SwellingExtraction Test of a Small Sample Size for Phase Behavior Study

Abstract Slimtube measurement is one of the standard experimental techniques used for determining the minimum miscibility pressure MMP of an oil and injection gas system prior to the in

SPE 153383

A New Look at the Minimum Miscibility Pressure (MMP) Determination from Slimtube Measurements

Abiodun Matthew Amao, SPE; Shameem Siddiqui, SPE; Habib Menouar, SPE, Bob L Herd Department of Petroleum Engineering, Texas Tech University

Copyright 2012, Society of Petroleum Engineers

This paper was prepared for presentation at the Eighteenth SPE Improved Oil Recovery Symposium held in Tulsa, Oklahoma, USA, 14–18 April 2012

This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s) Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s) The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers 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 SPE copyright

Abstract

Slimtube measurement is one of the standard experimental techniques used for determining the minimum miscibility pressure (MMP) of an oil and injection gas system prior to the initiation of an enhanced oil recovery (EOR) project It is preferred because it involves actual fluid displacement in a porous medium However, the specific criterion for determining the cut-off point during the measurement is not uniquely agreed upon in the literature Different criteria have been proposed by research-ers and this has been one of the setbacks of using Slimtube measurements

The most commonly used criterion is the 1.2 PV criterion, which uses the recovery after injecting 1.2 pore volumes of the displacing gas as the cut-off However, experimental observations show that even at supercritical condition, the volume of a gas is a strong function of the experimental pressure Therefore, there is a need to develop an alternative means of determin-ing the MMP that is not subject to particular pore volumes injected durdetermin-ing Slimtube measurements

This work presents different means of determining the MMP, based entirely on recovery and the particular displacement phe-nomenon In this approach, two new parameters are defined – the instantaneous recovery rate (IRR) and the oil recovery rate (ORR) The maximum values for these parameters for each experiment are used as the cut-off value

This new criteria was used in analyzing nine experimental data using oil from the Permian Basin The results were compared with MMP prediction based on maximum recovery from each of the runs and the results were found to be in agreement These new criteria will provide consistent cut-off point for experimental runs because Slimtube measurements take a long time to complete The new procedure ensures that adequate data have been gathered during each experimental run, sufficient for a consistent experimental analysis

Introduction

The measurement of the MMP is of immense interest in the petroleum industry, several experimental procedures, correla-tions, numerical routines and algorithms have been proposed in the literature Experimental methods include Slimtube mea-surement (Yellig et al., 1980), rising bubble technique (Christiansen et al., 1987), vanishing interfacial tension (Rao, 1997) Numerical methods include single and multiple cell models, 1-D Slimtube simulations (Metcalfe et al., 1973, Neau et al, 1996) Analytical methods are based on method of characteristics (Wang, 1998) Empirical methods are the different correla-tion based prediccorrela-tion methods as presented in the literature (Emera et al., 2005, Emera et al 2006, Huang et al 2003) However, of all these methods the Slimtube experimental method is the most standard procedure for predicting the MMP This is a dynamic experiment which is designed to mimic a one dimensional reservoir The Slimtube is a cylindrical tube, with a diameter of 0.25 inch with length ranging from 25 –75 ft It is packed with uniform sand or glass beads and it is housed in a temperature bath The tube is initially saturated with the reservoir oil above its bubble point pressure (i.e single phase oil) The oil is then displaced by the proposed injection gas from the tube at a fixed experimental pressure controlled by

a back pressure regulator Miscibility conditions are determined by conducting the experiment at various pressures or injec-tion gas enrichment levels and recording the oil recovery The recovery data is then plotted against the pressure and the curve

is used in predicting the MMP Different criteria have been proposed in the literature for identifying the MMP from this ex-perimental procedure

Background and Theory

Miscibility has become a very important concept in the design and operation of gas injection processes The attainment of

miscibility in any miscible injection process is the optimal operational regime for the process Therefore, it is of special

im-portance in miscible gas injection processes Thermodynamically, two or more fluids are termed miscible if a mixture of the

fluids forms a single phase whenever the fluids are mixed in any proportion at a particular condition of pressure and

tempera-ture (or a particular thermodynamic state) Therefore, when two fluids attain miscibility, the interface between them vanishes,

i.e the interfacial tension (IFT) equals zero Two or more fluids are said to be first contact miscible (FCM) if the resulting

mixture is a single phase fluid whenever the fluids first come in contact and are mixed in any proportion Multi-contact

misc-ible (MCM), this implies the two fluids become miscmisc-ible after several contacts Therefore, a fundamental premise of MCM is

that the fluids must contact each other numerous times and exchange components back and forth until miscibility is attained

and a single phase system results Classically, MCM has been explained by two governing mechanisms, these are the

vapo-rizing gas drive and the condensing gas drive mechanisms

Vaporizing gas drive (VGD) mechanism occurs if miscibility between an injected lean gas and the reservoir oil is achieved

by the enrichment of the injected lean gas with medium and intermediate hydrocarbon components from the reservoir oil

