Copyright 2007, International Petroleum Technology Conference This paper was prepared for presentation at the International Petroleum Technology Conference held in Dubai, U.A.E., 46 December 2007. This paper was selected for presentation by an IPTC Programme Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the International Petroleum Technology Conference and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the International Petroleum Technology Conference, its officers, or members. Papers presented at IPTC are subject to publication review by Sponsor Society Committees of IPTC. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the International Petroleum Technology Conference is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of where and by whom the paper was presented. Write Librarian, IPTC, P.O. Box 833836, Richardson, TX 75083-3836, U.S.A., fax 01-972-952-9435.

Abstract In some of Iranian oil reservoirs gas is injected for pressure maintenance as well as displacement of oil by gas. In some of these fields, it comes to a premature breakthrough of injected gas due to high permeability in some regions of the reservoir or because of the geometry of the reservoir.

Foam injection appears to be a promising tool in solving the problem with thief zones and low recovery from EOR methods such as immiscible gas injection in Iranian oil reservoirs. It can also mitigate the effect of gravity override and achieve increased displacement efficiency in these reservoirs.

Introduction Field application of foam is becoming a proven technology, surfactant costs withstanding, to control the mobility of gaseous phases in porous media. Foam has been employed in large number of documented field trials world wide [1].

Typical applications span from steam and co2 foam to alleviate gravity override and channeling, production well treatments to reduce GOR, to gelled-foams for long-lasting plugging of high permeability channels. Foam processes have also been studied and field tested for use as groundwater aquifer clean up methods [1].

Foam has been employed in more than 30 documented field trials world wide, mainly in the USA. In the North Sea, foam has been tested in production well treatments both on the Oseberg field and on the Snorre field in the Norwegian sector, and on the Beryl-field in the British sector. Late in 1998, a large injector treatment started on Snorre, involving injection of almost 1000 tonnes surfactant [2].

In the present work, foam is injected into the reservoir and then using a field-scale simulation study, we investigate the effect of foam injection on gas mobility and oil recovery improvement. The obtained results reveal a significant

incremental recovery. Gas breakthrough is also retarded remarkably. Geological Overview of the Field The M field was discovered in 1962/63 and subsequent drilling has confirmed two reservoirs (Asmari and Bangestan). This simulation study is concerned only with the shallower Asmari reservoir.

It was put on production in 1974. A total of 47 wells have now been drilled on the field, of which 12 are dedicated to producing the Asmari reservoir and one well utilized as an observation well.

The Asmari formation is recognized as a regionally extensive geological unit, and it is known to contain a number of large oil accumulations; one of these is located at M field. Despite some complex reservoir lithology, there is good evidence of pressure communication within the Asmari between some of the different accumulations around the Ahwaz area. This is associated with a strong subsurface aquifer system.

The structure is a northwest-southeast trending asymmetric anticline. It is defined by seismic with no surface expression, and it is located on the Khuzestan plain. This area slopes gently at a rate of 1 m in 5 km to the southwest between Ahwaz and Khorramshahr. The M structure is located some 60 km north of the Persian Gulf.

The Asmari structure covers an area 42 x 5.5 km at the mapped spill point (around 2,400 mss). The hydrocarbon- bearing reservoir covers an area 30 x 3 km with the reservoir crest located at 2,144 mss.

The M structure has a dip of 6 to 8 and 5 to 6 on the northeast and southwest flanks respectively. However, the dip decreases toward the southeastern and northwestern extremities.

The first field study for the Asmari was prepared by BP in 1974 using 3 wells. That study divided the Asmari into 5 units.

Zone 1: Upper carbonate Zone 2: Upper sandstone Zone 3: Middle carbonate Zone 4: Lower sandstone Zone 5: Lower carbonate In 1978 Shir Mohammadi reviewed the reservoir and

separated it into 8 zones. Zones 1, 6 and 8 were mainly carbonate whereas Zones 2, 3, 4 and 5 were mainly sandstone, and Zone 7 was locally sandy.

Zone 1: Carbonate rocks. Zone 2: Sandstone (mainly).

