Updating MPS Facies Realizations Using the Ensemble Smoother with Multiple Data Assimilation

This paper is presenting the results of a study focused on the update of facies models generated by multipoint statistics (MPS) within an ensemble history matching workflow. The tested parameterization consists in updating the uniform random numbers used by MPS to generate the facies realizations with an ensemble method as proposed in the work of Hu et al. (2012). The novelty of this study lies in use of the ensemble smoother with multiple data assimilation (ES-MDA) to update the random number realizations. Tests on synthetics cases show that increasing the iteration number within ES-MDA can significantly improve the quality of the history-match achieved by this approach. The workflow is briefly detailed in the first part of the paper. Then, we present and discuss the history-matching results for two synthetic cases: an inverted five-spot 2D model with channels and a more complex 3D model with dunes.