History Matching Channelized Reservoirs Using the Ensemble Kalman Filter

Even though the ensemble Kalman filter (EnKF) is widely used, history matching reservoirs with facies description has proven<br>to be a major challenge. A preferred technique for estimating large-scale facies fields within the petroleum industry is still<br>missing. In this paper we present a new approach to this problem. Instead of applying the EnKF directly on facies realizations,<br>the approach applies a transformation of facies fields to a specific level-set function, representing distances between facies types.<br>This ensures better agreement with the EnKF Gaussianity assumptions, and the method always returns facies realizations with<br>geological authenticity. The method also offers large flexibility in generating the initial ensemble, which can be done using any<br>geostatistical tool. Further, no modifications of the standard EnKF equations are needed.