.41

Saturation pressure (Bubble point pressure) 223.1 bars

The bubble point pressure could be determined through oil viscosity, oil volume factor and solution

gas oil ratio (Figure 6, 9, 10). Above the saturation pressure, the oil volume factor increases while

pressure decreases because of the expansion of reservoir volume. But once it hits the saturation

pressure, it starts to decrease as dissolved gas is liberated (Figure 6). For GOR, it stays constant above

bubble point pressure and starts to decrease when pressure drops below bubble point pressure as

dissolved gas is liberated (Figure 9). Whereas for oil viscosity, it becomes more and more viscous

under bubble point pressure as dissolved gas is liberated (Figure 10).

c. Tank properties

Irreducible water saturation, Swi: 0.25

By using the curve Kro Vs Sg, residual oil saturation=1-0.6-0.25=0.15 (Figure 11).

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Figure 6 Oil volume factor

Figure 7 Gas volume factor

Figure 8 Gas viscosity

Figure 9 Oil viscosity

Figure 10 Solution gas ratio

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Figure 11 Relative permeabilities' curves

Figure 12 Average reservoir pressure versus time

Figure 13 Cumulative oil production versus oil

Figure 14 Solution gas ratio versus time

Figure 15 Cumulative water production versus time

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5. History matching (MBAL)

a. Without aquifer

Figure 16 History match by changing the oil in

place

Figure 17 Oil in place suggested by regression function

At first glance, the pressure decline rate is too high compared to the historical data. It seems that the

volume is not sufficient to support the pressure. The regression function is used where the only

parameter, initial oil volume, is adjusted (Figure 17). The result shown does not fit the historical data

with the increased oil volume. Since extra energy is needed to support the pressure, the simulation

has given an increased oil volume which is around 5 times of the initial oil volume. This assumption is

rejected as it is considered as not realistic.

b. Bottom aquifer

Figure 18 History match by bottom aquifer influx

(line) and without aquifer (dotted line)

Figure 19 Aquifer volume and permeability as modified

parameter

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Since the increased oil volume is not accepted as the control parameter of the history matching,

aquifer is introduced as a pressure support mechanism. In this case, the bottom aquifer will be

investigated. The regression function has proposed to adjust vertical permeability and the aquifer

volume (Figure 19). The quality of the history matching is very good (Figure 18). However, this

simulation is rejected due to two reasons. Firstly, the increased volume of aquifer which is around 30

times of the initial oil volume is not realistic. Secondly, the vertical permeability which is around 0.04

mD is too low to be justified.

c. Closed radial aquifer

Figure 20 History match by closed radial aquifer

influx (line) [before regression] and without aquifer

(dotted line)

Figure 21 Data input of aquifer before regression

method

Figure 22 History match by closed radial aquifer

influx (line) [after regression] and without aquifer

(dotted line)

Figure 23 Radius ratio and aquifer permeability as

main modifying parameters

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In this case, the closed radial aquifer is tested by assuming the parameters shown in Figure 21. The

quality of the history matching is not accepted and regression function is used (Figure 20). By

adjusting the outer/inner radius and the aquifer permeability, the simulation shows a good history

matching (Figure 22). For the radius ratio around 7 and a permeability of 50 mD, the adjusted

parameters are more reasonable compared to the previous simulations.

d. Conclusion

From the first simulation, it should be noted that presence of an aquifer is necessary for the pressure

maintenance. The aquifer model used in the simulation is Hurst-Van Everdinghen modified type

which is considered as the most generalized model for studies. By applying different aquifer models,

the closed radial aquifer seems to have the most reliable simulation with aquifer permeability of

around 50 mD.

6. ECLIPSE Model Review

a. Grid properties

Field description

a. Number of cells: 118 X 31 X 23 = 84134 cells

b. Average cell dimensions (m)

DX DY DZ

98.815 99.05 15.221

Figure 24 3D view of reservoir

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Grid optimization

a. Pinch out criteria: 0.2m

b. Number of pinch out generated: 150

c. Pore volume cut-off (MINPV): 100

d. Number of inactive cells due to MINPV: 251

e. Number of active cells: 42036

f. Number of non-neighbor connections: 21883

Faults

a. Number of faults: 33

b. Geometry of faults

Most of the faults are in the direction of NW-SE and N-S. Their dip is mostly sub-vertical.

By visualizing the NNC in 2D view, it could be concluded that most of them are transverse

or normal faults (Figure 25).

Figure 25 NNC of layer k=4 of the field

Equilibration regions

a. Number of equilibration regions (EQLNUM): 1

b. Geometry of regions

1 equilibration region signifies that there is only one unique region in the entire field

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(Figure 26). There isnt any compartmentalization in the field although there are quite a

number of faults.