The lean gas basically vaporizes (strips) these components off the oil, becomes richer, and due to several multiple contacts

becomes miscible with the oil As the injected gas migrates through the reservoir, its composition changes gradually from the

initial value to a critical composition, which is the point of miscibility with the reservoir oil The zone in which the

composi-tion of the injected gas gradually changes from its initial state to the reservoir fluid composicomposi-tion is called the transicomposi-tion zone

(Rathmell et al., 1971) This is a complex thermodynamic phenomenon driven by the chemical potential of the two fluids and

their composition Here, miscibility is controlled by the reservoir oil composition

Condensing gas drive (CGD) mechanism occurs if miscibility is attained between an enriched injection gas and the reservoir

oil through the condensation (loss) of the intermediate components of the gas to the reservoir oil The multiple contacts

be-tween the two fluids lead to the enriching of the reservoir oil until it attains a critical composition, at which point it becomes

miscible with the injection gas Here, miscibility is controlled by the composition of the injected gas, which is also called its

enrichment level

MCM is achievable only when the compositional path goes through the critical state of the system The critical composition

of a hydrocarbon system is unique MCM is a strong function of temperature, pressure and composition of the injected gas

and reservoir fluid However, we assume hydrocarbon reservoirs to be isothermal without a significant variation in

tempera-ture (although this assumption may not be valid for compositionally grading reservoirs) This implies that the only variables

that can be controlled by petroleum engineers are reservoir pressure and injection gas composition (since we cannot change

the reservoir oil composition) This leads to two very important concepts in MCM, these are the minimum miscibility

pres-sure (MCM) and the minimum miscibility enrichment (MME)

The MMP is the lowest pressure at which the injected gas and the oil in place become multi-contact miscible At this

pres-sure, the displacement process becomes very efficient The MME at a particular pressure is the lowest possible enrichment

level of a given component or a group of components in the injection gas which results in multi-contact miscibility The

MMP and the MME are conceptually the same They both define the same physical phenomenon but from two different

an-gles The MMP defines it as a variation in pressure to achieve miscibility while the MME defines it as a variation in the

injec-tion gas composiinjec-tion to achieve miscibility Therefore, the accurate predicinjec-tion of MMP/MME is of prime importance in the

design and optimization of any miscible gas injection process

Experimental Methodology

The methodology employed for this experimental study is presented in this section Carbon Dioxide (CO2) was used as the

injection gas in this experimental study The Slimtube apparatus used was manufactured by Ruska; however some

modifica-tions were made to the original design to accommodate the data acquisition system and a differential capillary tube in the

flow stream

Oil Sample

The crude oil sample used for this study, hereafter referred to as oil sample, was obtained from G R Brown and Associates

It is from a well in their Garza field, located in the Permian Basin and Garza County of West Texas The sample is a

separa-tor sample (stock tank), which implies that it was obtained at separasepara-tor conditions The oil has a specific gravity of 0.849 at

60/60 oF, which corresponds to an API gravity of 35.16o

Apparatus

The experimental apparatus consists of the CO2 loading apparatus, the Slimtube experimental setup and the data acquisition

system Figure 1 is the schematic presentation of how CO2 was transferred from the CO2 cylinder to a floating piston

accumu-lator (FPA) used in the setup Figure 2 shows the schematic diagram of the Slimtube setup, as stated earlier, modifications

were made to the original Ruska design to integrate the data acquisition system and a thin capillary tube The aim of the

ca-pillary tube was to further characterize the effluent property of the fluid being displaced from the Slimtube A Quizix pump

was used for the fluid displacement The data acquisition system is based on the National Instruments LabVIEW software

and their compact field point hardware The connection of the pressure transducers to the field point and ultimately to the

data acquisition computer is shown in figure 2 The volume of the fluid effluent is recorded by connecting an electronic bal-ance to the data acquisition

