SPE 96844

Light-Oil Air-Injection Performance: Sensitivity to Critical ParametersL.A. Adetunji,* SPE, NTNU and Total E&P Norge; R. Teigland, SPE, Total E&P Norge; and J. Kleppe, SPE, NTNU

Copyright 2005, Society of Petroleum Engineers This paper was prepared for presentation at the 2005 SPE Annual Technical Conference and Exhibition held in Dallas, Texas, U.S.A., 9 – 12 October 2005. This paper was selected for presentation by an SPE Program Committee following review of information contained in a proposal submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Papers presented at SPE meetings are subject to publication review by Editorial Committees of the Society of Petroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to a proposal of not more than 300 words; illustrations may not be copied. The proposal must contain conspicuous acknowledgment of where and by whom the paper was presented. Write Librarian, SPE, P.O. Box 833836, Richardson, TX 75083-3836, U.S.A., fax 01-972-952-9435. Abstract The objective of this study is to determine parameters that have major impact on the recovery from air injection into low permeable fractured chalk reservoirs that produce light oils, such as the Ekofisk field in the Norwegian North Sea. Earlier works on air injection into light oil reservoirs mainly focused on mathematical modeling of air injection and also on laboratory studies. In this paper, we present results from numerical simulation study. Results show that when recoveries from low permeability and high permeability reservoirs are compared, recovery is accelerated in the former. In addition, for maximum recovery, air should be injected into all layers containing hydrocarbons. The ultimate recovery from air injection was observed to be insensitive to the amount of water injected during the secondary recovery phase. Also, for optimum recovery, there exists a minimum temperature at which air should be injected, this temperature being a function of the injection rate. Lastly, we observed that residual oil saturation to gas does not have any significant effect on the recovery factor from air injection. These results are only valid for single porosity systems and may not all apply to dual porosity systems. Also, no economic analysis was undertaken in this study. Introduction In recent years, High Pressure Air Injection (HPAI) has proven to be a valuable EOR process, especially in deep, high pressure, low permeability fields, where other recovery processes are uneconomic. As stated by Moore et al 1, HPAI is loosely defined as an EOR process in which compressed air is injected into a high gravity, high pressure oil reservoir, with the expectation that the oxygen will react with a fraction of the reservoir oil at an elevated temperature to produce flue gas. The produced flue gas usually comprises 10 to 14% CO2, with the rest being N2. * Now with Texas Tech U.

In its simplest implementation, the process is initiated simply by injecting air, which will spontaneously ignite the in- place oil due to the high temperature and pressure conditions in the reservoir. The desire to obtain optimum recovery from an air injection project requires the engineer to employ competent field development practices. This necessitates the knowledge of parameters that have significant effect on the performance of a reservoir. The possible application of air injection to light-oil reservoirs in the North Sea has been the subject of research in recent years. The giant structures of North Sea oil fields and the large amount of residual oil after secondary recovery make the consideration of air-injection as an enhanced oil recovery (EOR) mechanism worthwhile. Currently, air-injection is being considered as a possible EOR mechanism in the Ekofisk field, Norway. We present result of the first part of a series of studies focusing on the possible application of air injection in the Ekofisk field. While further studies would be conducted using dual porosity systems, this initial study utilizes single porosity reservoir models. The Ekofisk Field The Ekofisk field, discovered in 1969, is located in the southern part of the Norwegian sector of the North Sea. The field consisting of two producing reservoirs, one each in the upper Ekofisk formation and the lower Tor formation, is a naturally fractured chalk field with low matrix permeability and high porosity. In between the two producing reservoirs is a layer commonly referred to as the tight zone, which acts as an impermeable barrier throughout most of the field. Original oil in place was estimated to be 6.4 billion barrels of oil. The original fluid was an undersaturated, moderately volatile crude oil with a 36o API gravity and a 1,530 scf/stb solution GOR. Reservoir porosity ranges between 25% and 40%. Matrix horizontal permeability varies between 0.1 and 5md depending on porosity. Fractures enhance overall permeability and yield effective permeability that is an order of magnitude higher. Vertical effective permeability is between 0.001 and 0.1 times that of horizontal effective permeability. The field is currently being waterflooded as a means to improve oil recovery.