Figure 26 Equilibration region of different layers

c. Equilibration parameters

b. Rock & Fluid properties

Rock properties

a. Number of rock types: 5

Irreducible water

(DRAINAGE)

Oil displaced by water

(IMBIBITION)

Oil displaced by gas

(DRAINAGE)

RT Swc Kro max Pcwo max Sorw Krw max Pcwo Sorg Krg max Pcgo

max

1 0,05 1 0,739 0,24 0,185 0 0,1718 0,5999 0

2 0,08 1 1,108 0,24 0,185 0 0,1664 0,5999 0

3 0,14 1 1,477 0,2965 0,09 0 0,1555 0,5999 0

4 0,2 1 1,847 0,2758 0,09 0 0,1447 0,5999 0

5 0,45 1 0 0,1897 0,09 0 0,0995 0,5999 0

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Sgmax is obtained when Kro=0. The residual oil saturation displaced by gas should take into account

the irreducible water saturation present in the reservoir. The formula used to calculate the residual

oil saturation is, Sorg=1-Sgmax-Swi.

Fluid properties

Oil Water Gas

Stock density (kg/m3) 849 1100 1,058

Viscosity is needed to define the fluid mobility and Eclipse calculates the fluid viscosities for reservoir

conditions. Since the fluids are static at stock tank conditions, it is not necessary to compute the

viscosity. Therefore there is no viscosity value for the fluids at stock tank conditions.

Number of PVT region: 1

Figure 27 PVT number of the field

Figure 28 PVT data extraction from Eclipse

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Datum depth 2620 m Oil volume factor* 1.42

Solution gas ratio (Rs) 139.5 Oil viscosity* 0.7663

Initial pressure 308 bars Oil density =(gRs+ost)/Bo

=701.82kg/m3

Saturation pressure* 213 bars

* Obtained through reading of Figure 28

The formation volume factor is a parameter which depends on bubble pressure and reservoir

pressure.

c. Original volume in place

Initial water saturation above free water level (FWL)

a. Number of regions retained for equilibration

Since the wettability of medium depends on the rock types, the regions determined should be

related with the rock types. Hence, there are 5 regions which correspond to 5 rock types. SATNUM is

a property which allows the visualization of the different regions (rock type based) in Floviz.

Lets consider a drainage process in a wetting reservoir where water is wetting fluid and oil as non-

wetting fluid. The FWL is the level where the capillary pressure is zero (in the absence of oil phase)

(Figure 29). The oil water contact is situated in the transition zone and PD is the minimum pressure

needed for the oil to displace water in a fully saturated reservoir. The water saturation then

decreases as the capillary pressure increases. When the water is trapped and thus becomes non-

mobile, the water saturation is now called irreducible saturation. At this level, the increase in

capillary pressure can no longer decrease the water saturation.

Figure 29 Definition of transition zone

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Since the wettability of each rock type is different, the transition zones among the rock types are

different as well. In order to compute the height of transition zones, the formula below is used:

Pc=gh, h=Pc/g

Original volumes in place

Reservoir condition Stock tank condition

Region Pore volume Water Oil Gas Water

volume

Oil Gas

(dissolved)

Rm3 Rm3 Rm3 Rm3 Sm3 Sm3 Sm3

1

2 2053487 1007122,626 1046364,374 NA 981601 731492 103804212

3 8991824 6019216,758 2972607,242 NA 5866683 2093825 291936052

4 330408383 276812782,9 53595600,12 NA 269798034 37799800 5349619270

5 136894800 122655521,6 14239278,41 NA 119547292 10174831 1428322342

7. Production history match

a. Aquifer permeability

In order to fit the early time data, the average pressure of the field should first be calibrated. The

pressure of the field will affect directly the gas production of the field. First, the Carter Tracy infinite

aquifer model is used in order to start the history matching. Aquifer permeability is the parameter

that should be modified in order to match the pressure profile. The aquifer permeability set is

around 50 mD as previous analysis from MBAL shows an ideal permeability at 50,25 mD. The result

shows a good fit of historical data at early times, but the pressure stabilizes at late times (Figure 30).

This is in contrast to the historical data where the well measurements show a declining pressure. The

good fit of pressure data at early times shows that the aquifer permeability is appropriate as the

permeability acts as the main parameter at early times. For late times pressure matching, the size of

the aquifer should be investigated.

b. Aquifer size

In order to have better match for late times, a closed aquifer has been chosen as the next step. By

using the parameters seen previously in MBAL, the result obtained are rather satisfied at late times

(Figure 31). However, it should be noted that the pressure at the end of the simulation seems to be

too low and perhaps a stronger aquifer is anticipated.

