DocumentCode :
548122
Title :
Singular value decomposition assisted Ensemble Kalman Filter for history matching problem
Author :
Jesmani, M. ; Shabaninia, Faridoon ; Karimaghaee, Paknoosh ; Ebadat, Afrooz
Author_Institution :
Sch. of Electr. & Comput. Eng., Shiraz Univ., Shiraz, Iran
fYear :
2011
fDate :
17-19 May 2011
Firstpage :
1
Lastpage :
1
Abstract :
The application of a recursive technique, the En-semble Kalman filter, to history matching problem has been considered. An algorithm is simplified in a way of reducing the order of the state vector by using Singular Value Decomposition (SVD). The state vector of the reservoir model is truncated to a few numbers of states corresponding to the largest singular values. The energy of the system is preserved by eliminating the state variables corresponding to the zero singular values or close to zero ones. In this way, the computational time is greatly reduced. Computational effort required for history matching of large reservoirs is a major problem. The algorithm of the proposed method is described by a synthetic model. Finally, it was evident from the simulation results that the application of the Ensemble Kalman filter combined with SVD significantly decreases the computational time of the estimation of unknown geological properties in large reservoirs. Furthermore, the example shows that the estimation results has improved in comparison with the results obtained with a much more expensive approach that estimates states in every grid blocks.
Keywords :
Kalman filters; recursive estimation; singular value decomposition; Kalman filter; history matching problem; recursive technique; singular value decomposition; state variables; Ensemble Kalman filter; History matching; Singular value decomposition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Engineering (ICEE), 2011 19th Iranian Conference on
Conference_Location :
Tehran
Print_ISBN :
978-1-4577-0730-8
Type :
conf
Filename :
5956013
Link To Document :
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