Estimation of Foam-Flow Parameters for Local Equilibrium Methods by Use of Steady-State Flow Experiments and Optimization Algorithms
- Authors
- Jose Sergio de Araujo Cavalcante Filho (University of Texas at Austin) | Mojdeh Delshad (University of Texas at Austin) | Kamy Sepehrnoori (University of Texas at Austin)
- DOI
- https://doi.org/10.2118/179597-PA
- Document ID
- SPE-179597-PA
- Publisher
- Society of Petroleum Engineers
- Source
- SPE Reservoir Evaluation & Engineering
- Volume
- 21
- Issue
- 01
- Publication Date
- February 2018
- Document Type
- Journal Paper
- Pages
- 160 - 173
- Language
- English
- ISSN
- 1094-6470
- Copyright
- 2018.Society of Petroleum Engineers
- Disciplines
- Keywords
- Local Equilibrium, Population Balance, Fitting Foam Model Parameters, Foam
- Downloads
- 3 in the last 30 days
- 199 since 2007
- Show more detail
- View rights & permissions
| SPE Member Price: | USD 5.00 |
| SPE Non-Member Price: | USD 35.00 |
Summary
Foam has been successfully used in the oil industry for conformance and mobility control in gas-injection processes. The efficiency of a foam-injection project must be assessed by means of numerical models. Although there are several foam-flow models in the literature, the prediction of foam behavior is an important issue that needs further investigation. In this paper, we estimate foam parameters and investigate foam behavior for a given range of water saturation by use of two local equilibrium foam models: the population balance assuming local equilibrium (LE) model and the University of Texas (UT) model. Our method uses an optimization algorithm to estimate foam-model parameters by matching the measured pressure gradient from steady-state foam-coreflood experiments. We calculate the effective foam viscosity and the water fractional flow by use of experimental data, and we then compare laboratory data against results obtained with the matched foam models to verify the foam parameters. Other variables, such as the foam texture and foam relative permeability, are used to further investigate the behavior of the foam during each experiment. We propose an improvement to the UT model that provides a better match in the high-quality regime by assuming resistance factor and critical water saturation as a linear function of the pressure gradient. Results show that the parameter-estimation method coupled with an optimization algorithm successfully matches the experimental data by use of both foam models. In the LE model, we observe different values of the foam effective viscosity for each pressure gradient caused by variations of foam texture and the shear-thinning viscosity effect. The UT model presents a constant effective viscosity for each pressure gradient; we propose the use of resistance factor and critical water saturation as a linear function of the pressure gradient to improve the match in the high-quality regime, when applicable.
| File Size | 1 MB | Number of Pages | 14 |
References
Afsharpoor, A., Lee, G. S., and Kam, S. I. 2010. Mechanistic Simulation of Continuous Gas Injection Period During Surfactant-Alternating-Gas (SAG) Processes Using Foam Catastrophe Theory. Chem. Eng. Sci. 65 (11): 3615–3631. https://doi.org/10.1016/j.ces.2010.03.001.
Alvarez, J., Rivas, H., and Rossen, W. 2001. Unified Model for Steady-State Foam Behavior at High and Low Foam Qualities. SPE J. 6 (3): 325–333.SPE-74141-PA. https://doi.org/10.2118/74141-PA.
Apaydin, O. G. and Kovscek, A. R. 2000. Transient Foam Flow in Homogeneous Porous Media: Surfactant Concentration and Capillary End Effects. Presented at the SPE/DOE Improved Oil Recovery Symposium, Tulsa, 3–5 April. SPE-59286-MS. https://doi.org/10.2118/59286-MS.
Blaker, T., Aarra, M. G., Skauge, A. et al. 2002. Foam for Gas Mobility Control in the Snorre Field: The FAWAG Project. SPE Res Eval & Eng 5 (4):317–323. SPE-78824-PA. https://doi.org/10.2118/78824-PA.
Boeije, C. S. and Rossen, W. 2015. Fitting Foam-Simulation-Model Parameters to Data: I. Coinjection of Gas and Liquid. SPE Res Eval & Eng 18 (2): 264–272. SPE-174544-PA. https://doi.org/10.2118/174544-PA.
Chen, Q., Gerritsen, M., and Kovscek, A. R. 2010. Modeling Foam Displacement With the Local-Equilibrium Approximation: Theory and Experimental Verification. SPE J. 15 (1): 171–183. SPE-116735-PA. https://doi.org/10.2118/116735-PA.
Chen, Y., Elhag, A. S., Reddy, P. P. et al. 2016. Phase Behavior and Interfacial Properties of a Switchable Ethoxylated Amine Surfactant at High Temperature and Effects on CO2-in-Water Foams. J. Colloid Interf. Sci. 470: 80–91. https://doi.org/10.1016/j.jcis.2016.02.028.
