Reservoir engineering has become of prime importance for oil and gas field development projects. With rising complexity, reservoir simulations and history matching have become critical for fine-tuning reservoir production strategies, improved subsurface formation knowledge and forecasting remaining reserves. The sparse spatial sampling of production data has posed a significant challenge for reducing uncertainty of subsurface parameters. Seismic, electromagnetic and gravimetry techniques have found widespread application in enhancing exploration for oil and gas and monitor reservoirs, however these data have been interpreted and analyzed mostly separately rarely utilizing the synergy effects that may be attainable. With the incorporation of multiple data into the reservoir history matching process there has been the request knowing the impact each incorporated observation has on the estimation. We present multi-data ensemble-based history matching framework for the incorporation of multiple data such as seismic, electromagnetics, and gravimetry for improved reservoir history matching and provide an adjoint-free ensemble sensitivity method to compute the impact of each observation on the estimated reservoir parameters. The incorporation of all data sets displays the advantages multiple data may provide for enhancing reservoir understanding and matching, with the impact of each data set on the matching improvement being determined by the ensemble sensitivity method.


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