IPTC 11181

A Full-Field Simulation Study of the Effect of Foam Injection on Recovery Factor of an Iranian Oil Reservoir S.M. Seyed Alizadeh, SPE, and N. Alizadeh, SPE, Amir Kabir University of Technology, and B. Maini, SPE, University of Calgary

2 IPTC 11181

Zone 3: Sandstone (mainly). Zone 4: Sandstone (mainly). Zone 5: Sandstone (mainly). Zone 6: Carbonate rocks. Zone 7: Carbonate rocks with local sandstone

developments. Zone 8: Carbonate rocks The present simulation study has retained the 8 zone

model. The first 3 zones plus a very small part of Zone 4 are recognized as oil bearing. Thus, the simulation model is based on three hydrocarbon bearing layers.

The Foam Model ECLIPSE 2002a version simulator is used for the current simulation study.

The physics of the foam flooding process is in general very complex. For example, when foam bubbles form in a porous medium the bubble size will typically fill the pore size of the rock matrix. These bubbles will tend not to move until they are compressed (hence reducing their size) by applying a higher pressure. Then in turn more bubbles will be generated at the new higher pressure, but with the original bubble size [3].

The Foam Model of this simulator is a preliminary model. It does not attempt to model the details of foam generation, flow and collapse. In this model we assume the foam is transported with the gas phase, and hence we model the foam by a tracer in the gas phase that accounts for adsorption on to the rock and decay over time [3].

Simulation Model Description The reservoir to be modeled consists of 9 layers. Zone 1 is a fractured zone, thus the first three layers have been defined as fractured using its relevant keyword in GRID section of the input data file. Within the limits of the available data, and recognizing there are some fractured layers in the reservoir, a dual porosity model was selected as the most practical approach for the reservoir modeling under present conditions. The position of the fractured layers is illustrated in figure 1.

After creating the structural framework and property model, the desired type of griding system can be implemented for the model. It is worthwhile to note that a corner point griding has been used for this purpose.

The number of grid cells in reservoir simulation (up-scaled) model is 048,691256 = grid cell for M Asmari Reservoir, as been detailed in table 1. However, one should note that the same number of grid cells are allocated for fracture cells as the model is dual porosity. As a consequence the total number of cells sums up to 12,096.

Table 1-Details of reservoir griding

Direction No. of Grids

X 56

Y 12

Z 9

Fig. 1-Schematic of the reservoir model with fractured layers of zone I

PVT Analysis of the Field The reservoir fluid is an undersaturated oil of 29 API gravity, viscosity of 1.18 cp and a GOR of 450 SCF/STB. The bubble point pressure is around 2,155 psia. The crude is characterized as a sweet Iranian intermediate-gravity.

Dry Gas data entry

The properties of gas above the dew point or well beyond the critical point are specified as a table of formation volume factor and viscosity versus pressure. The keyword format is columns of pressure, gas formation volume factor and viscosity in that order from left to right. Instead of representing in tabular form, Bg and g data, are shown in figures 2 and 3 respectively.

Fig. 2-Gas Formation Volume Factor (Bg) as a function of pressure

Fractured Layers

Single Poosity Layers

IPTC 11181 3

Live Oil data entry The properties of oil above (undersaturated) and below

(saturated) the bubble point are entered as a table of pressure, formation volume factor and viscosity versus bubble point Gas/Oil Ratio. The undersaturated FVF and viscosity must be specified at the highest pressure in the table.

The corresponding data which consist of o are illustrated in figure 3 whilst those include Rs and Bo is portrayed in figure 4.

It should be noted that there are usually some additional data which defines the properties of undersaturated oil at the specified values of RS corresponding to each bubble point pressure in the experiments. These are the Oil FVF as well as the oil viscosity above the bubble point as a function of pressure.

There are 31 tables each of which contains the above data. In order to avoid huge volume of data in tabular form to be included in this paper, they are shown in figures 5 and 6.

Fig. 3-Viscosity of Oil and Gas phases as a function of pressure

Fig. 4-Bubble Point GOR and Oil FVF as a function of pressure

Fig. 5-Oil FVF (Bo) above the bubble point as a function of pressure

Fig. 6-Oil Viscosity (o) above the bubble point as a function of pressure Water PVT data entry

The PVT properties of water are also declared in the model. At reference pressure of 3840 psia, water viscosity of 0.65 cp, formation volume factor of 1.027 bbl/STB and compressibility of 5.35e-6 psi-1 was entered for the current model.

