Reservoir History Matching Using Ensemble Kalman Filters with Anamorphosis Transforms
Type
ThesisAuthors
Aman, Beshir M.Advisors
Hoteit, Ibrahim
Committee members
Al-Naffouri, Tareq Y.
Sun, Shuyu

Date
2012-12Permanent link to this record
http://hdl.handle.net/10754/255452
Metadata
Show full item recordAbstract
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.Citation
Aman, B. M. (2012). Reservoir History Matching Using Ensemble Kalman Filters with Anamorphosis Transforms. KAUST Research Repository. https://doi.org/10.25781/KAUST-853VJae974a485f413a2113503eed53cd6c53
10.25781/KAUST-853VJ