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Figure 30 History match of pressure data by infinite aquifer

Figure 31 History match of pressure data by closed aquifer

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c. Faults transmissibility

After the matching of the average field pressure, the next step would be analysis on well per well

basis. Firstly, wells data WBP9 is used to compare to the historical average reservoir pressure

obtained through well testing. WBP9 is the average reservoir pressure in the 9 surrounding the well

cell. It should be noted that WBP9 is a numerical approximation of the natural reservoir pressure

situated outside of the drainage area. Therefore, WBP9 is lower than the historical observed values

due to the presence of well in the area used for WBP9 calculation. During the matching process, late

time responses are more important in comparing both pressures as the early time responses depend

on the geological model while late times responses rely more on the reservoir dynamics such as fluid

flows. Late time responses are also influenced heavily by distance which is an important parameter

controlling the reservoir pressure distribution. By analyzing the well pressure and historical data, the

wells NAN101 and NAN104 show a higher pressure than the historical data while NAN108 shows a

lower pressure (Figure 32, 33, 34). The difference in pressure distribution shows eventually the

compartmentalization due to the presence of multiple faults.

Since the faults play a role in the pressure distribution, the next step would be on investigating the

influence of faults particularly on the faults transmissibility. Pressure data obtained in January 2002

shows that there are different pressure distributions in the field (Figure 37). The pressure is higher in

the West than in the East. By using the isobar lines of the field, it can be deduced that the faults 620

and 621 are sealed (Figure 37). Fault 35 and 52 are sealed as well as their pressure data is matched

with the historical ones. If the faults are opened, the aquifer water influx could have decreased the

pressure. This has been shown through the sensitivity analysis (Figure 35).

Figure 32 NAN101 WBP9 vs historical pressure



Figure 35 Sensitivity analysis of faults 35&50 on NAN507

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Figure 36 Mismatch zones of pressure data

Figure 37 Pressure distribution observed January 2002 and flow lines (black arrow)

The data provided by sensitivity analysis shows the influence of each major fault on the wells

pressure and water production. By using the information gathered through analysis of isobars and

comparisons between the well and history data, a combination of faults transmissibility is planned

for the simulation (Figure 38). The combination has shown an improved match on the well pressure

data (Figure 39, 40, 41, 42).

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Figure 38 Faults transmissibility

Figure 39 NAN101 WBP9 with faults' transmissibility

modification (after: red line, before: green line)







Figure 43 NAN105 total water production vs

historical data

Although the pressure is better matched compared to the original default faults transmissibility, the

well water production data has not been satisfied. Thus, the water total production of each well can

be only partly matched using the transmissibility multipliers explained previously as it is affected by

the pressure distribution: when there is lack of pressure support from aquifer (probably due to

sealed faults), the pressure drawdown between blocks would be higher (consequently it becomes

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lower in the single block) and hence the gravity effects would become increasingly more important.

As the gravity entails slowing down the water approaching to the well bore for the wells with high

attitude, this could cause a drop on water production in the well which is in the uplifted block (Figure

36, 43).

At this stage, assuming that the faults transmissibility is well calibrated, the next parameter which

can be used in order to match the well water production would be the horizontal permeability of the

reservoir. The aquifer model should be first identified before modifying the reservoir permeability.

By looking at the curve of the wells water production, two types of aquifer model could be easily

recognized (Figure 44, 45). Bottom aquifer support would show a faster increase in the water

production due to its proximity to the well while edge aquifer shows a slower increase in water

production compared to the former (Figure 44, 45).

Figure 44 Edge aquifer support

Figure 45 Bottom aquifer support

There are two types of trends which could be observed with the water production data: it is either

too much water produced or insufficient water produced compared to the historical data. For a

bottom aquifer support, if there is lack of water produced, it means that the pressure drawdown is

decreasing and that the gravity effects are strong. Hence, in order to produce more water, the

horizontal permeability should be decreased. This is illustrated by defining a box on the area of

well NAN102 (Figure 46). This area is chosen as it is delimited by the major faults in the region (Figure

46). In NAN102, there is too much water produced. As explained previously, the permeability needed

to be increased in order to have less water produced (Figure 47). However, the result obtained is

rather disappointing as there is not much improvement compared to previous simulation (without

defining the box). Then next attempt is on the relative permeability curves where the relative

permeability of water at the end point (KRWR) is lowered in order to have less water production.

