COMPARISON OF CO2- EOR SIMULATION STUDIES USING CO2 – SURFACTANT CO-

INJECTION, SURFACTANT ALTERNATING CO2 GAS (SAG), AND CONTINUOUS CO2 INJECTION

IN FIELD T

Prof. Dr. Ir. HP. Septoratno Siregar, OGRINDO RC ITB, Billal Maydika Aslam, OGRINDO RC ITB

Abstract

Miscible and immiscible CO2 Flooding projects are respectively proven and potential EOR methods.

Environmental initiative such as Kyoto Protocol also encourage CO2 injection into reservoir due to potential reduction

of greenhouse gas volume. However conventional CO2 EOR methods have suffered from limited recovery efficiency

due to gravity segregation, gas override, viscous fingering and channeling through high permeability streaks.

Numerous theoretical and experimental studies as well as field applications have indicated that foaming of CO2 reduces

its mobility, thereby helping to control the above negative effects.

The objective of this study is to compare the recovery efficiency of foam methods using co-injection and

surfactant alternating CO2 gas (SAG) to conventional CO2 flooding in field-scale simulation. Simple (quasi-

equilibrium) foam model is used as incorporated in CMG-STARSTM simulator. Immiscible injection method is

preferred due to high Minimum Miscibility Pressure (MMP) and fracture pressure limitation of the selected reservoir.

The study highlight the effect of varying injection rate to oil recovery for each methods. Pattern optimization by

altering insignificant producer to injector is done as it prove higher recovery factor. Field injection parameter is also

calculated to ensure feasibility of injection in real condition. The study also suggest some aspects to increase accuracy

of the field-scale simulation.

Keywords: CO2-EOR, Foam, Co-injection, SAG, Mobility Control

Introduction

Favorable mobility ratio between oil bank and gas slug is necessary for mobilization and displacement of oil in

CO2 EOR methods. Lower mobility ratio ensure more stable displacement of slug, which prevent channeling and

segregation. Hence the purpose of foam application in CO2 EOR is to improve the control of gas mobility by altering

gas effective permeability (Fig.1). The use of foam also improve microscopic displacement efficiency by reducing

capillary forces via reducing the interfacial tensions due to the presence of surfactant.

Foam can be placed in a reservoir in four ways:

1. In co-injection, gas and aqueous surfactant solution are injected simultaneously from a single well.

Foam forms in the surface facilities where the fluids meet, in the tubing, or shortly after the fluids

enter the formation.

2. In surfactant-alternating-gas or SAG injection, gas and surfactant solution are injected in separate

slugs from a single well. Foam forms in the formation where gas meets previously injected surfactant

solution, or when surfactant solution meets previously injected gas.

3. It is possible to dissolve some surfactants directly into supercritical CO2 (Lee et al.,2008; Ashoori et

al., 2010) Then there is no need to inject aqueous surfactant solution; injected CO2 with dissolved

surfactant forms foam as it meets water in the formation.

4. Surfactant solution and gas can be injected simultaneously, but from different sections of a vertical

well (gas injected below the surfactant solution), or from parallel horizontal wells (gas injected from

the lower well) (Stone, 2004; Rossen et al., 2010).

The study will be focused on co-injection method and SAG method which are proved by laboratory experiment

to have better injectivity than preformed foam. Based on published field result, for low pressure and high permeability,

the co-injection foam is effective at normal surfactant concentration, and it can be considered for long term injection.

For high pressure and low permeability, SAG at medium or even low surfactant concentration can be considered.

For foam application to be successful, surfactant concentration used have to create ultra-low IFT so that pseudo

emulsion between oil and foam would occur (Talebian et al., 2013). Another important parameter to be considered is

Figure 1. Relative Permeability function before and after foam is added

foam quality. Based on laboratory experiment, 1:4 volume ratio of surfactant and CO2 would generate 70% - 90%

foam quality which will be suitable for foam EOR application (Brioletty et al., 2005).

