Ensemble smoother with multiple data assimilation

Computers and Geosciences

Volumn 55, Issue , 2013, Pages 3-15

  Emerick, Alexandre A ^a   Reynolds, Albert C ^a  

^a UNIVERSITY OF TULSA   (United States)

Author keywords

Ensemble Kalman filter; Ensemble smoother; History matching; Multiple data assimilation

Indexed keywords

COMPUTATIONAL COSTS; ENSEMBLE KALMAN FILTER; ENSEMBLE SMOOTHER; ENSEMBLE-BASED METHOD; ERROR COVARIANCE MATRIX; HISTORY MATCHING; MULTIPLE DATA; RESERVOIR HISTORY MATCHING;

COVARIANCE MATRIX; GEOPHYSICS; ITERATIVE METHODS; KALMAN FILTERS; PETROLEUM RESERVOIRS;

DATA PROCESSING;

COMPARATIVE STUDY; COMPUTER SIMULATION; COVARIANCE ANALYSIS; DATA ASSIMILATION; ENSEMBLE FORECASTING; ERROR ANALYSIS; HYDROCARBON RESERVOIR; KALMAN FILTER; SMOOTHING;

EID: 84875881109     PISSN: 00983004     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cageo.2012.03.011     Document Type: Article

References (41)

1. Aanonsen S.I., Nævdal G., Oliver D.S., Reynolds A.C., Vallés B. Review of ensemble Kalman filter in petroleum engineering. SPE Journal 2009, 14(3):393-412.
2. Bertino L., Evensen G., Wackernagel H. Sequential data assimilation techniques in oceanography. International Statistical Review 2003, 71(2):223-241.
3. Bianco, A., Cominelli, A., Dovera, L., Nævdal, G., Vallès, B., 2007. History matching and production forecast uncertainty by means of the ensemble Kalman filter: a real field application. In: Proceedings of the EAGE/EUROPEC Conference and Exhibition, London, U.K., 11-14 June. No. SPE 107161.
4. Chen C., Li G., Reynolds A.C. Closed-loop reservoir management on the Brugge test case. Computational Geosciences 2010, 14(4):691-703.
5. Chen Y., Oliver D. Ensemble-based closed-loop optimization applied to Brugge field. SPE Reservoir Evaluation & Engineering 2010, 13(1):56-71.
6. Chen Y., Oliver D. Ensemble randomized maximum likelihood method as an iterative ensemble smoother. Mathematical Geosciences 2012, 44(1):1-26.
7. Chen Y., Zhang D. Data assimilation for transient flow in geologic formations via ensemble Kalman filter. Advances in Water Resources 2006, 29(8):1107-1122.
8. Emerick A.A., Reynolds A.C. Combining sensitivities and prior information for covariance localization in the ensemble Kalman filter for petroleum reservoir applications. Computational Geosciences 2011, 15(2):251-269.
9. Emerick A.A., Reynolds A.C. History matching a field case using the ensemble Kalman filter with covariance localization. SPE Reservoir Evaluation & Engineering 2011, 14(4):423-432.
10. Emerick A.A., Reynolds A.C. History matching time-lapse seismic data using the ensemble Kalman filter with multiple data assimilations. Computational Geosciences 2012, 16(3):639-659.
11. Evensen G. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. Journal of Geophysical Research 1994, 99(C5):10143-10162.
12. Evensen G. Sampling strategies and square root analysis schemes for the EnKF. Ocean Dynamics 2004, 54(6):539-560.
13. Evensen G. Data Assimilation: The Ensemble Kalman Filter 2007, Springer, Berlin.
14. Evensen, G., Hove, J., Meisingset, H.C., Reiso, E., Seim, K.S., Espelid, O., 2007. Using the EnKF for assisted history matching of a North Sea reservoir model. In: Proceedings of the SPE Reservoir Simulation Symposium, Houston, TX, 26-28 February. No. SPE 106184.
15. Evensen G., van Leeuwen P.J. An ensemble Kalman smoother for nonlinear dynamics. Monthly Weather Review 2000, 128(6):1852-1867.
16. Gao G., Reynolds A.C. An improved implementation of the LBFGS algorithm for automatic history matching. SPE Journal 2006, 11(1):5-17.
17. Gu Y., Oliver D.S. An iterative ensemble Kalman filter for multiphase fluid flow data assimilation. SPE Journal 2007, 12(4):438-446.
18. Haugen V., Nævdal G., Natvik L.-J., Evensen G., Berg A.M., Flornes K.M. History matching using the ensemble Kalman filter on a North Sea field case. SPE Journal 2008, 13(4):382-391.
19. Houtekamer P.L., Mitchell H.L. Ensemble Kalman filtering. Quarterly Journal of the Royal Meteorological Society 2005, 131:3269-3289.
