Bridging multipoint statistics and truncated Gaussian fields for improved estimation of channelized reservoirs with ensemble methods

In this paper, we present a new parameterization of channelized reservoirs with two facies types, which is coupled with the ensemble Kalman filter (EnKF) and the iterative adaptive Gaussian mixture filter (IAGM) for history matching (HM) of production data. The main objectives are to match the past data within the model and measurement uncertainties and to preserve the geological realism in order to predict the future behavior of the reservoir. The parameterization bridges the method of Gaussian truncation with multipoint statistics