Objectives

The objectives of this study are described as follows:

1. Determine and compare areal sweep efficiency (Ea), vertical sweep efficiency (Ev) and microscopic

displacement efficiency (Ed) by simulation from reservoir section

2. Determine and compare field-scale recovery factor increment of each methods from simulation

3. Optimize injection pattern based on existing producer and injector wells

4. Determine limitation of injection parameters

Reservoir Model and Properties

For better understand the effect of EOR methods, depleted brownfield reservoir model is used. Secondary

recovery mechanism (waterflood) has already applied in the field before the start of simulation. Selected reservoir

model is a four-way dip closure separated by sealing fault. The reservoir is a heterogeneous reservoir comprised of 10

rock types. The reservoir is divided into 7 sectors based on fault boundary. NCE sector will be used for simulation

study since it has the biggest reserve compared to other sectors (Fig 2). Selected reservoir model contains 2698 active

grid block with gross bulk volume of 517530000 ft3.

Figure 2. Aerial View of Reservoir Model and Reserves for each sector

From NCE sector, only middle part of the sector will be used in EOR simulation since it has the highest residual

oil. The oil saturation profile at the start of simulation shows that residual oil is collected in upper part of the reservoir

(Fig 3.)

Average reservoir properties of the selected reservoir model is given in Table 1. Minimum Miscibility Pressure

is calculated using Yellig & Metcalfe correlation. Overburden gradient of 1 psi/ft is assumed to be equal to fracture

gradient.

Table 1. Average Reservoir Properties

Properties Value

Average Porosity 21.5%

Initial Water Saturation 77.0%

Reservoir Temperature (Tres) 133.37 F

Initial reservoir pressure (Pres) 158.95 psi

Datum Depth 2403.33 ft

Thickness 57.2 ft

Bubble Pressure 704.17 psi

Permeability (avg) 82.5 mD

Oil Viscosity 1.1 cP

Oil Density 48.7 API

MMP (by Yellig & Metcalfe) 1938.06 psi

Fracture Gradient 1 psi/ft

Figure 3. Oil Saturation Distribution at Start of Simulation

EOR Method Screening

Technical criteria screening is done to check suitability of selected reservoir to CO2 EOR method. Criteria is

based on data from successful EOR project and oil recovery mechanism (Taber et al., 1997). Comparison of reservoir

and oil properties with technical criteria values is given in table 2.

Table 2. Reservoir & Oil Properties Screening to CO2 EOR Technical Criteria

Technical Criteria Field Condition Status

API oil > 22 48.7 OK

Viscosity <10 cp 1.1 cp OK

So >20% PV 58.9% OK

Depth >1800ft 2000 ft OK

Reservoir condition and oil properties passed all screening criteria. However, since initial reservoir pressure is

very low it is hardly possible to achieve miscibility condition although dissolution of CO2 in oil still happens. The

degree of CO2 solubility in oil will depend on pressure difference between average reservoir pressure and minimum

miscibility pressure.

Field Scale Simulation

Field scale simulation is done using CMG-STARSTM simulator. Corner point grid system is used for reservoir

model. Steady state (quasi-equilibrium) simple foam model is used both in co-injection method and SAG method.

Surface injection rate is varied for each method by 0.05 PV/year, 0.1 PV/year and 0.15 PV/year. Each method is

applied for 20 years, starting from 1st January 2015. Simulation constraints used in field-scale simulation is given in

table 3.

Table 3. Simulation Constraints for Field Scale

Simulation Constraints

Producer Wells

#wells 3 wells

Min. BHP 300 psi

Max. Water cut 99%

Max. Liquid Rate 500 STBD

Injector Wells

#well 8 wells

Max. BHP 1000 psi

Surface Injection Rate 0.05, 0.1, 0.15 PV/year

Basically, each cases are grouped by the method of CO2 EOR used, the definition of each case group are described

below

Case Group 1 – Continuous CO2

Conventional CO2 Flooding using pure CO2 gas, three different rates as defined before are simulated

Case Group 2 – Co-injection

Co-injection of CO2 gas and aqueous surfactant solution with 4:1 volume ratio, three different rates as

defined before are simulated.

Case Group 3 – SAG

Alternate injection between surfactant solution and gas with surfactant injected first as pad. 2 years cycle

is used to maintain small slug size as recommended by field result. Three different rates as defined before

are simulated with CO2 gas rate four times higher than surfactant rate to achieve 4:1 volume ratio.