Reference densities of the phases

All PVT properties are functions of pressure in the black oil model. The surface densities of each component are also pressure and temperature dependent.

The data used for the model is oil density of 54.33 lb/ft3, water density of 69.23 lb/ft3 and gas density of 0.068 lb/ft3.

Increasing pressure direction

Increasing pressure direction

4 IPTC 11181

Porosity/Permeability Relationship The iso-permeability maps in this model were built using a porosity/permeability relationship. To obtain the relationship, using routine core analysis, core data measurements of samples taken from different layers were used, and then by applying geometrical average the following correlations were attained:

Zone I: ( )( )

==

68.271.360098.068.223.13097.0

gx

gx

forEXPKforEXPK

(1)

Zone II: ( )( )

==

68.227.32038.068.265.21063.0

gx

gx

forEXPKforEXPK

(2)

Zone III: ( )( )

==

68.238.27098.068.208.21196.0

gx

gx

forEXPKforEXPK

(3)

where g is the matrix grain density whose data is provided

in the form of pre-generated maps. The above correlations were entered in the simulator (Property Calculator in FloGrid) to generate the iso-K maps.

According to the following three criteria, 10 different rock types have been classified for matrix using their relevant formula. The 11th rock type represents the fractures.

Lithology of the layers comprising the reservoir Capillary behavior of the rock samples in the lab Porosity frequency distribution of each lithology

Fluid and Rock-Fluid Interaction Data The SCAL data (Saturation Tables) including capillary pressure and relative permeability which are utilized in defining the saturation distribution and the mechanism of multiphase flow in porous media should be determined for each rock type of the reservoir.

There are two series of relative permeability and PC measurements on the rock samples; the Gas/Oil system as well as the Water/Oil system. To obtain the sets of Gas/Oil and Water/Oil curves each belonging to a specific rock type the following procedure was performed in Core Lab:

At first, all the test data were classified based on

the 10 rock type categories. For every rock type all the available test data were

collected, analyzed and averaged.

These averaged curves provide a basis for attaining the desired Kr and Pc curves in accordance with each rock type. The special core analysis on the rock samples has determined the hysteresis in capillary pressure curves. Hysteresis Option

The results of special core analysis reveal that hysteresis exists in the core samples.

Since there are 11 rock types in the model, including the fractures, and the existence of hysteresis necessitates a couple

of curves (drainage and imbibition) of Pc for each rock type, hence a voluminous number of saturation tables are used in the current model.

For fracture system, relative permeability was set equal to saturation (straight line relative permeability). Also, the capillary pressure in the fractures was neglected (Pcf=0).

Below comes the drainage as well as imbibition Pc curve for rock type 10 as an example (figures 7 to 10).

Fig. 7-Drainage capillary pressure curve for Oil/Water system

Fig. 8-Imbibition capillary pressure curve for Oil/Water system

Drainage

Imbibition

IPTC 11181 5

Fig. 9-Drainage capillary pressure curve for Oil/Gas system

Fig. 10-Imbibition capillary pressure curve for Oil/Gas system Permeability Anisotropy To account for the anisotropy in the vertical direction, the core data were plotted on a log-log scale and the relation 89.02606.0 XY = was proposed based on the best straight line passing through the data-points. Thus, a value of

hv KK = 89.0 for permeability in the Z-direction has been used in the model. More details are shown in figure 11.

Defining Fracture Properties To define the porosity, permeability and also Net-to-Gross Ratio for the fracture cells, the relevant data are entered as listed in table 2.

It is worthwhile to note that by the aid of fracture analysis of FMI logging files as well as tracer testing, different fracture properties have been determined. Fracture spacing in X, Y and Z directions was considered as 100ft, 100ft and 20ft respectively. However, an equivalent matrix-fracture coupling

factor, , of 0.011 was defined for the simulation model based on the Kazemi and Gilman equation [4].

Fig. 11-Vertical/Horizontal permeability relationship

Table 2-Property Data for Fracture Cells

Property value

NTG 1

Porosity 0.001

PermX 500 md

Fluid Contacts and Initialization In order to run a simulation, the initial conditions at the beginning of the simulation should be defined. These are:

Initial pressure and phase saturation for each grid cell Initial solution ratios, that is gas-oil and/or oil-gas

ratio for each cell Depth dependence of reservoir fluid properties, which

are API, saturated GOR, bubble point, saturated OGR and dew point versus depth.

