Polymer-Flood Modeling Using Streamlines
- Marco Thiele (Streamsim Technologies) | Roderick Batycky (StreamSim Technologies) | Stefan Pöllitzer (OMV Exploration) | Torsten Clemens (OMV Exploration)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- April 2010
- Document Type
- Journal Paper
- 313 - 322
- 2010. Society of Petroleum Engineers
- 5.5.8 History Matching, 5.5 Reservoir Simulation, 5.8.7 Carbonate Reservoir, 5.5.3 Scaling Methods, 5.3.1 Flow in Porous Media, 5.5.7 Streamline Simulation, 5.4.1 Waterflooding, 5.4.7 Chemical Flooding Methods (e.g., Polymer, Solvent, Nitrogen, Immiscible CO2, Surfactant, Vapex), 7.1.8 Asset Integrity, 5.3.2 Multiphase Flow, 5.1.1 Exploration, Development, Structural Geology, 1.8 Formation Damage, 5.7.2 Recovery Factors, 6.5.2 Water use, produced water discharge and disposal, 5.4.2 Gas Injection Methods, 4.3.4 Scale, 4.1.5 Processing Equipment, 5.1.5 Geologic Modeling
- polymer flooding, streamline simulation
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The successful design of a polymer flood relies on the ability to properly model the in-situ distribution of polymer concentration while accounting for its effects on fluid properties such as increasing water viscosity as a function of polymer concentration and loss of polymer caused by adsorption. Despite advances in numerical techniques and computer hardware, the numerical modeling of polymer floods using Eulerian-based approaches such as finite difference (FD) remains a challenge: Coarse grids tend to excessively smear concentration fronts, masking the true impact of polymers; yet introducing finer grids inevitably leads to excessive run times, making the use of modern reservoir-engineering workflows unrealistic. This problem was already outlined in 1978 by Lake et al. (1981). We revisit the same problem 30 years later in the context of modern streamline (SL) simulation techniques.
We present the extension of modern SL simulation to field-scale polymer flooding, which represents a step change from the hybrid, 2D steady-state models used in the 1970s. We apply well-established physical models for polymer flooding to capture the displacement efficiency in 1D, and couple it with a 3D SL simulator to capture the interpattern sweep efficiency caused by well rates, reservoir architecture, and reservoir heterogeneity. Because modern 3D SL simulators account for changing well rates, nonuniform initial conditions, and gravity, adding polymer functionality means that real-field polymer floods can be modeled efficiently using SLs so as to be useful in modern reservoir-engineering workflows that center on assessing uncertainty and risk associated with design parameters and geological scenarios.
In this paper, we proceed to outline the basic architecture of a SL simulator with a polymer option. The physics of polymer flooding is the same as that being used in established FD codes. We discuss advantages and disadvantages of the formulation and present in numerical experiments 1D, 2D, and 3D to illustrate our results.
|File Size||1 MB||Number of Pages||10|
3DSL User Manual v3.00 (March 2008). 2008. Calgary: StreamsimTechnologies.
Batycky, R.P, Seto, A.C., and Fenwick, D.H. 2007. Assisted History Matching of a1.4-Million-Cell Simulation Model for Judy Creek 'A' Pool Waterflood/HCMF Usinga Streamline-Based Workflow. Paper SPE 108701 presented at the SPE AnnualTechnical Conference and Exhibition, Anaheim, California, USA, 11-14 November.doi: 10.2118/108701-MS.
Batycky, R.P., Blunt, M.J., and Thiele, M.R. 1997. A 3D Field-Scale Streamline-BasedReservoir Simulator. SPE Res Eng 12 (4): 246-254.SPE-36726-PA. doi: 10.2118/36726-PA.
Batycky, R.P., Thiele, M.R., Baker, R.O., and Chugh, S.H. 2008. Revisiting ReservoirFlood-Surveillance Methods Using Streamlines. SPE Res Eval & Eng 11 (2): 387-394. SPE-95402-PA. doi: 10.2118/95402-PA.
Bratvedt, F., Gimse, T., and Tegnander, C. 1996. Streamline computations for porousmedia flow including gravity. Transport in Porous Media 25 (1): 63-78. doi:10.1007/BF00141262.
