Control of Numerical Dispersion in Streamline-Based Simulations of Augmented Waterflooding
- Abdulkareem M. AlSofi (Imperial College London) | Martin J. Blunt (Imperial College London)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- June 2013
- Document Type
- Journal Paper
- 1,102 - 1,111
- 2013. Society of Petroleum Engineers
- 5.4.7 Chemical Flooding Methods (e.g., Polymer, Solvent, Nitrogen, Immiscible CO2, Surfactant, Vapex), 5.4.1 Waterflooding, 6.5.2 Water use, produced water discharge and disposal, 5.3.2 Multiphase Flow, 5.4.2 Gas Injection Methods, 2.5.2 Fracturing Materials (Fluids, Proppant)
- 5 in the last 30 days
- 336 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 12.00|
|SPE Non-Member Price:||USD 35.00|
Augmented waterflooding is when a component is coinjected with water to modify the fractional-flow curve. Examples include polymer flooding, surfactant injection, low-salinity waterflooding, and carbonated-water injection (including applications related to carbon dioxide storage). The numerical simulation of these processes is a challenge for several reasons: The appropriate physical behavior needs to be incorporated consistently into empirical models of the fractional flow, whereas the solutions should minimize numerical dispersion, allowing the correct and accurate tracking of compositional variations.
Lower-order numerical simulations of these processes give excessive front smearing, requiring many thousands of gridblocks in one dimension to resolve the fronts adequately, rendering the predictions from 3D simulations dubious at best. These erroneous predictions are not caused by phase dispersion (the improper prediction of water velocity)--as in black-oil simulation, in which the effect is less significant--but occur because of the coupling of compositional dispersion with fractional flow. Small errors in composition alter the fractional flow, causing the development of incorrect wave speeds. The same effect is also seen in compositional simulation of gas injection.
We propose a simple method for streamline-based simulations that substantially reduces numerical dispersion. The method is rooted in the assumption of segregated flow within a gridblock. After comparing numerical and analytical results in one dimension, we implement the method into a 3Dstreamline-based simulator of polymer flooding that also incorporates a physically based model of the fluid rheology. We demonstrate that traditional simulation methods can vastly overestimate recovery, potentially leading to poor injection design and management decisions. We demonstrate the utility of our approach by suggesting optimal strategies for the design of polymer injection on the basis of our improved simulation technique.
|File Size||1 MB||Number of Pages||10|
AlSofi, A. M. and Blunt, M. J., 2009. Streamline-Based Simulation ofNon-Newtonian Polymer Flooding. Paper SPE 123971 presented at the 2009 SPEAnnual Technical Conference and Exhibition, New Orleans, Louisiana, 4-7October. http://dx.doi.org/10.2118/123971-MS.
Aziz, K. and Settari, A., 1979. Petroleum Reservoir Simulation.London: Applied Science Publishers.
Batycky, R. P., Blunt, M. J. and Thiele, M. R., 1997. A 3D Field-ScaleStreamline-Based Reservoir Simulator. SPE Res Eng 12 (4):246-254. http://dx.doi.org/10.2118/36726-PA.
Beraldo, V. T., Blunt, M. J., Schiozer, D. J., et al. 2007. StreamlineSimulation With an API Tracking Option. Paper SPE 107496 presented at theEUROPEC/EAGE Conference and Exhibition, London, United Kingdom, 11-14 June. http://dx.doi.org/10.2118/107496-MS.
Christie, M. A. and Blunt, M. J. 2001. Tenth SPE Comparative SolutionProject: A Comparison of Upscaling Techniques. SPE Res Eval & Eng 4 (4): 308-317. http://dx.doi.org/10.2118/72469-PA.
Christopher, C. A., Clark, T. J. and Gibson, D. H. 1988. Performance andOperation of a Successful Polymer Flood in the Sleepy Hollow Reagan Unit. PaperSPE 17395 presented at the SPE Enhanced Oil Recovery Symposium, Tulsa,Oklahoma, 16-21 April. http://dx.doi.org/10.2118/17395-MS.
Edwards, M. G. 1996. A Higher-Order Godunov Scheme Coupled with DynamicLocal Grid Refinement for Flow in a Porous Medium. Comput. Method. Appl.M. 131 (3-4): 287-308. http://dx.doi.org/10.1016/0045-7825(95)00935-3.
Haugse, V., Karlsen, K. H., Lie, K.-A., et al. 2001. Numerical Solution ofthe Polymer System by Front Tracking. Transport Porous Med. 44 (1): 63-83. http://dx.doi.org/10.1023/A:1010740024800.
