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Reservoir History Matching Using Ensemble Kalman Filters with Anamorphosis Transforms

This work aims to enhance the Ensemble Kalman Filter performance by transforming the non-Gaussian state variables into Gaussian variables to be a step closer to optimality. This is done by using univariate and multivariate Box-Cox transformation.
Some History matching methods such as Kalman filter, particle filter and the ensemble Kalman filter are reviewed and applied to a test case in the reservoir application. The key idea is to apply the transformation before the update step and then transform back after applying the Kalman correction. In general, the results of the multivariate method was promising, despite the fact it over-estimated some variables.

Identiferoai:union.ndltd.org:kaust.edu.sa/oai:repository.kaust.edu.sa:10754/255452
Date12 1900
CreatorsAman, Beshir M.
ContributorsHoteit, Ibrahim, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, Al-Naffouri, Tareq Y., Sun, Shuyu
Source SetsKing Abdullah University of Science and Technology
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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