Joint Updating of Petrophysical Properties and Discrete Facies Variables From Assimilating Production Data Using the EnKF

Abstract

Summary The ensemble Kalman filter (EnKF), is a sequential data-assimilation technique that has been shown to work quite well in obtaining conditional facies models from assimilating production data. Because the problem of history matching geological facies is quite complex, most efforts at solving this problem typically assume that facies properties are constant and spatially homogeneous. In this paper, we propose a method for updating both the categorical facies variables and the spatially heterogeneous and nonuniform properties of the facies in a consistent manner within the EnKF framework. Tests of our proposed approach on two representative examples with different features of nonstationarity resulted in satisfactory history-match solutions and geologically consistent estimates of the nonuniform and heterogeneous petrophysical properties.