2 SPE 96844

Study Method Using a thermal compositional simulator, a 2-D reservoir model was built incorporating a pesudoized 6-component EOS fluid characterization and core analysis data taken from the Ekofisk field. The effects of model grid-sizes were then evaluated. Subsequently, sensitivity analyses were performed on permeability, perforation profile, amount of water injected before start of air-injection, temperature of injected air and residual oil saturation to gas, to determine their effects on recovery. PVT Model Description Pseudoization. The Ekofisk fluid characterization used in this study is as provided by Okamoto2. To make the thermodynamic fluid description as simple as possible, the 12-component Ekofisk fluid characterization was reduced to 6 components using Peng Robinson equation of state. The volatility of the components was taken into consideration during the lumping of the components. The lumping comprises N2, C02, C1 and pseudo-components ‘lite’, ‘medium’ and ‘heavy’. N2 and C02 were treated as separate components since they are non-hydrocarbons and both make up the resultant flue gas. Also, as C1 is a major component in the live oil, it was not lumped with any other component. The pseudoization procedure ensured that the 6-component characterization is representative of the 12-component fluid model. Table 1 shows the live oil composition/lumping. Reactions and Stoichiometry. The oxidation reactions involve a high number of components and are very complex. A 5-equation model was therefore used in this study. This implies 5 equations for each reactive pseudo-component. With 3 reactive pseudo-components, namely ‘lite’, ‘medium’ and ‘heavy’, the simulation needs 15 equations. Consequently, the degree of freedom, which is the degree of uncertainty, is too high. As some of the reactions are limited in time and eventually all reactions result in the production of flue gas, the global equation below as suggested by Okamoto2 was used as a first approximation at the reservoir scale for each reactive component:

( ) OHxCOCOOxCH x 222 2111

4122

++

++

⇒⎥⎦

⎤⎢⎣

⎡+

++

+β

βββ

β

Where,

2/ COCO=β

CHx /=

Simulation Runs Description Grid Effect. The relative permeability curves shown in Figs. 2-3 and a rock permeability of 500md were used for all the models. Water was injected into the system for the first 400 days at an in-situ injection rate of 90 m3/d and the production well was constrained at 90 m3/d in-situ total liquid rate. After 400 days, air at a temperature of 200oC was injected into the reservoir and air-injection was maintained as the recovery mechanism till the end of production, using the same production/injection rates as that used for water injection. Four models, 5x1x2, 6x1x2, 9x1x2 and 12x1x2 were used for this set of sensitivity analysis. Table 2 shows the grid configurations while the model parameters are as given in Table 3. As shown in Fig. 4, for all the models, the cumulative oil production was approximately 47,800 Sm3 which translates to a recovery factor of 87.5%. The remaining oil was apparently burnt as fuel to maintain the combustion. The cumulative oil production plot revealed that there were only marginal differences in the production profiles of the models with 9 and 11 grids in the x-direction. Grid effect was very apparent in the cumulative gas production as shown in Fig. 5. Grid effect was also observed in the injection rate. The more grids used, the longer the production life of the system. For the range of injection rates (i.e. 30 m3/d to 120 m3/d) used in this study, convergence problems were encountered when the model had more than 11 grid blocks in the x-direction. Hence, it was decided to use the model with configuration 9x1x2 as the base model. For the other sensitivity analyses, the model below was used, unless otherwise stated:

i. 9 grid cells in the x-direction (base model). The reason for the decision was that it was the most stable and least affected by grid effects. ii. Relative permeability curves shown in Figs. 2-3. iii. Rock permeability value of 500md. iv. Water was injected into the system at 90 m3/d (in- situ) for the first 400 days and the production well was constrained at 90 m3/d (in-situ) total liquid rate. Air injection at 200 oC started immediately afterwards

and air was maintained as the injected fluid till the end of the simulation run.

Composition of produced oil/gas with time. For all the models used in this study, the composition with time of the produced oil and gas, exhibited the same trend. Hence, only the composition of the oil and gas produced over the entire life of base model (model with 9 grid cells in the x-direction) will be analyzed. Fig. 6 shows the composition of the oil produced over the life of the reservoir. It was observed that the main components of the produced oil were the heavy and medium pseudo-components. However, while the percentage of the heavy pseudo-component increased with time, that of the medium pseudo-component dropped and eventually, the total percentage of all the other components except the heavy pseudo-component dropped to 0.3% while that of the heavy pseudo-component increased to 99.7%. It is worthy of note that there was no oxygen breakthrough until the end of the producing life of the reservoir.