Experimental Procedure

The experimental procedure is presented in two parts, first the CO2 loading procedure and secondly the Slimtube experimen-tal procedure The CO2 loading procedure was used to safely transfer CO2 from the supply bottle at a pressure of 800 psi to higher pressure in the FPAs needed for the experiments Figure 1 shows this layout; vacuum was pulled on the CO2 supply line to evacuate any air from the two FPAs Both FPAs were then filled with CO2 from the CO2 cylinder, after which valve B was close and FPA-1 was used to load up FPA-2 Thus FPA-2 had a CO2 at higher pressure, the pressure was monitored us-ing the data acquisition system

The Slimtube experimental procedure is in three parts, the Slimtube pre-experimental clean-up and preparation, experimental run and post-experimental clean-up Prior to this the volume of the porous medium in the Slimtube had been determined The Slimtube was prepared for the experiment by cleaning it with Toluene, after which the heating system was turned on and al-lowed to equilibrate Kaydol 35 was used as the bath oil, its properties were found to be most suitable for the experimental conditions Nitrogen gas was then connected to the Slimtube and the system was blown-down, after this, vacuum was pulled

on the porous medium to evacuate the Nitrogen gas The Slimtube was then filled with the sample oil, the fill-up was contin-ued until a consistent sample was observed at the effluent The experimental set point was determined by the backpressure applied on the system as shown in figure 2

The already loaded CO2 gas in the FPA was then connected to the Slimtube setup, the CO2 gas was then loaded into the resi-dent FPA in the Slimtube apparatus Once the CO2 loading had been completed, the system was allowed to equilibrate, and the experiment was commenced

After the experiment, the Slimtube was cleaned using Toluene, this was done to prevent any residual CO2 gas in the porous medium and to prevent the formation and deposition of Asphaltenes in the porous medium The same procedure outlined above was then followed to prepare the Slimtube for the next experimental run

The experiments were conducted at a constant and flow rate of 0.25 cc/min, which corresponds to 15 cc/hr The injection of

CO2 was continued until the incremental recovery recorded was zero, the experiment was deemed completed at this point Several experiments were conducted and the results are presented and analyzed in the next section

Results and Analysis

In this section the Slimtube data are presented The first set of data presented is the raw data acquired using the data acquisi-tion system designed for the experiments The raw data have null recovery time; while the other set have only data during oil recovery active times The null recovery time is basically the time it took the system to build pressure up to and above the prevailing back pressure preset on the system The experiments were designed this way so that the whole history of system pressure buildup, to CO2 breakthrough and end of the experiment can be captured This approach helped in a holistic assess-ment and analysis of the data; also it prevented any surge in pressure or perturbations in the Slim tube during the experi-ments Experiments were conducted at nine pressure points, figure 3 shows the injection pressure recorded during the expe-riments Figures 4 through 12 show the injection and back pressures and the recovery volume for each experimental run Fig-ure 13 is the recovery plot versus pore volume injected (PVI) for all the experimental run

Data Analysis and MMP Prediction

In this section, a detailed analysis of the data acquired in the course of the Slimtube experiments is presented Several de-rived plots were made to investigate the dynamics of the Slimtube experiments and improve on the measurement and evalua-tion criteria as it is practiced today The MMP was calculated using the standard methodology of plotting recovery vs pres-sure and drawing a line through the sloping part and the straight line part, the intersection of which gives the MMP In the literature, several criteria have been proposed for predicting the MMP from a Slimtube experiment Some of the criteria and definition of the MMP are;

̇ The pressure that causes 90% oil recovery at 1.2 P.V of gas injected (William et al., 1980)

̇ An oil recovery of 94% when the gas-oil ration reaches 40,000 scf/bbl (Holm and Josendal, 1974)

Egwuenu, (2004) also listed the following criteria among others;

̇ Distinct point of maximum curvature when cumulative recovery of oil at 1.2 PV of gas injected is plotted vs pressure

̇ Distinct point of maximum curvature when recovery of oil at gas breakthrough is plotted vs pressure

A critically look at these criteria reveals a fundamental non-uniqueness Also from the recovery curves of all the runs pre-sented in figure 13, it is apparent that the 1.2 PV criteria cannot be a consistent one, considering that different pore volumes

of the injection gas has to be injected for different experimental pressures

A comparison was made to show the recoveries at these “known” pore volume criteria and a plot of each of these has been made, this is presented in Table 1 and figure 14 It is obvious that the classic shape of the MMP curve is not apparent; hence the MMP cannot be determined from these plots

