Ensemble Kalman Methods in Reservoir History Matching - Why Do they sometimes Fail and how Can you Fix it?

The ensemble Kalman based methods have seen numerous successful application over the past 10 years in fields such as numerical weather predictions, oceanography, and reservoir history matching. However, it is well-known that the standard implementation of the ensemble Kalman update equation can lead unphysical model updates and the problem known as filter divergence (or ensemble collapse). In this paper, we will re-visit recent theoretical results which highlights the issues of the standard ensemble Kalman update equations and identifies how you can potentially fix them. We use the data from the Brugge field to demonstrate the link between the theoretical results and practical applications in reservoir history matching.