Initial analytical aquifer conditions Fluid contact depths, that is OWC and/or GOC

For the current study, the datum depth, pressure at datum

depth, depth of WOC and capillary pressure at WOC are utilized to initialize the model. Initial pressure was specified to be 3490 psia at the reference depth of 7100 ft. initial WOC is measured to be at a depth of 7486 ft.

It should be noted that an initial GOC depth of 5000 ft is defined which is well above the top asmari depth. This is because the reservoir is initially undersaturated, thus no GOC initially exists.

The existence of an active bottom-drive aquifer for this reservoir was proved. To account for this, an analytical Carter-Tracy aquifer has been defined for this model. First, the

Drainage

Imbibition

6 IPTC 11181

aquifer was connected to the reservoir from bottom of the lowermost layer. Then, the initial aquifer properties were specified for the model. Initial quifer data are covered in table 3.

Table 3-Initial aquifer data used in the model

Property Value

Datum Depth 7100 ft

Permeability 150 md

Porosity 20%

Total Compressibility 3.6E-6 psi-1

Inner Radius 6000 ft

Thickness 200 ft

Angle of Influence 360

Matching Initial Fluids in Place The latest estimation of the OIIP for asmari reservoir in M field, based on the production data up to 2001 is 3315 MMSTB.

To make sure that the geological model which is input to the simulator is validated and the amount of initial fluids in place calculated by the simulator are in agreement with reports, first, a simulation run was carried out.

The model gives an OIIP of 3024.515 MMSTB which is unsatisfactory and not close to the estimated value noted before.

To get a match for this property, different methods can be applied. For the sake of simplicity and not to change a lot of parameters, reservoir pore volume in different layers have been changed to get an ultimate match.

Table 4 summarizes the results of different pore volume changes in order to obtain the target OIIP value for the reservoir.

The first row of the following table shows the total values of fluids in place calculated by simulator for grid blocks. An increase of 11.612 % in the initial total reservoir pore volume calculated by simulator appears to yield us an acceptable OIIP estimate.

History matching of Reservoir Past Performance Matching Parameters Estimation

In order to get an acceptable history match, correction to some of the assumptions was made and some parameters were changed.

According to uncertainty of fractures parameters and regarding to the fact that in a fractured reservoir, the main production path is from the fractures, so the fractures properties were deliberated as history matching parameters which include and transmissibility factor of the fractures.

Also, since the reservoir under study is initially undersaturated and the existence of an active aquifer has been confirmed, so the analytical aquifer parameters such as permeability, porosity, thickness, angle of influence and the aquifer connections to the reservoir (reservoir grid cells to which it can be connected) are considered as matching parameters.

Table 4-The results of matching initial fluids in place for the model

Change in Calculated

Pore Volume (%)

OIIP (MMSTB)

Total Reservoir Pore Volume

(Res. bbl)

Total Dissolved

GIIP (MMMSCF)

0 3024.515521 18741470433 1633.387632

10 3274.676346 20311937048 1768.486823

11 3299.692429 20468983710 1781.996742

11.6 3314.702078 20563211707 1790.102693

11.61 3314.952239 20564782173 1790.237792

11.612 3315.002271 20565096267 1790.264812

History matching results

In this study, several models were constructed to have a simulator model close to the reservoir real behavior. In this regard there was an effort to obtain oil production history, pressure, and GOR of the field by alteration of matching parameters in acceptable ranges and the adjustment of these amounts in the simulator model. The model was run several times for history matching purposes.

According to these conditions, the best possible matching in the field pressure, GOR and oil production rate was taken with adjustment of all matching parameters in the model. Since none of the existing wells have cut any water to date, it was not possible to take a history match of reservoir water cut. Obtained results are shown in figures 12 to 15.

The main reason of rather steep decline in the reservoir pressure could be due to low permeability of layers in zone 3. The permeabilities were increased by changing the corresponding transmissibilities of these layers.