The volume of a gas is still a strong function of pressure even at supercritical conditions, the critical pressure and temperature

of C02 is 1070 psia and 88 oF respectively However a look at the plot of density vs pressure for different temperatures for

CO presented in figure 15 shows that huge variability in the density with increase in pressure This explains why pore

vo-lumes are still immensely affected by the experimental pressures, even at supercritical conditions

A critical look at the recovery plot in figure 13 shows that the point at which recovery plateaus is a function of the

experi-mental pressure Also as the pressure decreases, more pore volume of the displacing gas has to be injected into the Slimtube

This implies that fixing a cut-off point from which the recovery is gotten in predicting the MMP is not adequate A more

con-sistent methodology is required, one that will be equally applicable irrespective of the operating pressure of the experiment

In this work, new criteria are proposed; these criteria are based on an intrinsic property of the experimental procedure and

recovery This new method is not affected by the “variable” pore volume injection criteria

The most important factor in a Slimtube experiment is the oil recovery, and for any miscible EOR process, we want to

max-imize recovery from an asset In addition to the known injected pore volume cut offs, the maximum recovery from a

Slim-tube had also been proposed as a criteria for determining the MMP, as presented by Egwuenu (2004) This criterion was also

used in choosing the points to plot on the classic recovery vs pressure plot for MMP determination This is presented in

fig-ure 25 and 26; table 2 shows the pore volumes at which these maximum recoveries were observed for each of the runs None

was below the 1.2 P.V criteria Also more limiting are the other criteria that stipulates particular recovery percentage This

data shows that much more than 1.2 PV is required to get the maximum recovery for a pressure point during Slimtube

expe-riments as indicated by the PVI @ maximum recovery column It can be understood that expeexpe-riments cannot go on forever,

however a representative recovery for each data point is essential for data analysis

The plots made included the conventional MMP plot and new rates plots, two types of rates were investigated These rates

are the instantaneous recovery rate (IRR) and oil recovery rate (ORR) These rate plots throw more light into understanding

the acquired Slimtube data Also a new approach is presented on how to consistently analyze Slimtube data based on the

newly proposed rate plots

The first derived data presented is the oil recovery rate (ORR), cumulative rate is calculated using the expression stated in

equation 1;

(1) This is recovery over the time taken

Figure 16 shows the plot of the calculated oil recovery rate with PVI The plot shows a unique inflection point on the data

which has a sharp turn for the high pressure plots while the inflexion point is not has sharp for the low pressure data

Interes-tingly, the maximum oil recovery rate does not have any unique physical significance based on analysis However, these

plots reveal the following salient points;

̇ Oil recovery rate is faster (higher) at higher pressure compared to lower pressures

̇ For the same pore volume of injection gas, more recovery is gotten at high pressure compared to low pressure

̇ Once the maximum ORR is achieved, decline sets in the oil recovery rate, decline is more rapid at higher pressure than

lower pressures

The ORR for all the runs was presented earlier in figure 16, this curve shows a maximum point and a point of inflexion in the

data This point is the first of the proposed new criteria; it is the maximum ORR of the data set

A plot of the maximum ORR for each of the experimental run versus the experimental pressure shows a linear trend with a R2

value of 0.9745; this is presented in figure 17 This implies a significant correlation between pressure and ORR

The second rate plot is the instantaneous recovery rate (IRR) The IRR is defined by the expression given in equation 2;

The time step is the time interval over which the data is acquired by the data acquisition system In this study, the time step

used is 10 seconds The IRR for each of the experimental run is presented in figures 18 through 26 As can be seen from the

figures, the unique point signifying maximum IRR is obvious in all the figures The only ones with a noisy IRR data are

fig-ures 19 and 20; however all the other figfig-ures have clear and distinctly observable maximum IRR This unique point and its

corresponding recovery is the newly proposed IRR cut-off to be used in predicting the MMP

̇ Calculate oil recovery rate (ORR) and the instantaneous recovery rate (IRR) for all the recovery data acquired for each

experimental run, using equation 1 and 2 respectively

̇ Determine the maximum ORR and IRR for each experimental run and record the corresponding recovery at these

maxi-mum points for each experiment

̇ Make plots of the recovery (either raw or percent) at these points vs pressure for each criterion, just as in the classic

