Data Assimilation by Ensemble Kalman Filter with Reparameterization for Nonlinear Problems

Yan Chen, Dean S. Oliver, Dongxiao Zhang & Yan Chen
Owing to its simplicity and efficiency the Ensemble Kalman filter (EnKF) has recently been applied for assimilating static and dynamic measurements to continuously update the estimate of the state vector, such as reservoir properties and responses. Many EnKF implementations showed promising results. However, the Gaussian assumption is an implicit requirement for obtaining a satisfactory estimate through EnKF or its variants. EnKF may not work properly when the state vector is strongly nonlinear and thus non-Gaussian....
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