Surfactant concentration used in simulation is given by simulator interpolation that gives the lowest IFT. For all

simulation using surfactant component, 0.000534 mole fraction of surfactant concentration is used.

Macroscopic Sweep Efficiency and Microscopic Displacement Efficiency Simulation

Reservoir section in NCE middle sector is carefully selected to simulate each aspect of recovery efficiency. To

determine areal sweep efficiency, a section consist of single layer (5x5x1 grid) and a producer well is selected. Single

injector well is then added in other side of section as in 5-spot injection. Considering more homogenous properties in

smaller section and no segregation effect, displacement efficiency and vertical sweep efficiency can be considered

constant or equal to 1 so that simulation in selected section will gives areal sweep efficiency based on recovery factor.

Similar principle is used for both areal sweep and displacement efficiency simulation. For vertical sweep efficiency,

1x10x10 grid is used to simulate gravity segregation. As for displacement efficiency, 10x1x1 grid is used to give

absolute sweep efficiency as also happens in slim-tube model. Grid model of each recovery efficiency simulation is

illustrated in Fig 4.

Figure 4. Simulation grid model for areal sweep (Ea), displacement (Ed) and vertical sweep (Ev) efficiency determination

Simulation for each recovery efficiency model is done for 5 years with injection rate of 0.6 PV/year. Simulation

constraint for recovery efficiency model is given in table 4.

Table 4. Simulation Constraint for Recovery Efficiency Model

Simulation Constraints

Producer Wells

#wells 1 well

Min. BHP 100 psi

Max. Water cut 99%

Max. Liquid Rate 100 STBD

Injector Wells

#well 1 well

Max. BHP 1000 psi

Surface Injection Rate 0.6 PV/year

Field Injection Parameter

Pressure gradient between injector and producer wells is checked to ensure bottom hole pressure constraint

does not exceed fracture gradient. Front velocity based on injection rate is also calculated to ensure the front velocity

is still within the limit of field practice.

Pressure Gradient of Injector-Producer Wells.

Distance between producer and nearest injector is calculated. Bottom hole pressure difference is then divided

by wells distance to give pressure gradient. Maximum injector bottom hole pressure is determined by using maximum

pressure gradient of 1 psi/ft. The result of calculation is given in table 5.

Table 5. Maximum injector BHP Calculation

mark Producer BHP(PSI) Distance (ft)

A T-141 325 A-A' 690

B T-113 300 B-B' 921

C T-049 300 C-C' 737

mark Injector BHP(PSI) Pressure Gradient(psi/ft)

A' T-117IW 1015 A-A' 1

B' T-112IW 1221 B-B' 1

C' T-112IW 1037 C-C' 1

It can be seen from the calculation that the bottom hole pressure constraint of 1000 psi is still below the

fracture pressure limit.

Front Velocity

Front velocity is calculated by assuming reservoir condition injection rate will not exceed the surface

injection rate due to compressibility. Rough calculation of front velocity can be done using equation 1.

𝑣𝐹𝑟𝑜𝑛𝑡 =

(𝑖𝑝

)𝑟𝑎𝑡𝑖𝑜

× 𝑞𝑖𝑛𝑗𝑒𝑐𝑡𝑖𝑜𝑛

𝐴𝑟𝑒𝑠𝑒𝑟𝑣𝑜𝑖𝑟 𝑖𝑛𝑗𝑒𝑐𝑡𝑒𝑑

… (1)

Where:

𝑣𝐹𝑟𝑜𝑛𝑡 ∶ 𝑓𝑟𝑜𝑛𝑡 𝑣𝑒𝑙𝑜𝑐𝑖𝑡𝑦 (𝑓𝑡/𝑑𝑎𝑦)

𝑞𝑖𝑛𝑗𝑒𝑐𝑡𝑖𝑜𝑛 ∶ 𝑖𝑛𝑗𝑒𝑐𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒 (𝑐𝑢𝑓𝑡 𝑑𝑎𝑦⁄ )

(𝑖

𝑝)