IPTC 11181 7

0

10000

20000

30000

40000

50000

60000

70000

80000

0 5 10 15 20 25 30 35Time (Year)

Oil

Rat

e (S

TB/D

ay)

Simulated oil rateObserved oil rate

Fig. 12-Reservoir oil production rate history match

2000

2200

2400

2600

2800

3000

3200

3400

3600

0 5 10 15 20 25 30 35

Time (Year)

Pres

sure

(Psi

a)a)

)

Simulated pressureObserved pressure

Fig.13 -Reservoir pressure history match

8 IPTC 11181

Some other useful information regarding the history matching is the amount of the water encroachment by active aquifer which is present in the model. Figure 15 shows the total amount of water influx (AAQT) into the reservoir until the end of history matching period. In fact, one of the key parameters whose properties have been changed to obtain the acceptable match with the observed data

is the analytic Cater-Tracy aquifer defined in the current model. With alteration of these properties the required pressure support for the reservoir has been controlled. The total water influx by aquifer and the total water production from the wells up to the end of history matching date, as calculated by simulator, are 403.577 MMSTB and 21.374 MMSTB respectively.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 5 10 15 20 25 30 35

Time (Year)

GO

R (M

scf/S

TB)

simulated GOR

Observed GOR

Fig. 14-Reservoir Gas/Oil ratio history match

Fig. 15-Cumulative aquifer influx during history matching period

IPTC 11181 9

Prediction of Reservoir Performance Reservoir future performance, optimum production and different scenarios for production increase using EOR methods were analyzed by the use of built simulation model following adjustment of the parameters for achievement of reservoir history match in a reservoir simulation trend. With enough confidence in reservoir modeling, the performance of the reservoir for three different scenarios was evaluated. In this regard necessary restrictions were defined for production and injection wells such as extra water production, maximum bottom-hole injection pressure and minimum oil rate of each production well, etc.

Production and injection well constraints

Under production conditions, a producing bottomhole pressure of 1,000 psi is assumed for all the following scenarios. For gas injection as well as foam injection scenarios, a maximum bottomhole pressure of 3,000 psi was specified.

According to the production history of the reservoir, a maximum well oil production rate of 10,000 STB/Day is assumed. However, this value was increased to 15,000 STB/Day in the injection scenarios.

Each of the injectors, are set to have a maximum gas injection rate of 1,000 Mscf/Day.

The simulator injects gas at the maximum specified rate or at the maximum rate allowed by the bottomhole pressure constraint, whichever was less.

The Scenario of Natural Depletion

This scenario is considered as the base case for the simulation and it takes advantage of the natural power of the reservoir. No additional wells were drilled in addition to those actually drilled in the reservoir. Furthermore, there are 14 vertical producers in the model.

According to the data from drilling and completion reports, the name of the wells and the layers in which they are produced based on their chronological order is as follows: (the numbers in parenthesis denote the wellhead position of the wells)

Well P1 (34, 5) was drilled on February 12, 1974 and perforated in layers 4 to 9.

Well P7 (26, 6) was drilled on June 9, 1974 and perforated in layers 3 to 6.

Well P8 (18, 6) was drilled on March 4, 1978 and perforated in layers 2 to 4.

Well P9 (37, 5) was drilled on July 9, 1978 and perforated in layer 1 only.

Well P10 (23, 5) was drilled on September 11, 1978 and perforated in layer 1 only.

Well P11 (32, 7) was drilled on September 29, 1990 and perforated in layers 7 and 8.

Well P12 (35, 6) was drilled on September 30, 1991 and perforated in layers 3 to 8.

Well P34 (29, 7) was drilled on April 12, 1995 and perforated in layers 7 and 8.

Well P42 (21, 7) was drilled on December 8, 1998 and perforated in layer 7 only.

Well P43 (31, 6) was drilled on December 6, 1999 and perforated in layers 7 to 9.

Well P47 (33, 6) was drilled on July 9, 2001 and perforated in layers 7 to 9.

Well P48 (22, 6) was drilled on August 25, 2001 and perforated in layers 1 to 6.

Well P56 (20, 6) was drilled on June 12, 2004 and perforated in layers 7 and 8.

Well P58 (40, 5) was drilled on December 30, 2004 and perforated in layer 3 only.

Table 5 lists the cumulative oil production for each of the wells present in this scenario. Some of the wells such as P09, P34, P47 and P56, as can be observed from the figures, produce a low fraction of total reservoir oil production which makes them suitable candidates for conversion to injection wells in the following scenarios.