SPE 96844 3

From Fig. 7, it was observed that before gas breakthrough, methane and lite pseudo-components were the main components in the gas produced. However, as soon as there was gas breakthrough, nitrogen and carbon dioxide were the main components in the gas produced, each making up an average of 82.5% and 16.3% respectively. Also, just as for produced oil, there was no oxygen breakthrough until the end of the producing life of the reservoir. Sensitivity to Permeability. This set of simulation runs examines the effect of rock permeability on the performance of air-injection particularly high temperature oxidation which was observed for Ekofisk oil. Three models with permeability values of 50md, 100md and 500md were used for this set of runs. During the period of air-injection, air was injected at a rate of 90 m3/d (in-situ) while the production well was constrained at 90 m3/d (in-situ) total liquid rate. While all the models produced the same cumulative oil and gas, it was observed that the oil production was accelerated in the model with 50md permeability (Fig. 8). The lowest production rate was obtained for the system with 500md as shown in Fig. 9. The same trend was observed for the gas production rate. For a better understanding of this trend which is contrary to that observed in water and immiscible gas injection, we analyzed the rate of movement of the flood front through the three models. As observed in Figs. 10-12, the velocity of the combustion front was highest in the 50md formation and consequently resulted in acceleration of production. The least velocity was observed for the 500md formation. We can infer from this trend that the main factor affecting oil production in these systems is thermal effect, while the effect of viscous forces was secondary. The oil saturation in all the grid cells for all the models was zero at the end of the simulation runs (Fig. 13). However, the temperature in the grid cells at the end of the simulation period for all the models was directly proportional to the systems’ permeability. The highest temperature was recorded for the model with 500md permeability while the lowest was recorded for the model with 50md (Fig. 14). Sensitivity to Perforation Profile. For this set of simulations, the effect of perforation profile on air-injection was examined. Three models were constructed; one model had the production well perforated only in the top layer, the second model had the production well perforated only in the bottom layer while the last model had the production well perforated in both layers. During the period of air injection, air was injected at a rate of 90 m3/d (in-situ) while the production well was constrained at 90 m3/d (in-situ) total liquid rate. It was observed that the production profiles were the same for the two cases in which only one layer was perforated for production i.e. cases with only layer 1 and only layer 2 perforated for production respectively. The production rates from these cases were higher than from the case in which both layers were perforated. However, the highest cumulative production was obtained when both layers were perforated for production. Also, there was no significant difference in the cumulative oil produced from both cases with the production well perforated in only one layer, as shown in Fig. 15.

For cumulative gas produced, there was no difference between the case in which the production well was perforated in both layers and that in which it was perforated in the top layer only. However, a slightly lower cumulative gas production was observed when the production well was perforated in the lower layer only (Fig. 16). At the end of the simulation period for all the models, the temperature distribution in the grid cells for the two cases in which the production well was perforated in only one layer was almost the same. However, the highest temperature was exhibited by the model in which both layers were perforated for production (Fig. 17). This is probably due to the significantly higher cumulative gas injection for this model when compared with the other two models. Only the model in which both layers were perforated for production had zero oil saturation in all the grid blocks at the end of simulation. For both models in which only one layer was perforated for production, except for the first two grid cells closest to the injector, the oil saturation in the other layer that was not perforated showed minimal changes throughout the simulation period (Fig. 18). Sensitivity to Temperature at which Air is injected. The objective of the two sets of simulation runs performed in this sensitivity analysis was to determine the effect of the temperature at which air was injected on the performance of an air-injection project. In the first set of simulations, the rates of production and injection during the air injection period were set at the same in-situ value of 60 m3/d and air was injected at 150 oC, 200 oC and 250 oC respectively. The cumulative oil production from the three scenarios is shown in Fig. 19. The highest cumulative production was obtained when injecting at 200oC while the lowest cumulative production was obtained when air was injected at 150oC (the simulation stopped at about 2000 days as the reactions were not self-sustaining). This was probably due to the fact that the rate of heat generation was smaller than the rate of heat loss. Injecting air at 150oC and 250oC resulted in sub-optimal oil recovery from the reservoir. The oil saturation in all the grid cells at the end of the simulation was zero only for the scenario in which air was injected at 200oC. However, it was observed that for the cases in which air was injected at 200oC and 250oC, there was no significant difference in the temperature distribution at the end of simulation. Another set of simulation was run with the injection/production rates during the air injection period set at in-situ value of 120 m3/d while air was injected at 250 oC. This was then compared with the scenario in which the injection/production rate was set at in-situ value of 60 m3/d and air injected at 200oC. The cumulative oil production was the same for the two scenarios, Fig. 21, while the cumulative gas production was higher for the scenario in which the injection/production rates were set at 60 m3/d (in-situ) and air injected at 200oC. However, the oil saturation in all the grid blocks at the end of simulation was zero for both scenarios, while the temperature in the grid blocks was generally higher for the scenario in which the injection/production rates were set at 120 m3/d and air injected at 250oC (Fig. 24).