𝑟𝑎𝑡𝑖𝑜

∶ 𝑖𝑛𝑗𝑒𝑐𝑡𝑜𝑟 𝑤𝑒𝑙𝑙𝑠 𝑡𝑜 𝑝𝑟𝑜𝑑𝑢𝑐𝑒𝑟 𝑤𝑒𝑙𝑙𝑠 𝑛𝑢𝑚𝑏𝑒𝑟 𝑟𝑎𝑡𝑖𝑜

𝐴𝑟𝑒𝑠𝑒𝑟𝑣𝑜𝑖𝑟 𝑖𝑛𝑗𝑒𝑐𝑡𝑒𝑑 ∶ 𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑟𝑒𝑠𝑒𝑟𝑣𝑜𝑖𝑟 𝑐𝑟𝑜𝑠𝑠 𝑠𝑒𝑐𝑡𝑖𝑜𝑛 𝑎𝑟𝑒𝑎 𝑝𝑒𝑟𝑝𝑒𝑛𝑑𝑖𝑐𝑢𝑙𝑎𝑟 𝑡𝑜 𝑖𝑛𝑗. 𝑓𝑙𝑜𝑤

The calculation result of front velocity using highest injection rate used in simulation study is presented in table 6.

Based on field practice, it is assumed that the front velocity should not exceed 2 ft/day.

Table 6. Front Velocity Calculation

Area 11515 Ft2

(i/p)ratio 2.67 well/well

Inj. Rate 0.15 PV/year

Vfront 1.48 ft/day

Vfront_max 2.00 ft/day

It can be seen from the calculation that injection rate of 0.15 PV/year will gives 1.48 ft/day front velocity which still

below the limit of maximum front velocity.

Injection Pattern Optimization

Initial injection pattern of middle part of NCE sector is similar to staggered direct line drive. Most of injector

wells are located in bottom part of the reservoir which is not favorable for gas injection. The injection pattern is then

changed into peripheral pattern by altering insignificant producer well into injector well. Initial and edited well pattern

is illustrated in fig 5. and fig 6.

The use of edited well pattern increase field recovery factor up to 2%. Another benefit of using more injector well and

less producer well as in edited pattern is reducing front velocity and also lower well injection rate.

Result and Discussion

Macroscopic Sweep and Microscopic Displacement Efficiency

Recovery factor is plotted against pore volume injected to see the performance of recovery efficiency. Recovery

efficiency performance for each case is given in Fig 7 – 9.

Figure 7. Areal Sweep Performance

Figure 5. Initial Well Pattern. Red: injector, Black: producer Figure 6. Altered Well Pattern. Blue: altered well

0

5

10

15

20

25

30

35

40

0 0.5 1 1.5 2 2.5 3 3.5

Rec

ove

ry F

acto

r (%

)

Pore Volume Injected ()

Areal Sweep (Ea)

Ea SAG

Ea Coinjection

Ea Continuous

Figure 8. Displacement Efficiency Performance

Summary of recovery efficiency for each method is given in fig 10. Efficiency ratio (multiplier) of foam methods to

continuous CO2 method is calculated

0

5

10

15

20

25

30

35

40

0 0.5 1 1.5 2 2.5 3 3.5

Rec

ove

ry F

acto

r (%

)

Pore Volume Injected ()

Displacement Efficiency (Ed)

Ed SAG

Ed Coinjection

Ed Continuous

0

5

10

15

20

25

30

35

40

45

0 0.5 1 1.5 2 2.5 3 3.5

Rec

ove

ry F

acto

r (%

)

Pore Volume Injected ()

Vertical Sweep (Ev)

Ev SAG

Ev Coinjection

Ev Continuous

Figure 9. Vertical Sweep Performance

In general it can be seen that foam methods greatly improve recovery efficiency compared to continuous CO2 injection

almost 40 times. By comparing oil saturation distribution before and after foam method is applied, it can be proven

that foam successfully reduce gravity segregation effect (Fig 10 & 11). Co-injection method give slightly better

performance compared to SAG method especially for areal and displacement efficiency. The result confirm the field

experience that co-injection is better for low pressure and short distance injection. However, the grid may have to be

refined to better examine the effect of distance on foam performance. SAG somehow better in vertical sweep

efficiency compared to co-injection. The result arose indication of surfactant-partitioning effect on reservoir. This may

lead to the reason of periodic pattern resulted for SAG recovery efficiency. Compositional simulator should be used

to clarify the indication. s

Figure 11. Recovery efficiency summary

Figure 10. Oil Saturation at the Start of Simulation (left) and after CO2 flooded (right). Gravity segregation occured

Field Recovery Factor

In field scale simulation, recovery factor result is also plotted against pore volume injected to see the performance of

recovery efficiency. Recovery factor plot for co-injection, SAG and continuous CO2 in field scale model for 0.15

PV/year injection rate is given in fig 12.