MMP plot

̇ Predict the MMP from any of these two plots

Figure 27shows the maximum recovery percentage vs experimental pressure The classic shape of the MMP curve is imme-diately apparent from looking at these figures From figure 28 and has shown on the plot, the MMP is determined to be about

1570 psi Figure 29 percent recovery at maximum ORR, the MMP is estimated to be 1565 psi from figure 30, which is

rea-sonably close to that predicted using the maximum recovery plot Figure 31 is the percentage recovery plot at maximum IRR,

the predicted MMP using the maximum IRR is 1550 psi

These results show that the MMP can be predicted accurately within an acceptable tolerance while using the newly proposed maximum ORR and maximum IRR criteria These new criteria will eliminate doubts in whether sufficient pore volumes has been injected during an experiment, because once the maximum ORR or IRR is determined during an experiment, the expe-rimentalist will be sure that sufficient volume of gas has been injected to predict the MMP for the oil system The maximum IRR is an inherent characteristic of each experimental run because it relates to the injection gas breakthrough time

Conclusions and Recommendations

Two new criteria have been presented and demonstrated as adequate in predicting the MMP These criteria has presented should further help in clarifying ambiguities inherent with MMP cut-offs based on pore volume injection These new criteria are based on recovery rates and their occurrence is an inherent function of the displacement process These same criteria are equally applicable to any MMP measurement irrespective of the injection gas used

The success of CO2 miscible gas injection projects is greatly dependent on the reservoir pressure The MMP as the name im-plies is a minimum pressure at which miscibility can occur, however, for sufficient recovery, the MMP has to be exceeded It

is apparent from the experiments that the displacement efficiency of CO2 is better at higher pressure because CO2 is highly compressible and as the pressure is increased, the density increases hence its displacement efficiency increases

Acknowledgement

The authors wish to acknowledge the financial support given by the Bob L Herd Department of Petroleum Engineering, Texas Tech University The authors also acknowledge Mr J McInerney for his support with the experiments

References

1 Ahmadi, K and Johns, R.T 2008 Multiple Mixing-Cell Method for MMP Calculations Paper SPE 116823, presented at the SPE Annual Technical Conference and Exhibition held in Denver, Colorado, September 21st – 24th

2 Christiansen, R.L and Haines, K.H 1987 Rapid Measurement for Minimum Miscibility Pressure with the Rising-Bubble

Appa-ratus SPE Reservoir Engineering 2 (4): 523-527 SPE 13114-PA

3 Dadina N Rao.1997 A New Technique of Vanishing Interfacial Tension for Miscibility Determination Fluid Phase Equilibria,

139, 311-324 Elsevier Science

4 Egwenu, A.M 2004 Improved Fluid Characterization for Miscible gas Floods Master’s thesis, University of Texas at Austin, Austin, Texas

5 Emera, K.M and Sarma H.K 2006 A Reliable Correlation to Predict the Minimum Miscibility Pressure when CO2 is Diluted

with other Gases SPE Reservoir Evaluation & Engineering, 366-377

6 Emera, K.M and Sarma, H.K 2005 Use of Genetic Algorithm to Estimate CO 2 -oil Minimum Miscibility Pressure-A key Para-meter in Design of CO 2 Miscible Flood Journal of Petroleum Science and Engineering 46, 37 -52

7 Holm L.W and Josendal V.A 1974 Mechanism of Oil Displacement by Carbon Dioxide Paper SPE 4736-PA Journal of

Petro-leum Technology, Volume 26,(12) 1427-1438

8 Huang, Y.F., Huang, G.H., Dong, M.Z and Feng, G.M 2003 Development of an Artificial Neural Network for Predicting

Min-imum Miscibility Pressure in CO2 Flooding Journal of Petroleum Science and Engineering 37, 83-95

9 Jarrell P.M., Fox C.E., Stein M.H and Webb S.L Practical Aspects of CO2 Flooding Monograph Series Volume 22, SPE,

Rich-ardson, TX

10 Kechut, N.I., Zain, Z Md., Ahmad, N and DM Anwar, Raja DM Ibrahim 1999 New Experimental Approaches in Minimum Miscibility Pressure (MMP) Determination Paper SPE 57286 presented at the SPE Asia Pacific Improved Oil Recovery Confe-rence held in Kuala Lumpur, Malaysia, 25th- 26th October