But this attempt again not successful. The unsuccessful attempts may be explained by the problem

observed on the transmissibility on the z direction (Figure 48). The blue cells are having zero

transmissibility and thus there is some bypassed oil found in some of the cells.

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Figure 46 "Box" defined around NAN102

Figure 47 WWPT of simulation without box (light blue) and with box (dark blue) vs history data

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Figure 48 Abnormal situation on the z transmissibility in the field

8. Production forecast

After having matched the reservoir pressure and the wells water production, the model is assumed

to be working and production forecast is launched. The simulation is run under ORAT mode where

the oil rate is set as constraint and the simulation data is thus fit perfectly the history data (Figure

49). The water production is more or less well matched (Figure 50). However, the field GOR has not

been matched properly as the GOR ratio increases earlier than expected and the ratio is rather high

(Figure 52). The bubble pressure is achieved too early comparing to the historical data (Figure 52).

This is due to the imperfect match of the pressure where the pressure is not sufficiently high during

the matching with the closed aquifer (Figure 31). This shows again the importance of matching

properly the reservoir pressure. In order to correct the GOR problem, constraints have been set for

the WECON, the economic limit data for production wells; that the GOR limit is set at 2000 for all

producing wells. However, the GOR ratio still surges to very high level (Dark blue line in Figure 52).

The main objective of production forecast is to plan the future development strategy. At the same

time, ideas like in fill well could be implemented in order to enhance the recovery factor. In this

study, a well has been proposed to be at the west of the region (at proximity of NAN102) where the

aquifer support is strong (Figure 53). Besides, there is a strong accumulation of oil at the cells K=3 to

7 where the oil saturation is around 0.8 to 0.95 (Figure 54). The additional well has provided

encouraging result where the recovery factor has been increased by 1%, from 34 to 35% (Figure 55).

Although 1% doesnt seem a lot but it has actually increased 1 Mm3 (8.4 Mbbl) and the only

additional well has added 420 M$ to the economic value at the price of 50$ per barril.

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Figure 49 FOPR vs time (do nothing case)

Figure 50 FWCT vs time (do nothing case)

Figure 51 FOPT, FWPT vs time (do nothing case)

Figure 52 Field GOR vs time (do nothing case)

Figure 53 Position of well NAN111

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Figure 54 Oil saturation at the vicinity of NAN111

Figure 55 Additional well for incremental oil recovery

9. History matching workflow

Two programs have been used for the field history matching namely MBAL and ECLIPSE. MBAL is

easily manipulated by using regression method in generating the best solution under certain

scenarios. Nevertheless, the parameter suggested by software should be investigated for its

coherence with the reservoir conditions. Then, ECLIPSE is software that provides more information

on dynamic evaluation. Besides, it can provide the simulation for each well whereas MBAL is limited

on the whole reservoir. During the planning of the combination for faults transmissibility, the

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matching parameter WBP9 should be the priority upon the well water production as there are other

factors that could be affecting the water production such as aquifer model and local transmissibility.

If the historical data is well matched by the model, the model is now fit for the production forecast

which is the ultimate objective for the history matching. At this stage, observations could be made on

the future remaining oil. This information is particularly useful in determining the position of the infill

well. Simulations can be run in order to check the performance of the additional well. It should be

noted that an infill well may not necessarily increase the oil recovery. The chart below shows the full

workflow on the history matching of the field:

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10. Conclusion

History matching is an inverse problem. There can be different sets of parameters that could lead to

the same results. Hence it is always important to check the coherence and consistency of the

parameters modified to the reality and the reservoir conditions. For example, during the simulation

through MBAL, the oil volume in place suggested initially was 5 times of the OIIP. Although the model

is well matched but it shouldnt be accepted due to the over exaggerating factor. MBAL could not

simulate the well dynamics like ECLIPSE did; however, it provides general ideas on the reservoir

properties. This is important for the setting parameters for first simulations in ECLIPSE. The geology

of the field should not be neglected in adjusting the parameters as we could see in previous section

that faults could play a major role in pressure distribution due to their transmissibility. To wrap things

up, the history matching is a long process and requires a lot of investigation on different parameters

and one should always try to understand the geology and the dynamics of the reservoir in order to

generate an appropriate model for the field.

11. References

CORNELL SYRIA PROJECT http://atlas.geo.cornell.edu/syria/

Robert K. Litak, Muawia Barazangi, Graham Brew, Tarif Sawaf, Anwar Al-Imam and Wasif Al-

Youssef Structure and Evolution of the Petroliferous Euphrates Graben System, Southeast

Syria AAPG Bulletin, V. 82, No. 6 (June 1998), P. 11731190.

History matching Report

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