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dc.contributor.authorElsheikh, Ahmed H.
dc.contributor.authorWheeler, Mary Fanett
dc.contributor.authorHoteit, Ibrahim
dc.date.accessioned2015-08-03T11:05:24Z
dc.date.available2015-08-03T11:05:24Z
dc.date.issued2013-06
dc.identifier.issn00219991
dc.identifier.doi10.1016/j.jcp.2013.01.047
dc.identifier.urihttp://hdl.handle.net/10754/562779
dc.description.abstractParameter estimation for subsurface flow models is an essential step for maximizing the value of numerical simulations for future prediction and the development of effective control strategies. We propose the iterative stochastic ensemble method (ISEM) as a general method for parameter estimation based on stochastic estimation of gradients using an ensemble of directional derivatives. ISEM eliminates the need for adjoint coding and deals with the numerical simulator as a blackbox. The proposed method employs directional derivatives within a Gauss-Newton iteration. The update equation in ISEM resembles the update step in ensemble Kalman filter, however the inverse of the output covariance matrix in ISEM is regularized using standard truncated singular value decomposition or Tikhonov regularization. We also investigate the performance of a set of shrinkage based covariance estimators within ISEM. The proposed method is successfully applied on several nonlinear parameter estimation problems for subsurface flow models. The efficiency of the proposed algorithm is demonstrated by the small size of utilized ensembles and in terms of error convergence rates. © 2013 Elsevier Inc.
dc.publisherElsevier BV
dc.subjectIterative stochastic ensemble method
dc.subjectParameter estimation
dc.subjectRegularization
dc.subjectSubsurface flow models
dc.titleAn iterative stochastic ensemble method for parameter estimation of subsurface flow models
dc.typeArticle
dc.contributor.departmentEarth Science and Engineering Program
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Division
dc.contributor.departmentEnvironmental Science and Engineering Program
dc.contributor.departmentEarth Fluid Modeling and Prediction Group
dc.identifier.journalJournal of Computational Physics
dc.contributor.institutionCenter for Subsurface Modeling (CSM), Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX, United States
kaust.personHoteit, Ibrahim
kaust.personElsheikh, Ahmed H.


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