Cheng, L., Reme, A. B., Shan, D. et al. 2000. Simulating Foam Processes at High and Low Foam Qualities. Presented at the SPE/DOE Improved Oil Recovery Symposium, Tulsa, 3–5 April. SPE-59287-MS. https://doi.org/10.2118/59287-MS.
Corey, A. T. 1954. The Interrelation Between Gas and Oil Relative Permeabilities. Producers Monthly. 19 (1): 38–41.
Cui, L., Ma, K., Puerto, M. et al. 2016. Mobility of Ethomeen C12 and Carbon Dioxide (CO2) Foam at High Temperature/High Salinity and in Carbonate Cores. SPE J. 21 (4): 1151–1163. SPE-179726-PA. https://doi.org/10.2118/179726-PA.
Falls, A. H., Hirasaki, G. J., Patzek, T. W. et al. 1988. Development of a Mechanistic Foam Simulator: The Population Balance and Generation by Snap-Off. SPE Res Eval & Eng 3 (3): 884–892. SPE-14961-PA. https://doi.org/10.2118/14961-PA.
Farajzadeh, R., Andrianov, A., Krastev, R. et al. 2012. Foam–Oil Interaction in Porous Media: Implications for Foam Assisted Enhanced Oil Recovery. Adv. Colloid Interfac. 183–184 (15 November): 1–13. https://doi.org/10.1016/j.cis.2012.07.002.
Farajzadeh, R., Lotfollahi, M., Eftekhari, A. et al. 2015. Effect of Permeability on Implicit-Texture Foam Model Parameters and the Limiting Capillary Pressure. Energy Fuels 29 (5): 3011–3018. https://doi.org/10.1021/acs.energyfuels.5b00248.
Friedmann, F. and Jensen, J. A. 1986. Some Parameters Influencing the Formation and Propagation of Foams in Porous Media. Presented at the SPE California Regional Meeting, Oakland, California, 2–4 April. SPE-15087-MS. https://doi.org/10.2118/15087-MS.
Friedmann, F., Chen, W. H., Gauglitz, P. A. et al. 1991. Experimental and Simulation Study of High-Temperature Foam Displacement in Porous Media. SPE Res Eng 6 (1): 37–45. SPE-17357-PA. https://doi.org/10.2118/17357-PA.
Huh, D. G. and Handy, L. L. 1989. Comparison of Steady and Unsteady-State Flow of Gas and Foaming Solution in Porous Media. SPE Res Eng 4 (1):77–84. SPE-15078-PA. https://doi.org/10.2118/15078-PA.
Kam, S. I. 2008. Improved Mechanistic Foam Simulation with Foam Catastrophe Theory. Colloids Surface. A 318 (1): 62–77. https://doi.org/10.1016/j.colsurfa.2007.12.017.
Khatib, Z. I., Hirasaki, G. J., and Falls, A. H. 1988. Effects of Capillary Pressure on Coalescence and Phase Mobilities in Foams Flowing Through Porous Media. SPE Res Eval & Eng 3 (3): 919–926. SPE-15442-PA. https://doi.org/10.2118/15442-PA.
Kovscek, A. R. and Radke, C. J. 1994. Fundamentals of Foam Transport in Porous Media. In Foams: Fundamentals and Applications in the Petroleum Industry, Vol. 242 of Advances in Chemistry, ed. L. L. Schramm, Chap. 3, 115–163. Washington, DC: American Chemical Society. https://doi.org/10.1021/ba-1994-0242.ch003.
Kovscek, A. R., Patzek, T. W., and Radke, C. J. 1993. Simulation of Foam Transport in Porous Media. Presented at the SPE Annual Technical Conference and Exhibition, Houston, 3–6 October. SPE-26402-MS. https://doi.org/10.2118/26402-MS.
Kovscek, A. R., Patzek, T. W., and Radke, C. J. 1994. Mechanistic Prediction of Foam Displacement in Multidimensions: A Population Balance Approach. Presented at the SPE/DOE Improved Oil Recovery Symposium, Tulsa, 17–20 April. SPE-27789-MS. https://doi.org/10.2118/27789-MS.
Kovscek, A. R., Tadeusz, W. P., and Radke, C. J. 1997. Mechanistic Foam Flow Simulation in Heterogeneous and Multidimensional Porous Media. SPE J. 2 (4): 511–526. SPE-39102-PA. https://doi.org/10.2118/39102-PA.
Lotfollahi, M., Farajzadeh, R., Delshad, M. et al. 2016. Comparison of Implicit-Texture and Population-Balance Foam Models. J. Nat. Gas Sci. Eng. 31 (April): 184–197. https://doi.org/10.1016/j.jngse.2016.03.018.