4 SPE 96844

It was observed from both Figs. 20 and 23 that the gas-oil ratio is directly proportional to the temperature at which air is injected. Sensitivity to amount of water injected before start of Air Injection. Three models were used for this sensitivity analysis. From start of simulation, water was injected at 90 m3/d (in-situ) until 30%, 45% and 60% pore volume (PV) had been injected respectively in the 3 models used. During the period of air-injection, air was injected at 120 m3/d (in-situ) while production rate was set at 120 m3/d (in-situ) total liquid rate. An additional simulation was run in which a total of 3.8PV water was injected before air-injection started. Fig. 24 showed that the cumulative oil production was independent of the amount of water injected before start of air- injection; as the same cumulative oil production was obtained in all the cases. The producing life of the reservoirs was least for the case in which 0.3 PV water was injected before injecting air, and longest for the case in which 3.8 PV volume water was injected before start of air injection. For all the models, the oil saturation in all the grid blocks was zero at the end of simulation (Fig. 25). Sensitivity to Residual Oil Saturation to Gas (Sorg). Sensitivity analysis was performed on the residual oil saturation to gas (Sorg) to determine its effect on air injection. Two relative permeability models with the same saturation exponents but different Sorg of 15% and 25% were used for this set of runs. The other end points are the same for the two models and relevant data are given in Table 3. While both models produced the same cumulative oil and gas, the recovery was accelerated in the model with Sorg of 15% as shown in Fig 27. At the end of the simulation runs for both models, there was no significant difference in the grid temperature distribution (Fig 29). Also, for both models, the oil saturation in all the grids was zero. This implies that unlike immiscible gas injection, the residual oil saturation to gas does not have significant effect on the recovery. Conclusions Based on the homogeneous single porosity reservoir model used in this study, the following conclusions were arrived at:

1. The tighter the reservoir, the smaller the project life; recovery is accelerated in lower permeability reservoirs.

2. The tighter the reservoir, the lower the system temperature at the end of air injection.

3. Within the range of permeability used in this study, the cumulative fluid production is independent of the system permeability.

4. The perforation profile has a great impact on the cumulative oil production. For optimum recovery, all hydrocarbon-containing layers should be perforated for production.

5. The cumulative oil production is independent of the cumulative amount of water injected before the start of air injection.

6. Oil recovery is sensitive to the temperature at which air is injected.

7. The residual oil saturation to gas has marginal effect on the cumulative oil produced.

Acknowledgement The authors thank Total Norge AS for financial support and permission to publish this work. In addition, special thanks to Alan Burns, Sebastien Renaud and C.H. Whitson for support during this work. Nomenclature GOR = Gas to oil ratio, Sm3/Sm3

h = height, m IOIP = Initial oil in place, m3

IGIP = Initial gas in place, m3

k = Permeability, md kv/kh = Ratio of vertical to horizontal permeability krg = Relative permeability to gas krog = Relative permeability of oil to gas krw = Relative permeability of water krow = Relative permeability of oil to water krwro = Relative permeability of Water at Sw=1-Sorw, Sg=0 krgro = Relative permeability of Gas at Sw=Swc, So=Sorgkrocw = Relative permeability of Oil at Sw=Swc, Sg=0 nw , now = Exponents for analytical relative permeabilityng, nog = Exponents for analytical relative permeability Sorw = Residual oil saturation to water Sorg = Residual oil saturation to gas Swc = Connate water saturation So = Oil saturation T = Temperature, K References

1. Moore, R. G., Mehta, S. A., and Ursenbach, M. G.:’’ A Guide to High Pressure Air Injection (HPAI) Based Oil Recovery,’’ paper SPE 75207 presented at the 2002 SPE/DOE Improved Oil Recovery Symposium, Tulsa, Oklahoma, April 13-17.