Table 5-Cumulative oil production of each well during primary production scenario

Well No. Cumulative oil production (STB)

P01 99,284,120

P07 106,279,050

P08 99,753,400

P09 3,087,002

P10 63,093,404

P11 49,118,240

P12 59,486,000

P34 958,520

P42 110,596,768

P43 33,572,704

P47 640,046

P48 68,316,000

P56 323,118

P58 34,580,140

The contributions of four significant drive mechanisms to

recovery are illustrated in figure 16. These mechanisms are oil expansion, rock compaction, water influx and gas influx (both solution gas drive and free gas drive).

The graph quantifies the proportion of oil produced by each physical process, accumulated during the simulation. As it can be seen, at early years of production which the reservoir fluid is still undersaturated, recovery associated with oil expansion and rock compaction are quite important and they provide a high fraction of total recovery.

Nevertheless, as time goes by and reservoir pressure declines, the major drive mechanism which is responsible for the oil production is water influx. The solution/free gas drive

10 IPTC 11181

has the lowest contribution in the oil production as it is usually the weakest drive mechanism.

Determination of Appropriate Injection Criteria Defining the Injection wells in the model

According to the geological reports of this field, reservoir seismic data is sparse, relatively old (2D only) and of poor quality. The map for the Top Asmari reservoir depth structure was created using well log information from most of the drilled wells.There are uncertainties with the structural map interpretation on the flanks and the northern and southern tip areas at either end of the reservoir where little well data was available. Due to these uncertainties, most of the wells are drilled on the crestal area of the structure.

Based on the above explanations and considering the fact that four of the production wells possess a low cumulative oil production in the first scenario (refer to table 5), the most cost-effective way of defining the injection wells is thought to be the conversion of wells P09, P34, P47 and P56 from production wells to injectors. Thus, a total number of four injectors are implemented in the injection scenarios.

Figure 17 depicts the top view of the wellhead position of the producers/injectors in those scenarios.

Sensitivity Analysis to Specify the Appropriate Perforation Intervals for Injectors

Different sensitivity runs are executed to investigate the effect of the completion interval on injection well performance.

Typically the foam will suffer from enhanced decay in the presence of water [3]. The lowermost layers (zone III layers) are adjacent to the bottom-drive aquifer. During production from reservoir, water encroaches into the neighboring layers and causes water saturation to increase in zone III. This is

quite unfavorable for the injected foam in that zone and could speed up the rate of foam decay.

Figures 18 to 20 depict the amount of injected as well as decayed foam in zones I to III. From the diagrams it can be deduced that lower layers are not favorable candidates to complete the injectors in.

As shown in figure 18, it is clear that very little fraction of the total injected foam is decayed when it is injected to the fractured layers which constitute the uppermost zone (Zone I) of the reservoir.

In the case of injection into zone II, as illustrated in figure 19, considerable amount of the injected foam becomes ineffective by adsorption and decay over time.

According to figure 20, the foam decay increases rapidly when injected in zone III. Thus, inadequate foam remains in solution to assist in mobility reduction of the injected gas. This could lead to lower sweep efficiency in the reservoir. The reason for such a finding could be the vicinity of Zone III layers by the aquifer. This, in turn, causes water saturation to increase in these layers as water encroaches into the reservoir. As mentioned previously, water saturation has a detrimental effect on foam stability and speeds up its acceleration.

Furthermore, due to the gravity override phenomenon, injected gas does not lead to high vertical sweep efficiency if injected into lower layers.

Based upon the above discussion, the first three layers (zone I) are chosen to be completed in the injectors.

The carbonate rocks of the uppermost zone (Zone I) appear to have more tendency to adsorb the injected surfactant in comparison to the other zones which mainly consist of sandstones. However, laboratory experiments on core samples taken from different zones with different lithology should be done to confirm this conclusion.

