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Multiple assisted history matching (AHM) techniques commonly applied in the oil and gas industry were benchmarked for their applicability to field studies. The benchmarking effort was aimed at exploration of the theoretical as well as practical benefits, challenges and tradeoffs of the AHM techniques as they are utilized for asset development and reservoir management.

This paper specifically discusses benchmarking of ensemble-based methods as applied for history matching of a key deepwater asset for the corporation. Two variations of ensemble-based methods are examined: the ensemble Kalman filter (EnKF) and the ensemble smoother with multiple data assimilation (ES-MDA) . In both techniques, the ensemble of parameter estimates evolves as field data are assimilated into the reservoir characterization, either sequentially using the EnKF or iteratively using the ES-MDA. Both of these variations …