Di Donato, G., Huang, W., and Blunt, M. 2003. Streamline-Based Dual PorositySimulation of Fractured Reservoirs. Paper SPE 84036 presented at the SPEAnnual Technical Conference and Exhibition, Denver, 5-8 October. doi:10.2118/84036-MS.
ECLIPSE Technical Reference Manual 2001A. 2001. Houston:Schlumberger/GeoQuest.
Fenwick, D., Thiele, M., Agil, M., Hussain, A., Humam, F., and Caers, J.2005. Reconciling Prior GeologicInformation With Production Data Using Streamlines: Application to a GiantMiddle-Eastern Oil Field. Paper SPE 95940 presented at the SPE AnnualTechnical Conference and Exhibition, Dallas, 9-12 October. doi:10.2118/95940-MS.
Gerritsen, M.G., Mallison, B.T., and Jessen, K.J. In press. A CompositionalFramework for Gas Injection Processes. Computational Geosciences (submitted 2007).
Grinestaff, G.H. 1999. Waterflood Pattern Allocations:Quantifying the Injector to Producer Relationship with StreamlineSimulation. Paper SPE 54616 presented at the SPE Western Regional Meeting,Anchorage, 26-27 May. doi: 10.2118/54616-MS.
Ibrahim, M.N., Clark, R.A., and Al-Matar, B.S. 2007. Streamline Simulation for ReservoirManagement of a Super Giant: Sabiriyah Field North Kuwait Case Study. PaperSPE 105069 presented at the SPE Middle East Oil and Gas Show and Conference,Kingdom of Bahrain, 11-14 March. doi: 10.2118/105069-MS.
Lake, L.W. 1989. Enhanced Oil Recovery. Englewood Cliffs, New Jersey,USA: Prentice Hall.
Lake, L.W., Johnston, J.R., and Stegemeier, G.L. 1981. Simulation and Performance Predictionof a Large-Scale Surfactant/Polymer Project. SPE J. 21(6): 731-739. SPE-7471-PA. doi: 10.2118/7471-PA.
Milliken, W.J., Emanuel, A.S., and Chakravarty, A. 2001. Applications of 3D StreamlineSimulation to Assist History Matching. SPE Res Eval & Eng 4 (6): 502-508. SPE-74712-PA. doi: 10.2118/74712-PA.
Nair, C.V.G. and Al-Maraghi, E. 2006. A Practical Approach in BuildingUpscaled Simulation Model for a Large Middle East Carbonate Reservoir HavingLong Production History. Paper SPE 100270 presented at the SPE Europec/EAGEAnnual Conference and Exhibition, Vienna, Austria, 12-15 June. doi:10.2118/100270-MS.
Peters, E., Arts, R.J., Brouwer, G.K., and Geel, C.R. 2009. Results of the Brugge BenchmarkStudy for Flooding Optimisation and History Matching. Paper SPE 119094presented at the SPE Reservoir Simulation Symposium, The Woodlands, Texas, USA,2-4 February. doi: 10.2118/119094-MS.
Pollock, D.W. 1988. SemianalyticalComputation of Path Lines for Finite-Difference Models. Ground Water 26 (6): 743-750. doi:10.1111/j.1745-6584.1988.tb00425.x.
Samier, P., Quettier, L., and Thiele, M. 2002. Applications of StreamlineSimulations to Reservoir Studies. SPE Res Eval & Eng 5 (4): 324-332. SPE-78883-PA. doi: 10.2118/78883-PA.
Thiele, M.R. and Batycky, R.P. 2006. Using Streamline-Derived InjectionEfficiencies for Improved Waterflood Management. SPE Res Eval &Eng 9 (2): 187-196. SPE-84080-PA. doi: 10.2118/84080-PA.
Zhu, Z., Gerritsen, M.G., and Thiele, M.R. 2009. Thermal Streamline Simulation ForHot Water Flooding. Paper SPE 119200 presented at the SPE ReservoirSimulation Symposium, The Woodlands, Texas, USA, 2-4 February. doi:10.2118/119200-MS.
Lake, L.W. 2007. Petroleum Engineering Handbook: Reservoir Engineeringand Petrophysics. Vol. V(B). Society of Petroleum Engineers.