2. Okamoto, M.: Thermodynamic Characterization of Reservoir Fluid and Phase Behavior Studies of Air + Oil Mixtures, AirOil Project, Work Package 3 Report, 2004.

3. Jensen, T. B., Harpole, K. J., and Østhus, A.: ‘‘EOR Screening for Ekofisk,’’ paper SPE 65124 presented at the 2000 SPE European Petroleum Conference, Paris, France, Oct. 24-25.

4. Turta, A. T., and Singhal, A. K.: ‘‘Reservoir Engineering Aspects of Light-Oil Recovery by Air Injection,’’ paper SPE 72503, SPE Reservoir Evaluation & Engineering, (Aug. 2001).

5. Lacroix, S., Delaplace, P., and Bourbiaux, B.: ‘’Simulation of Air Injection in Light-Oil Fractured Reservoirs: Setting-Up a Predictive Dual Porosity Model,’’ paper SPE 89931 presented at the 2004 SPE Annual Technical Conference and Exhibition, Houston, Texas, Sept. 26-29.

6. Greaves, M., Ren, S. R., and Rathbone, R. R.: ‘‘Air Injection Technique (LTO Process) for IOR from Light Oil Reservoirs: Oxidation Rate and Displacement Studies,’’ paper SPE 40062 presented at the 1998 SPE/DOE Improved Oil Recovery Symposium, Tulsa, Oklahoma, April 19-22.

7. Jakobsson, N. M., and Christian, T. M.: ‘‘Historical Performance of Gas Injection of Ekofisk,’’ paper SPE 28933 presented at the 1994 SPE Annual Technical Conference and Exhibition, New Orleans, Sept. 25-28.

SPE 96844 5

8. Surguchev, L. M., Koundin A., and Yannimaras, R.: ‘‘Air Injection - Cost Effective IOR Method to Improve Oil Recovery from Depleted and Waterflooded Fields,’’ paper SPE 57296 presented at the 1999 SPE Asia Pacific Improved Oil Recovery Conference, Oct. 25-26.

9. Ren, S. R., Greaves, M., and Rathbone, R. R.: ‘‘Air Injection LTO Process: An IOR Technique for Light-Oil Reservoirs,’’ SPE Journal, (March 2002).

10. Turta, A. T., and Singhal, A. K.: ‘‘Reservoir Engineering Aspects of Oil Recovery from Low Permeability Reservoirs by Air Injection,’’ paper SPE 48841 presented at the 1998 SPE International Oil and Gas Exhibition, Beijing, China, Nov. 2-6.

11. Tingas, J., Greaves, M., and Young, T. J.: ‘‘Field Scale Simulation Study of In-Situ Combustion in High Pressure Light Oil Reservoirs,’’ paper SPE 35395 presented at the 1996 SPE/DOE Improved Oil Recovery Symposium, Oklahoma, April 21-24.

12. Athos 4.1 Simulator Release by IFP/Beicip-Franlab.

SI Metric Conversion Factors

atm x 1.013 250* E+05 = Pa bbl x 1.589 873 E-05 = m3

cp x 1.0* E-03 = Pa.s ft x 3.048* E-01 = m ft3 x 2.831 685 E-02 = m3

oF (oF-32)/1.8 = oC oF (oF+459.67)/1.8 = K lbm/ft3 x 1.601 846 E+01 = kg/m3

psi x 6.894 757 E-02 = bar psi x 6.894 757 E+00 = kPa scf/bbl x 1.801 175 E-01 = std m3/m3

* Conversion factor is exact.