Lotfollahi, M., Varavei, A., Delshad, M. et al. 2015. Development of a Hybrid Black-Oil/Surfactant Enhanced Oil Recovery Reservoir Simulator. J. Pet. Sci. Eng. 133 (September): 130–146. https://doi.org/10.1016/j.petrol.2015.05.008.
Ma, K., Farajzadeh, R., Lopez-Salinas, J. L. et al. 2014. Non-uniqueness, Numerical Artifacts, and Parameter Sensitivity in Simulating Steady-State and Transient Foam Flow Through Porous Media. Transport Porous Med. 102 (3): 325–348. https://doi.org/10.1007/s11242-014-0276-9.
Ma, K., Lopez-Salinas, J. L., Puerto, M. C. et al. 2013. Estimation of Parameters for the Simulation of Foam Flow through Porous Media. Part 1: The Dry-Out Effect. Energy Fuels 27 (5): 2363–2375. https://doi.org/10.1021/ef302036s.
Ma, K., Mateen, K., Ren, G. et al. 2016. Modeling Foam Flow at Achievable Reservoir Flow Rates Using the Population-Balance Approach and Implications for Experimental Design. Presented at the Abu Dhabi International Petroleum Exhibition & Conference, Abu Dhabi, 7–10 November. SPE-182902-MS. https://doi.org/10.2118/182902-MS.
Ma, K., Ren, G., Mateen, K. et al. 2015. Modeling Techniques for Foam Flow in Porous Media. SPE J. 20 (3): 453–470. SPE-169104-PA. https://doi.org/10.2118/169104-PA.
Nelder, J. A. and Mead, R. 1965. A Simplex Method for Function Minimization. Comput. J. 7 (4): 308–313. https://doi.org/10.1093/comjnl/7.4.308.
Osterloh, W. and Jante, M. Jr. 1992. Effects of Gas and Liquid Velocity on Steady-State Foam Flow at High Temperature. Presented at the SPE/DOE Enhanced Oil Recovery Symposium, Tulsa, 22–24 April. SPE-24179-MS. https://doi.org/10.2118/24179-MS.
Prigiobbe, V., Worthen, A. J., Johnston, K. P. et al. 2016. Transport of Nanoparticle-Stabilized CO2-Foam in Porous Media. Transport Porous Med. 111(1): 265–285. https://doi.org/10.1007/s11242-015-0593-7.
Rossen, W. R. and Boeije, C. S. 2015. Fitting Foam-Simulation-Model Parameters to Data: II. Surfactant-Alternating-Gas Foam Applications. SPE Res Eval & Eng 18 (2): 273–283. SPE-165282-PA. https://doi.org/10.2118/165282-PA.
Rossen, W. R., Zeilinger, S. C., Shi, J. X. et al. 1994. Mechanistic Simulation of Foam Processes in Porous Media. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, 25–28 September. SPE-28940-MS. https://doi.org/10.2118/28940-MS.
Rossen, W. R., Zeilinger, S. C., Shi, J. X. et al. 1999. Simplified Mechanistic Simulation of Foam Processes in Porous Media. SPE J. 4 (3): 279–287. SPE-57678-PA. https://doi.org/10.2118/57678-PA.
Sanders, A., Jones, R. M., Rabie, A. et al. 2012. Implementation of a CO2 Foam Pilot Study in the SACROC Field: Performance Evaluation. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 8–10 October. SPE-160016-MS. https://doi.org/10.2118/160016-MS.
Stevens, J., Martin, F., and Harpole, K. 1995. CO2 Foam Field Verification Pilot Test at EVGSAU: Phase IIIB--Project Operations and Performance Review. SPE Res Eng 10 (4): 266–272. SPE-27786-PA. https://doi.org/10.2118/27786-PA.
Tang, G.-Q. and Kovscek, A. R. 2006. Trapped Gas Fraction During Steady-State Foam Flow. Transport Porous Med. 65 (2): 287–307. https://doi.org/10.1007/s11242-005-6093-4.
Vassenden, F. and Holt, T. 2000. Experimental Foundation for Relative Permeability Modeling of Foam. SPE Res Eval & Eng 3 (2): 179–185. SPE-62506-PA. https://doi.org/10.2118/62506-PA.
Zeng, Y., Muthuswamy, A., Ma, K. et al. 2016. Insights on Foam Transport from a Texture-Implicit Local-Equilibrium Model with an Improved Parameter Estimation Algorithm. Ind. Eng. Chem. Res. 55 (28): 7819–7829. https://doi.org/10.1021/acs.iecr.6b01424.
Zhou, Z. and Rossen, W. R. 1995. Applying Fractional-Flow Theory to Foam Processes at the "Limiting Capillary Pressure". SPE Advanced Technology Series 3 (1): 154–162. SPE-24180-PA. https://doi.org/10.2118/24180-PA.