11 Metcalfe, R.S., Fussel, D.D and Shelton, J.L 1973 A Multi-cell Equilibrium Separation Model for the Study of Multiple Con-tact Miscibility in Rich Gas Drive Paper SPE 3995 presented at SPE-AIME 47th Annual Fall Meeting, held in San Antonio

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117, 265-272 Elsevier Science

13 Rathmell, J.J, Stalkup, F.I and Hassinger, R.C 1971 A Laboratory Investigation of Miscible displacement by Carbon Dioxide Paper SPE 3483, presented at the 46th Annual Fall Meeting of the Society of Petroleum Engineers of AIME, held at New Orleans, Louisiana, October 3 rd -6 th

14 Wang, Y 1998 Analytical Calculation if Minimum Miscibility Pressure PhD dissertation, Stanford University, Stanford, Cali-fornia

15 William, C A., Zana, E.N and Humphrys, G.E.1980 Use of the Peng-Robinson Equation of State to Predict Hydrocarbon Phase Behavior and Miscibility for Fluid Displacement Paper SPE 8817 presented at the first joint SPE/DOE Symposium on Enhanced Oil Recovery, Tulsa, Oklahoma

16 Yellig W F and Metcalfe R.S 1980 Determination and Prediction of CO 2 Minimum Miscibility Pressure Journal of Petroleum

Technology, 160-168

CO 2 Cylinder

Vacuum Pump

Trap

Water Reservoir

Quizix Pump

Floating Piston Accumulators (FPA)

7 Micron Filter

:Three-Way Valve

Pressure Gauge

Measuring Cylinder

Vent

FPA-2

Relief Valve

A

: Two-way Valve

FPA-1

Figure 1: Schematic Diagram of the CO 2 Loading Procedure

Water Collector Water

Reservoir

Quizix Pump

Soltrol 170

CO 2

Electronic Balance

Compact Fieldpoint

Pressure

DeMod DeMod

BPR

TC TC

DPT DPT

DPT: Differential Pressure Transducer

DeMod: Demodulator

BPR: Back Pressure Regulator

Oil Bath

TC-120 AI-112 cFP-2200

B

A C

D

Sight Glass

Figure 2: Schematic of the MMP Experimental Set-up

Figure 3: Injection Pressure vs PVI for all Runs Figure 4: Pressures and Recovery vs PVI @ 500 psia

Figure 5: Pressures and Recovery vs PVI @ 750 psia Figure 6: Pressures and Recovery vs PVI @ 1000 psia

Figure 7: Pressures and Recovery vs PVI @ 1250 psia Figure 8: Pressures and Recovery vs PVI @ 1500 psia

Figure 9: Pressures and Recovery vs PVI @ 1750 psia Figure 10: Pressures and Recovery vs PVI @ 2000 psia

Figure 11: Pressures and Recovery vs PVI @ 2500 psia Figure 12: Pressures and Recovery vs PVI @ 3000 psia

Figure 13: Recovery vs Pore Volume Injected (PVI) for all Runs

Table 1: Percent Recovery at Different Pore Volume Injected

500 2.7514 3.6353 5.6665

750 3.5756 5.2877 8.7081

1000 6.0309 8.3690 12.9325

1250 5.1544 7.3515 11.7541

1500 12.8565 17.9117 30.0048

1750 21.9832 33.9096 80.3450

2000 11.1503 19.6013 54.9985

2500 34.3303 85.9567 87.4906

3000 57.9736 87.8251 88.0850

Figure 14: Plot of Recovery at Suggested Pore Volume for MMP Evaluation

Figure 15: Density vs Pressure Plot at Different Temperatures (Jarell et al., 2002)

0

10

20

30

40

50

60

70

80

90

100

0 500 1000 1500 2000 2500 3000 3500

Pressure (psi)

Recovery at Different Pore Volume Cut-offs

Recovery @ 1.0 PV (%) Recovery @ 1.2 PV (%) Recovery @ 1.5 PV (%)

0

10

20

30

40

50

60

Pressure (psi)

Density @ 80 F Density @ 100 F Density @ 150 F Density @ 200 F

Figure 16: Oil Recovery Rate (ORR) vs PVI for all Runs Figure 17: Maximum Oil Recovery Rate (ORR) vs Pressure

Figure 18: Oil Recovery and IRR vs PVI @ 500 psi

Figure 19: Oil Recovery and IRR vs PVI @ 750 psi Figure 20: Oil Recovery and IRR vs PVI @ 1000 psi