Table 1: Composition/Lumping of the live oil Components MW (g/mol) Density (kg/m3) @

Standard conditions Lumping

N2 N2

C02 C02

C1 16.04 300.0 C1

C2 30.07 356.7 C3 44.09 506.7

LITE

iC4 58.12 562.1 nC4 58.12 583.1 iC5 72.15 623.3 nC5 72.15 629.9 C6 85.00 666.7

MEDIUM

C7+ 237.00 866.0 HEAVY

Table 2: Grid Size Variation Model No. No. of grids ∆x, meters

1 5 10,30,70,70,70 2 6 10,40,50, 50, 50, 50, 3 9 10,30, 30, 30, 30, 30, 30, 30, 30 4 11 10,15,25, 25, 25, 25, 25, 25, 25, 25, 25

Table 3: Reservoir and Rock Properties Reservoir Length, m Width, m Reservoir Thickness, m (2 units, 10m each) Reservoir Height, mss Permeability, md Porosity Cr, bar-1

Initial Reservoir Temperature, oC Water Injection Temperature, oC Initial Reservoir Pressure, bara at 3100m Irreducible Water Saturation Residual Oil Saturation to Water Residual Oil Saturation to Gas Critical Gas Saturation Relative permeability of Water at Sw=1-Sorw, Sg=0 Relative permeability of Gas at Sw=Swc, So=Sorg Relative permeability of Oil at Sw=Swc, Sg=0 nw, now, ng, nogBottomhole Injection Pressure, bar Bottomhole Flowing Pressure, bar Initial Oil-Water Contact, mss Initial Oil-in-Place, 103 Sm3

Initial Gas-in-Place, 109 Sm3

250 70 20 3100 500 0.34 0.000044 131 30 380 0.34 0.3 0.25 0.05 0.9 0.55 0.635 3, 2, 2.4, 2.2 450 70 3180 54.63 -

Table 4: Reservoir Oil and Air Characterization

Component

Reservoir Oil (Mole Fraction)

Air (Mole Fraction)

N2O2CO2C1Lite Medium Heavy

0.0010 0.0000 0.0085 0.4347 0.1181 0.0936 0.3441

0.79 0.21

6 SPE 96844

Table 5: Component Properties and EOS Parameters, Peng-Robinson EOS

Compo-nent

Mol. Wt.

Critical Temp. (oC)

Critical Pressure

(bar)

Critical Volume (cm3/g-

mol)

Accentric Factor

Vol. Shift

Parachor Ω-A Ω-B

N2O2CO2 CO C1Lite Medium Heavy

28.0 32.0 44.0 28.0 16.0 35.0 80.0

254.0

-146.850 -118.570 31.150

-104.700 -82.090 136.781 221.369 496.719

33.9910 50.4300 73.7500 34.9910 46.4000 67.8150 33.0384 15.6116

90.066 73.395 93.955 92.758 99.000

540.554 498.319

1067.020

0.0350 0.0222 0.2250 0.0484 0.013

-0.071779 0.260343 0.654607

-7.425 -5.426 -5.152 -9.169 -4.102 -9.827 -5.503 53.259

41.00 53.20 70.00 70.00 77.00

119.10 251.10 520.20

0.45724 0.45724 0.45724 0.45724 0.45724 0.45724 0.45724 0.45724

0.0778 0.0778 0.0778 0.0778 0.0778 0.0778 0.0778 0.0778

Binary Interaction Parameters

Compo-nent

O2 CO2 CO C1 Lite Medium Heavy

N2O2CO2 CO C1Lite Medium

-0.011

0.000 -0.053

0.0 0.0 0.0

0.12 0.02 0.15 0.00

0.1200 0.0000 0.1500 0.0000 0.0221

0.1200 0.0000 0.1500 0.0000 0.0155 0.2024

0.1200 0.0000 0.1500 0.0000 0.0945 0.1260 0.0100

Layer 1 250m

Layer 2

10m

70m

10m

Figure 1: Schematic of Reservoir Model

SPE 96844 7

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Sw

Kr

krw

krow

Figure 2: Oil-water relative permeability curve.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

1-Sg

Kr

krg

krog

Figure 3: Gas-oil relative permeability curve.

0

0.02

0.04

0.06

0 1000 2000 3000 4000 5000 6000 7000 8000 9000Time (days)

Std.

Cum

. Oil

Prod

uctio

n (1

06 Sm

3 )

5 grids

6 grids

9 grids

11 grids

Figure 4: Standard cumulative oil production for different number of grids.

0

0.02

0.04

0.06

0.08

0.1

0 1000 2000 3000 4000 5000 6000 7000 8000 9000Time (days)

Std.

Cum

. Gas

Pro

duct

ion

(109 S

m3 )

5 grids

6 grids

9 grids

11 grids

Figure 5: Standard cumulative gas production for different number of grids.

