Ensemble Kalman Filter for Nonliner Likelihoods

This paper defines the update equation (sometimes called the analysis step) in the Ensemble Kalman filter in a conceptually different way. For linear likelihood models the new approach coincides with the traditional version. When the likelihood is nonlinear the new approach is still applicable. Another feature of the new approach is that it opens for Monte Carlo sampling of the likelihood. This can be used to improve predictions. A synthetic reservoir example with a nonlinear, black-box, seismic likelihood function shows that the approach can be applied to reservoir models.