The Role of Geomechanical Observation in Continuous Updating of Thermal-Recovery Simulations With the Ensemble Kalman Filter
- Ali Azad (Shell Canada) | Richard Chalaturnyk (University of Alberta)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- May 2013
- Document Type
- Journal Paper
- 1,043 - 1,056
- 2013. Society of Petroleum Engineers
- 5.3.9 Steam Assisted Gravity Drainage, 5.8.5 Oil Sand, Oil Shale, Bitumen, 5.3.4 Integration of geomechanics in models, 5.5 Reservoir Simulation
- 0 in the last 30 days
- 244 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 12.00|
|SPE Non-Member Price:||USD 35.00|
In-situ thermal methods such as steam-assisted gravity drainage (SAGD) and cyclic steam stimulation (CSS) are widely used in oil-sand reservoirs. The physics of such thermal processes is generally well-understood, and it has been shown that rock properties are highly influenced by the geomechanical behavior of the reservoir during these recovery processes. Geomechanics improves the process dynamically, and its response can depict the progress of production within a reservoir. However, the potential of geomechanical monitoring is not usually practiced. With increased implementation of highly instrumented wells and communication technologies providing real-time monitoring data from different sources, combining available data into reservoir geomechanical simulations can improve updating numerical models and the prediction process.This research explores effective uses of geomechanical observation data for history matching and types of geomechanical observation sources adequate for thermal recovery. The ensemble Kalman filter (EnKF), combined with an iterative geomechanical coupled simulator, has been chosen as the data-assimilation algorithm to update the model continuously on the basis of geomechanical observations and production data. The results show that considering geomechanical modeling and observation improves history matching when geomechanical behavior plays a role in the process.
|File Size||2 MB||Number of Pages||14|
Agar, J.G., Morgenstern, N.R., and Scott, J.D. 1987. Shear Strength andStress-Strain Behaviour of Athabasca Oil Sand at Elevated Temperatures andPressures. Can. Geotech. J. 24 (1): 1-10. http://dx.doi.org/10.1139/t87-001.
Anderson, J.L. 2007. Exploring the Need for Localization in Ensemble DataAssimilation Using a Hierarchical Ensemble Filter. Physica D: NonlinearPhenomena 230: 99-111. http://dx.doi.org/10.1016/j.physd.2006.02.011.
Azad, A. and Chalaturnyk, R.J. 2011. Numerical Study of SAGD:Geomechanical-Flow Coupling for Athabasca Oil Sands Reservoirs, Proceedingsof the ARMA 45th US Rock Mechanics/Geomechanics Symposium, 1-14.
Chalaturnyk, R.J. 1996. Geomechanics of the Steam-Assisted Gravity DrainageProcess in Heavy Oil Reservoirs. PhD dissertation, University of Alberta,Edmonton, Canada.
Chalaturnyk, R.J. and Li, P. 2004. When Is It Important To ConsiderGeomechanics in SAGD Operations? J. Cdn. Pet. Tech. 43 (4):53-61.
Chalaturnyk, R.J. and Scott, J.D. 1995. Geomechanics Issues ofSteam-Assisted Gravity Drainage, Paper SPE 30280 presented at the SPEInternational Heavy Oil Symposium, Calgary, Alberta, Canada, 19-21 June. http://dx.doi.org/10.2118/30280-MS.
Chang, H., Chen, Y., and Zhang, D. 2010. Data Assimilation of Coupled FluidFlow and Geomechanics Using the Ensemble Kalman Filter. SPE J. 15 (2): 382-394. http://dx.doi.org/10.2118/118963-PA.
Chen, Y. 2008. Ensemble-Based Closed-Loop Production Optimization. PhDdissertation, University of Oklahoma, Norman, Oklahoma.
Chitralekha, S.B., Trivedi, J.J., and Shah, S.L. 2010. Application of theEnsemble Kalman Filter for Characterization and History Matching ofUnconventional Oil Reservoirs. Paper SPE 137480 presented at the CanadianUnconventional Resources and International Petroleum Conference, Calgary,Alberta, Canada, 19-21 October. http://dx.doi.org/10.2118/137480-MS.
Collins, P.M. 2007. Geomechanical Effects on the SAGD Process. SPE ResEval & Eng 10 (4): 367-375. http://dx.doi.org/10.2118/97905-PA.
Deutsch, C.V. and Journel, A.G. 1997. GSLIB: Geostatistical SoftwareLibrary and User's Guide. Oxford University Press.
Du, J. and Wong, R.C.K. 2007. Coupled Geomechanics-Reservoir Simulation ofUTF Phase A Project Using a Full Permeability Tensor. Proceedings of thePetroleum Society's 8th Canadian International Petroleum Conference,1-16.