0.0

0.2

0.4

0.6

0.8

1.0

0 2000 4000 6000 8000 10000

Time (days)

Com

pone

nts

in O

il, F

ract

ion

N2

lite

C02

C1

02

medium

heavy

Figure 6: Percentage of each component in produced oil for simulation with 9 grid cells per layer in x-direction.

0

0.2

0.4

0.6

0.8

1

0 2000 4000 6000 8000 10000

Time (days)

Com

pone

nt in

Gas

, Fra

ctio

n

02C02C1N2liteheavymedium

Figure 7: Percentage of each component in produced gas for simulation with 9 grid cells per layer in x-direction.

8 SPE 96844

0

0.02

0.04

0.06

0 2000 4000 6000 8000 10000

Time (days)

Std.

Cum

. Oil

Prod

uctio

n (1

06 Sm

3 )

50md

100md

500md

Figure 8: Standard cumulative oil production for different reservoir permeabilities.

0

15

30

45

60

75

0 1000 2000 3000 4000 5000 6000 7000 8000 9000

Time (days)

Std.

Oil

Prod

uctio

n R

ate

(Sm

3 /d)

50md

100md

500md

Figure 9: Standard oil production rates for different reservoir permeabilities.

100

200

300

400

500

1 2 3 4 5 6 7 8 9

Grid

Tem

pera

ture

(o C)

50 md

100 md

500 md

Figure 10: Average temperatures after 2500 days in each model for different permeability runs.

100

200

300

400

500

1 2 3 4 5 6 7 8 9

Grid

Tem

pera

ture

(o C)

50 md

100 md

500 md

Figure 11: Average temperatures after 5100 days in each model for different permeability runs.

150

200

250

300

350

400

450

1 2 3 4 5 6 7 8 9

Grid

Tem

pera

ture

(o C)

5700 days, 100 md

5700 days, 500 md

8500 days, 500 md

Figure 12: Average temperatures after 5700 and 8500 days for the 100md and 500md models for different permeability runs.

0

0.25

0.5

0.75

1

1 2 3 4 5 6 7 8 9

Grid

Oil

Satu

ratio

n

layer2-50md-5100 days

layer1-50md-5100 days

layer1-100md-5700 days

layer2-100md-5700 days

layer1-500md-8500 days

layer2-500md-8500 days

Figure 13: Oil saturation at the end of simulations for different permeabilities.

SPE 96844 9

250

300

350

400

450

1 2 3 4 5 6 7 8 9

Grid

Tem

pera

ture

(o C)

layer1-50md-5100 days

layer2-50md-5100 days

layer2-100md-5700 days

layer1-100md-5700 days

layer1-500md-8500 days

layer2-500md-8500 days

Figure 14: Temperature distribution at the end of simulations for different permeabilities.

0

0.02

0.04

0.06

0 2000 4000 6000 8000 10000

Time (days)

Std.

Cum

. Oil

Prod

uctio

n (1

06 Sm

3 )

Perf in layer 1

Perf in layer 2

Perf in layers 1 & 2

Figure 15: Standard cumulative oil production for different perforation scenarios.

0

0.02

0.04

0.06

0.08

0 1000 2000 3000 4000 5000 6000 7000 8000 9000

Time (days)

Std.

Cum

. Gas

Pro

duct

ion

(109 S

m3 )

Perf in layer 1

Perf in layer 2

Perf in layers 1 & 2

Figure 16: Standard cumulative gas production for different perforation scenarios.

100

200

300

400

500

1 2 3 4 5 6 7 8 9

Grid

Tem

pera

ture

(o C)

6100 days-layer1-Perf in layer 1

6100 days-layer2-Perf in layer 1

5800 days-layer1-Perf in layer 2

5800 days-layer2-Perf in layer 2

8500 days-layer1-Perf in layers 1 & 2

8500 days-layer2-Perf in layers 1 & 2

Figure 17: Temperatures at end of simulations for different perforation scenarios.

0

0.2

0.4

0.6

1 2 3 4 5 6 7 8 9

Grid

Oil

Satu

ratio

n

6100 days-layer1-Perf in layer 16100 days-layer2-Perf in layer 15800 days-layer1-Perf in layer 25800 days-layer2-Perf in layer 28500 days-layer1-Perf in layers 1 & 28500 days-layer2-Perf in layers 1 & 2

Figure 18: Oil saturations at end of simulations for different perforation scenarios.

