Multimodal ensemble Kalman filtering using Gaussian mixture models |
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| Authors: | Laura Dovera Ernesto Della Rossa |
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| Institution: | (1) Cold and Arid Regions Environmental and Engineering Research Institute, CAS, 730000 Lanzhou, China;(2) Department of Geological Sciences, Florida State University, Tallahassee, FL 32306, USA;(3) Department of Scientific Computing, Florida State University, Tallahassee, FL 32306, USA; |
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| Abstract: | In this paper we present an extension of the ensemble Kalman filter (EnKF) specifically designed for multimodal systems. EnKF
data assimilation scheme is less accurate when it is used to approximate systems with multimodal distribution such as reservoir
facies models. The algorithm is based on the assumption that both prior and posterior distribution can be approximated by
Gaussian mixture and it is validated by the introduction of the concept of finite ensemble representation. The effectiveness
of the approach is shown with two applications. The first example is based on Lorenz model. In the second example, the proposed
methodology combined with a localization technique is used to update a 2D reservoir facies models. Both applications give
evidence of an improved performance of the proposed method respect to the EnKF. |
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