Dusseault, M. and Morgenstern, N.R. 1978. Shear Strength of Atabasca OilSand. Can. Geotech. J. 15: 216-238.
Edmunds, N.R., Kovalsky, J.A., Gittins, S.D. et al. 1994. Review of Phase ASteam-Assisted Gravity-Drainage Test. SPE Res Eval & Eng 9(2): 119-124. http://dx.doi.org/10.2118/21529-PA.
Evensen, G. 2009. The Ensemble Kalman Filter for Combined State andParameter. IEEE Control Systems Magazine 29 (3):82-104.
Gu, Y. 2006. History Matching Production Data Using the Ensemble KalmanFilter. PhD dissertation, University of Oklahoma, Norman, Oklahoma.
Gu, Y. and Oliver, S.O. 2006. The Ensemble Kalman Filter for ContinuousUpdating of Reservoir Simulation Models. J. Energy Resources Technol. 128: 79-87.
Gul, A., Nejadi, S., Shah, S.L. et al. 2011. Make Use of DynamicData--A Constraint Based Enkf for SAGD Reservoir Characterization andProduction Management. Proceedings of the 2011 World Heavy Oil Congress,1-14.
Kim, J., Tchelepi, H.A., and Juanes, R. 2011. Stability, Accuracy, andEfficiency of Sequential Methods for Coupled Flow and Geomechanics. SPEJ. 16 (2): 249-262. http://dx.doi.org/10.2118/119084-PA.
Kosar, K.M., Scott, J.D., and Morgenstern, N.R. 1987. Testing To Determinethe Geotechnical Properties of Oil Sands. Proceedings of the 38th AnnualTechnical Meeting of the Petroleum Society of CIM, Calgary, 995-1010.
Li, P. 2006. Numerical Simulation of the SAGD Process Coupled WithGeomechanical Behaviour. PhD dissertation, University of Alberta, Edmonton,Canada.
Li, P. and Chalaturnyk, R.J. 2009. History Match of the UTF Phase A ProjectWith Coupled Reservoir Geomechanical Simulation. J. Cdn. Pet. Tech. 48 (1): 29-35.
Nævdal, G., Johnsen, L.M., Aanonsen, S.I. et al. 2005. ReservoirMonitoring and Continuous Model Updating Using Ensemble Kalman Filter. SPEJ. 10 (1): 66-74. http://dx.doi.org/10.2118/84372-PA.
Oldakowski, K. 1994. Absolute Permeability of Oil Sands. PhD dissertation,University of Alberta, Edmonton, Canada.
Sætrom, J. and Omre, H. 2010. Ensemble Kalman filtering With ShrinkageRegression Techniques. Computational Geosci. 15 (2):271-292.
Samieh, A.M. and Wong, R.C.K. 1997. Deformation of Athabasca Oil Sand at LowEffective Stresses Under Varying Boundary Conditions. Can. Geotech. J. 34: 985-990.
Scott, J.D., Proskin, S.A., and D.P. Adhikary. 1994. Volume and PermeabilityChanges Associated With Steam Stimulation in an Oil Sands Reservoir. J. Cdn.Pet. Tech. 33 (7): 44-52.
Scott, J.D. and Seto, A.C. 1986. Thermal Property Measurements on Oil Sands.J. Cdn. Pet. Tech. 25 (6): 70-77.
Settari, A., Walters, D.A., and Behie, G.A. 2001. Use of Coupled Reservoirand Geomechanical Modeling for Integrated Reservoir Analysis and Management.J. Cdn. Pet. Tech. 40 (12): 55-61.
Tortike, W.S. 1991. Numerical Simulation of Thermal, Multiphase Fluid Flowin an Elastoplastic Deforming Oil Reservoir. PhD dissertation, University ofAlberta, Edmonton, Canada.
Touhidi-Baghini, A. 1998. Absolute Permeability of McMurray Formation OilSands at Low Confining Stresses. PhD dissertation, University of Alberta,Edmonton, Canada.
Tran, D., Nghiem, L., and Buchanan, L. 2005. Improved Iterative Coupling ofGeomechanics With Reservoir Simulation. Paper SPE 93244 presented at the SPEReservoir Simulation Symposium, The Woodlands, Texas, 31 January-2 February. http://dx.doi.org/10.2118/93244-MS.
Zhang, Y. and Oliver, D.S. 2010. Improving the Ensemble Estimate of theKalman Gain by Bootstrap Sampling. Mathematical Geosci. 42(3): 327-345.