Figure 13. Recovery Factor in Field Scale Simulation using 0.15 PV/year injection rate

The result of field scale simulation verify the result from recovery efficiency model. Irregular pattern of recovery

factor in SAG method happened because not all the gas converted into foam, thereby reducing recovery efficiency. It

has been reported that using smallest slug size possible may be improve SAG recovery performance. However slug

0

5

10

15

20

25

30

35

40

45

0.00 0.50 1.00 1.50 2.00 2.50

Rec

ove

ry F

acto

r (%

)

Pore Volume Injected ()

Field Recovery

RF SAG

Figure 12. Oil Saturation Distribution at the Start of Simulation (Left) and after Foam applied (right). Gravity override handled

size sensitivity is not performed in this study. The effect of varying injection rate to recovery factor is illustrated in

fig 14.

Figure 14. Field Oil Recovery factor vs. Injection Rate

Higher injection rate give higher recovery factor until a certain limit. The higher injection rate used, the higher

reservoir pressure increase will be. Continuous CO2 give poor RF increment. This result happened because CO2 is not

effective in increasing reservoir pressure due to its compressibility. Co-injection and SAG methods lower gas mobility

hence the effect of high gas compressibility is controlled. Simulation result also proved that SAG and co-injection

method gave higher reservoir pressure than continuous CO2 (fig 14).

47.47 47.47 47.75

57.70

64.01

68.31

58.38

64.08

67.67

40

45

50

55

60

65

70

75

80

0.05 0.1 0.15

RF

(%)

Injection Rate (PV/year)

Field Oil Recovery Factor (%)

Continuous

Coinjection

SAG

Figure 15. Reservoir Pressure profile for each method (blue: SAG, green: co-injection, black: continuous)

Conclusion

1. Both SAG and co-injection foam EOR methods greatly improve sweep & displacement efficiency compared

to continuous CO2 flooding based on simulation result using heterogeneous and depleted oil reservoir model.

CO2 volume required per unit volume of oil produced is also reduced by using SAG and co-injection method

2. For lower pressure and short distance injection, Co-injection gives slightly better recovery performance than

SAG. However grid refinement and well injectivity parameter should be checked to ensure valid simulation

result.

3. Increasing injection rate will increase reservoir pressure hence recovery factor increased due to oil swelling

by CO2. The relation between recovery factor and injection rate show an optimum condition exist.

4. Altering insignificant producer well into injector to create peripheral pattern may improve recovery

efficiency.

References

1. Peningkatan Perolehan Minyak dengan Injeksi Gas CO2 dan Surfaktan Secara Serempak”, Letty Brioletty,

Septoratno Siregar, Edward ML Tobing. IATMI. 2005

2. “Foam Assisted Enhanced Oil Recovery at Miscible and Immiscible Conditions”. R. Farajzadeh et al. Paper

SPE 126410 presented at 2009 Kuwait International Petroleum & Exhibition Conference, Kuwait, 14-16

December 2009

3. The Effect of Foam Stability in CO2-Foam Flooding”, K. Teerakijpaiboon, F. Srisuriyachai. Chulalongkorn

University. Thailand. 2013

4. “Enhanced Oil Recovery using Foam Injection; a Mechanistic Approach”, Rasak Mayowa Sunmonu, SPE,

Mike Onyekonwu SPE; Institute of Petroleum Studies (IPS), University of Port Harcourt/IFP School. 2013

5. “Foam assisted CO2-EOR : Concepts, Challenges, and Applications”, Seyedeh H. Talebian. Universiti

Teknologi PETRONAS. 2013

6. “Development of a New Foam EOR Model From Laboratory and Field Data of the Naturally Fractured

Cantarell Field”, Fraser Skoreyko. Computer Modelling Group. 2013