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-STARS TM 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
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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.