Helfferich, F. G. 1981. Theory of Multicomponent, Multiphase Displacement inPorous Media. SPE J. 21 (1): 51-62. http://dx.doi.org/10.2118/8372-PA.
Jerauld, G. R., Lin, C. Y., Webb, K. J., et al. 2008. Modeling Low-SalinityWaterflooding. SPE Res Eval & Eng 11 (6): 1000-1012. http://dx.doi.org/10.2118/102239-PA.
Jessen, K., Wang, Y., Ermakov, P., et al. 2001. Fast, Approximate Solutionsfor 1D Multicomponent Gas Injection Problems. SPE J. 6 (4):442-451. http://dx.doi.org/10.2118/56608-MS.
Lake, L. W. 1989. Enhanced Oil Recovery. Englewood Cliffs, NJ:Prentice Hall.
Liu, J., Pope, G. A. and Sepehrnoori, K. 1995. A High-Resolution, FullyImplicit Method for Enhanced Oil Recovery Simulation. Paper SPE 29098 presentedat SPE Reservoir Simulation Symposium, San Antonio, Texas, 12-15 February. http://dx.doi.org/10.2118/29098-MS.
Patton, J. T., Coats, K. H. and Colegrove, G. T. 1971. Prediction of PolymerFlood Performance. SPE J. 11 (1): 72-84. http://dx.doi.org/10.2118/2546-PA.
Pope, G. A. 1980. The Application of Fractional Flow Theory to Enhanced OilRecovery. SPE J. 20 (3): 191-205. http://dx.doi.org/10.2118/7660-PA.
Risebro, N. H. and Tveito, A. 1991. Front Tracking Applied to a NonstrictlyHyperbolic System of Conservation Laws. SIAM J. Sci. Stat. Comp. 12 (6): 1401-1419. http://dx.doi.org/10.1137/0912076.
Saad, N., Pope, G. A. and Sepehrnoori, K. 1990. Application of Higher-OrderMethods in Compositional Simulation. SPE Res Eval & Eng 5(4): 623-630. http://dx.doi.org/10.2118/18585-PA.
Schlumberger (Editor). 2007. Eclipse Technical Description, 1482 pp.
Solano, R., Johns, R. T. and Lake, L. W. 2001. Impact of Reservoir Mixing onRecovery in Enriched-Gas Drives Above the Minimum Miscibility Enrichment.SPE Res Eval & Eng 4 (5): 358-365. http://dx.doi.org/10.2118/73829-PA.
Sorbie, K. S. 1991. Polymer-Improved Oil Recovery. Glasgow, Scotland:Blackie.
Thiele, M. R., Batycky, R. P., Pollitzer, S., et al. 2008. Polymer FloodModeling Using Streamlines - Part 1. Paper SPE 115545 presented at SPE AnnualTechnical Conference and Exhibition, Denver, Colorado, 21-24 September. http://dx.doi.org/10.2118/115545-MS.
Thiele, M. R., Batycky, R. P., Pollitzer, S. and Clemens, T., 2010.Polymer-Flood Modeling Using Streamlines. SPE Res Eval & Eng13 (2): 313-322. http://dx.doi.org/10.2118/115545-PA.
Todd, M. R. and Longstaff, W. J. 1972. The Development, Testing, andApplication of a Numerical Simulator for Predicting Miscible Flood Performance.J. Pet Tech 24 (7): 874-882. http://dx.doi.org/10.2118/3484-PA.
Wang, D., Seright, R. S., Shao, Z., et al. 2008. Key Aspects of ProjectDesign for Polymer Flooding at the Daqing Oilfield. SPE Res Eval & Eng11 (6): 1117-1124. http://dx.doi.org/10.2118/109682-PA.
Willhite, G. P. 1986. Waterflooding. SPE Textbook Series, Vol. 3.Richardson, Texas: Textbook Series, SPE.
Wyatt, K., Pitts, M. and Surkalo, S. 2008. Economics of Field ProvenChemical Flooding Technologies. Paper SPE 113126 presented at SPE/DOE Symposiumon Improved Oil Recovery, Tulsa, Oklahoma, 20-23 April. http://dx.doi.org/10.2118/113126-MS.
Xiaoqin, Z., Wenting, G., Nan, M., et al. 2008. Simulation on TechnicalLimits of Multi-Molecule-Weight Polymer Flooding in Heterogeneous Multi-LayerReservoirs in Daqing Oilfield. Paper SPE 12014 presented at InternationalPetroleum Technology Conference, Kuala Lumpur, Malaysia, 3-5 December. http://dx.doi.org/10.2523/12014-MS.