Fig. 16-Cumulative oil production obtained from different drive mechanisms in natural depletion scenario

water influx

oil expansion rock compaction

gas influx

IPTC 11181 11

Injected, Adsorbed and Decayed Foam

0

100000

200000

300000

400000

500000

600000

700000

11323 12323 13323 14323 15323 16323 17323time (Days)

Am

ount

of F

oam

(LB

)-

Total Injected Foam

Decayed Foam

Adsorbed Foam

Fig. 17-Top view of the locations of the injection wells used in injection scenarios

Injected, Adsorbed and Decayed Foam

0

100000

200000

300000

400000

500000

600000

700000

11323 12323 13323 14323 15323 16323 17323

Time (Days)

Am

ount

of F

oam

(LB

)-

Total Injected FoamDecayed FoamAdsorbed Foam

Fig. 18-Amount of injected, adsorbed and decayed foam in zone I Fig. 19-Amount of injected, adsorbed and decayed foam in zone II

Location of injectors

12 IPTC 11181

Fig. 20-Amount of injected, adsorbed and decayed foam in zone III

The Scenario of Immiscible Gas Injection

The second scenario to be presented is injection of immiscible gas into the reservoir under study. Based on the results from the previous scenario, four of the production wells (P09, P34, P47 and P56) have been converted to injectors. Besides, four additional wells were drilled as producers in the most prolific areas of the reservoir. The field plateau target oil rate was selected as 120,000 STB/Day.

The original producers in the first scenario (with the exception of P9, P34, P47 and P56) are defined in the same way (identical completion intervals and wellhead positions) for this scenario. The following additional producers were drilled as infill wells:

Well P61 (29, 5) was drilled vertically on January 12, 2005 and perforated in layers 4 to 7.

Well P63 (19, 5) was drilled vertically on January 12, 2005 and perforated in layers 4 to 7.

Well P70 (32, 5) was drilled vertically on January 12, 2005 and perforated in layers 4 to 7.

Well P79 (38, 6) was drilled vertically on January 12, 2005 and perforated in layers 4 to 7.

The Scenario of Foam Injection

This is the last scenario to be considered in the current study. Like the former scenario, some wells initially as producers are changed into injection wells after some years of production (P09, P34, P47 and P56). Also, the same additional wells are drilled as producers in January 12 2005. The field plateau target oil rate was selected as 120,000 STB/Day.

The concentration of foam in the injection stream of each injector was set as 0.03 lb/STB.

Comparison of Different Scenarios In order to compare the above scenarios, each group of results is plotted in the same graph. As it can be seen from figure 21, foam injection maintains reservoir pressure compared to other

scenarios. The lowest average pressure for this case is around 2000 Psia.

As shown in figure 22, the producing GOR has a dramatic increase for the case of immiscible gas injection and it becomes steady at approximately 1.5 MSCF/STB. The use of foam appears to be quite effective in decreasing the amount of GOR.

Fig. 21-Reservoir pressure comparison in injection scenarios with base case

Fig. 22-Reservoir GOR comparison in scenarios No.2 and 3 with base case

Utilizing immiscible gas injection, the field oil production rate reaches a plateau of 120,000 STB/Day steadily for almost two years and becomes stabilized at around 50,000 STB/Day during last 5 years of production.

As depicted in figure 23, the use of foam has resulted in a plateau rate of 120,000 STB/Day which maintains for nearly

Injected, Adsorbed and Decayed Foam

0

100000

200000

300000

400000

500000

600000

700000

11323 12323 13323 14323 15323 16323 17323time (Days)

Am

ount

of F

oam

(LB

)-

Total Injected Foam

Decayed Foam

Adsorbed Foam

Beginning of prediction

foam injection

immiscible gas injection

immiscible gas injection

foam injection

Beginning of prediction

IPTC 11181 13

five years and becomes steady at 51,000 STB/Day during last three years.

The key parameter to assess the feasibility of an EOR process is the recovery factor achieved by it. Regarding figure 24, it is observed that the best scenario from recovery factor viewpoint is scenario No.3. Foam injection has resulted in incremental oil recovery in excess of 10% compared to the natural depletion. However, economical analysis must confirm this scenario.

Fig. 23-Oil production rate comparison in injection scenarios with base case

With regard to the table presented below, foam injection scenario is the recommended case for future development of the filed under study.

According to little difference in recovery factor between first and second scenarios and also considering the fact that the cumulative gas production is very high in the second case, injection of immiscible gas is not economically justifiable

Fig. 24-Recovery comparison in different scenarios during the prediction phase (last 15 years)

Table 6-Short description of the simulated cases

No. of wells

Case No.

