Ensemble Kalman filter regularization using leave-one-out data cross-validation
Permanent link to this recordhttp://hdl.handle.net/10754/552767
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AbstractIn this work, the classical leave-one-out cross-validation method for selecting a regularization parameter for the Tikhonov problem is implemented within the EnKF framework. Following the original concept, the regularization parameter is selected such that it minimizes the predictive error. Some ideas about the implementation, suitability and conceptual interest of the method are discussed. Finally, what will be called the data cross-validation regularized EnKF (dCVr-EnKF) is implemented in a 2D 2-phase synthetic oil reservoir experiment and the results analyzed.
CitationEnsemble Kalman filter regularization using leave-one-out data cross-validation, AIP Conference Proceedings 1479 , 1247 (2012); doi: 10.1063/1.4756379
Conference/Event nameInternational Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2012