20. Jansen J., Brouwer D., Naevdal G., van Kruijsdijk C. Closed-loop reservoir management. First Break 2005, 23:43-48.
21. Jansen, J.D., Douma, S.D., Brouwer, D.R., den Hof, P.M.J.V., Heemink, A.W., 2009. Closed-loop reservoir management. In: Proceedings of the SPE Reservoir Simulation Symposium, The Woodlands, TX, 2-4 February. No. SPE 119098.
22. Keppenne C.L., Rienecker M.M. Assimilation of temperature into an isopycnal ocean general circulation model using a parallel ensemble Kalman filter. Journal of Marine Systems 2003, 40-41:363-380.
23. Liu G., Chen Y., Zhang D. Investigation of flow and transport processes at the MADE site using ensemble Kalman filter. Advances in Water Resources 2008, 31(7):975-986.
24. Nævdal, G., Mannseth, T., Vefring, E.H., 2002. Near-well reservoir monitoring through ensemble Kalman filter. In: Proceedings of the SPE/DOE Improved Oil Recovery Symposium, 13-17 April. No. SPE 75235.
25. Oliver D.S., Chen Y. Improved initial sampling for the ensemble Kalman filter. Computational Geosciences 2009, 13(1):13-27.
26. Oliver D.S., Chen Y. Recent progress on reservoir history matching: a review. Computational Geosciences 2010, 15(1):185-221.
27. Peters L., Arts R., Brouwer G., Geel C., Cullick S., Lorentzen R., Chen Y., Dunlop K., Vossepoel F., Xu R., Sarma P., Alhuthali A., Reynolds A. Results of the Brugge benchmark study for flooding optimisation and history matching. SPE Reservoir Evaluation & Engineering 2010, 13(3):391-405.
28. Reichle R.H., McLaughlin D.B., Entekhabi D. Hydrologic data assimilation with the ensemble Kalman filter. Monthly Weather Review 2002, 130(1):103-114.
29. Reynolds A.C., He N., Oliver D.S. Reducing uncertainty in geostatistical description with well testing pressure data. Reservoir Characterization-Recent Advances 1999, 149-162. American Association of Petroleum Geologists. R.A. Schatzinger, J.F. Jordan (Eds.).
30. Reynolds, A.C., Zafari, M., Li, G., 2006. Iterative forms of the ensemble Kalman filter. In: Proceedings of 10th European Conference on the Mathematics of Oil Recovery, Amsterdam, 4-7 September.
31. Rommelse, J., 2009. Data Assimilation in Reservoir Management. Ph.D. Thesis, Technical University of Delft, Delft, The Netherlands.
32. Skjervheim J.-A., Evensen G., Aanonsen S.I., Ruud B.O., Johansen T.A. Incorporating 4D seismic data in reservoir simulation models using ensemble Kalman filter. SPE Journal 2007, 12(3):282-292.
33. Skjervheim, J.-A., Evensen, G., Hove, J., Vabø, J.G., 2011. An ensemble smoother for assisted history matching. In: Proceedings of the SPE Reservoir Simulation Symposium, The Woodlands, TX, USA, 21-23 February. No. SPE 141929.
34. Szunyogh I., Kostelich E.J., Gyarmati G., Patil D.J., Hunt B.R., Kalnay E., Ott E., Yorke J.A. Assessing a local ensemble Kalman filter: perfect model experiments with the national centers for environmental prediction global model. Tellus A 2005, 57:528-545.
35. Tarantola A. Inverse Problem Theory and Methods for Model Parameter Estimation 2005, SIAM, Philadelphia, USA.
36. Thulin, K., Li, G., Aanonsen, S.I., Reynolds, A.C., 2007. Estimation of initial fluid contacts by assimilation of production data with EnKF. In: Proceedings of the SPE Annual Technical Conference and Exhibition, Anaheim, CA, 11-14 November. No. SPE 109975.
37. van Leeuwen P.J., Evensen G. Data assimilation and inverse methods in terms of a probabilistic formulation. Monthly Weather Review 1996, 124:2898-2913.
38. Wang C., Li G., Reynolds A.C. Production optimization in closed-loop reservoir management. SPE Journal 2009, 14(3):506-523.
39. Wang Y., Li G., Reynolds A.C. Estimation of depths of fluid contacts by history matching using iterative ensemble-Kalman smoothers. SPE Journal 2010, 15(2).
40. Wu Z., Reynolds A.C., Oliver D.S. Conditioning geostatistical models to two-phase production data. SPE Journal 1999, 3(2):142-155.
41. Zachariassen, E., Skjervheim, J., Vabø, J., Lunt, I., Hove, J., Evensen, G., 2011. Integrated work flow for model update using geophysical monitoring data. In: Proceedings of the 73rd EAGE Conference & Exhibition, Vienna, Austria, 23-26 May.