Cumulative Oil

Production (MMSTB)

Cumulative Gas

Production (MMMSCF) Old wells

New wells

Incremental Recovery

Factor ( % of OIIP)

Pressure at the end

of simulation

(Psia)

Time on Plateau

Rate (Years)

Comments

BC(no injection) 727.93 489.24 14 --- 4.4 1802 ---- ---

Immiscible Gas injection 879.214 637.5 14 4 8.4 1940 2

Four of the wells converted to injectors in 2005.

Four new producers drilled in 2005

Foam injection 1069.076 480.18 14 4 12.4 2060 5

Four of the wells converted to injectors in 2005

Four new producers drilled in 2005

Beginning of prediction

immiscible gas injection

foam injection

immiscible gas injection

foam injection

14 IPTC 11181

Conclusions 1. According to the obtained results, foam injection

appears to be promising tool in decreasing the gas-oil ratio. While injecting the same amount of gas as in immiscible gas injection process, the amount of GOR in foam injection is remarkably diminished. This eliminates the demand for early upgrading the degassing and NGL facilities to cope with large volume of produced gas. Therefore, use of foam is economically justifiable compared with injection of immiscible gas.

2. Based on the attained results of the study, foam injection maintains the reservoir pressure, hence preserves the potential energy of reservoir and prevents from early depletion of reservoir.

3. The application of foam has a significant effect on increasing the recovery factor of the reservoir. Thus, it can be implied that the use of foam flooding improves the sweep efficiency considerably and recovers additional oil from unswept areas of the reservoir. The supporting reason for this conclusion is the attained results that exhibit the higher incremental recovery factor of the reservoir, achieved by applying foam compared with injection of immiscible gas.

4. Care should be taken in selecting the completion intervals for injectors. As discussed previously, foam decay can be accelerated in presence of high water saturation. This, in turn, results in reducing the effectiveness of the injected foam. So one should avoid completing the injection wells in the layers close to aquifer.

Recommendations To be able to reach the production target and increase the total recovery during the decline period, a special focus on further data acquisition and comprehensive reservoir studies is essential. Data acquisition and further studies are needed as an integrated part of the field developments, and the development plans should regularly be revised taking new knowledge into account. This will contribute to reduce uncertainty and improve success rate of new wells. An improved reservoir understanding is of special importance for evaluation of extensive IOR efforts, like gas injection and infill drilling. In general, the following issues are recommended:

1. The model is suitable for scoping studies of future development schemes, but it can be improved by adding information such as core data obtained from new drilling. The existing development well density is very low, and is equivalent to one well per 8 km2 (2,000 acres). Most of the reservoir is of very good quality and consequently reservoir sweep efficiency could be improved with closer well spacing.

2. Fractures play an important role for production performance and reservoir properties. Fracture characterization plays an important role in further field development. Necessary data for development of a reliable fracture model to predict direction, size, special distribution and frequency of natural fractures

is needed, and should be included in the reservoir model.

3. Since the data used in the foam model are not related to the Asmari reservoir, an experimental reservoir study on core samples from this reservoir should be conducted to obtain the foam data of the particular filed under study.

4. Data for better understanding of fluid contacts, pressure regimes and communication in the reservoir is needed.

Nomenclature

cP = capillary pressure

gB = gas formation volume factor

g = gas viscosity = matrix shape factor

oB = oil formation volume factor

o = oil viscosity rK = relative permeability

Acknowledgment Special thanks are due to management of Tehran Petroleum Research Center for permission to use their license of ECLIPSE simulator. References

1. Kovscek, Anthony R.: Reservoir Simulation of Foam Displacement Processes, 7th UNITAR international conference, Beijing, China, Oct. 27-31, 1998.

2. Torleif Holt, Frode Vassenden and Amir Ghaderi: Use of Foam for Flow Control of Gas, 9th oil and gas conference, RIPI, Iran.

3. Eclipse 100 Technical Description 2002a, Schlumberger Geoquest, 2002.

4. Gilman J. R., Kazemi, H.: Improvements in Simulation of Naturally Fractured Reservoirs, paper SPE 10511 presented at the 6th SPE Symposium on Reservoir Simulation, New Orleans, Louisiana, Jan. 31-Feb. 3, 1982.