0

0.02

0.04

0.06

0 4000 8000 12000 16000 20000

Time (days)

Std.

Cum

. Oil

Prod

uctio

n (1

06 Sm

3 )

150 deg C, 60 m3/d

200 deg C, 60 m3/d

250 deg C, 60 m3/d

Figure 19: Standard cumulative oil production for different air injection temperatures at injection rate of 60 m3/d.

10 SPE 96844

0.0E+00

4.0E+04

8.0E+04

1.2E+05

1.6E+05

0 4000 8000 12000 16000 20000

Time (days)

Gas

-Oil

Rat

io (S

m3 /S

m3 )

150 deg C, 60 m3/d

200 deg C, 60 m3/d

250 deg C, 60 m3/d

Figure 20: Gas-Oil Ratio for different air- injection temperatures at injection rate of 60 m3/d.

0

0.02

0.04

0.06

0 2000 4000 6000 8000 10000 12000 14000 16000

Time (days)

Std.

Cum

. Oil

Prod

uctio

n (1

06 Sm

3 )

200 degC, 60 m3/d

250 degC, 120 m3/d

Figure 21: Standard cumulative oil production for different air- injection temperatures at injection rates of 60 and 120 m3/d.

0

0.02

0.04

0.06

0.08

0.1

0 4000 8000 12000 16000

Time (days)

Std.

Cum

. Gas

Pro

duct

ion

(109 S

m3 )

200 degC, 60m3/d

250 degC, 120 m3/d

Figure 22: Standard cumulative gas production for different air injection temperatures at injection rates of 60 and 120 m3/d.

0.E+00

2.E+04

4.E+04

6.E+04

0 4000 8000 12000 16000

Time (days)

Gas

-Oil

Rat

io (S

m3 /S

m3 )

200 degC, 60 m3/d

250 degc, 120 m3/d

Figure 23: Gas-Oil Ratio for different air-injection temperatures at injection rates of 60 and 120 m3/d.

200

250

300

350

400

450

1 2 3 4 5 6 7 8 9Grid

Tem

pera

ture

(o C)

15100 days-layer1-200 degC-60 m3/d

15100 days-layer2-200degC-60 m3/d

10700 days-layer1- 250 degC -120 m3/d

10700 days-layer2-250 degC-120 m3/d

Figure 24: Temperatures at end of simulation for different air-injection temperatures.

0

0.02

0.04

0.06

0 2000 4000 6000 8000 10000 12000 14000 16000 18000Time (days)

Std.

Cum

. Oil

Prod

uctio

n (1

06 Sm

3 )

0.3PV water injected

0.45PV water injected

0.6PV water injected

3.8PV water injected

Figure 25: Standard cumulative oil production for different total water injection before start of air-injection.

SPE 96844 11

0.00

0.25

0.50

0.75

1.00

1 2 3 4 5 6 7 8 9

Grid

Oil

satu

ratio

n

6000 days-layer1-0.3PV water injected6000 days-layer2-0.3PV water injected6695 days-layer1-0.45PV water injected6695 days-layer2-0.45PV water injected6994 days-layer2-0.6PV water injected6994 days-layer1-0.6PV water injected16000 days-layer1-3.8PV water injected16000 days-layer2-3.8PV water injected

Figure 26: Oil saturations at end of simulation for different total water injection before start of air-injection.

0

0.02

0.04

0.06

0 1000 2000 3000 4000 5000 6000 7000 8000 9000

Time (days)

Std.

Cum

. Oil

Prod

uctio

n (1

06 Sm

3 )

15% Sorg

25% Sorg

Figure 27: Standard cumulative oil production for different residual oil saturations to gas.

0

0.02

0.04

0.06

0.08

0 1000 2000 3000 4000 5000 6000 7000 8000 9000

Time (days)

Std.

Cum

. Gas

Pro

duct

ion

(106 S

m3 )

15% Sorg

25% Sorg

Figure 28: Standard cumulative gas production for different residual oil saturations to gas.

250

300

350

400

450

1 2 3 4 5 6 7 8 9

Grids

Tem

pera

ture

(o C)

layer1-15%Sorg-6900 days

layer2-15%-Sorg-6900 days

layer1-25%Sorg-8500 days

layer2-25%Sorg-8500 days

Figure 29: Temperatures at end of simulations for different residual oil saturations to gas.