History Matching of a Stochastic Multifractal Subesismic Fault Model

Many geostatistical methods have been developed to generate realistic models of subseismic fault networks. The problem is that these models are difficult to history match. In this work, we present an original methodology in which history matching is performed through a modification of fault positions. We first propose a multifractal methodology to generate the faults. The method has been specifically developed to allow history matching. The model parameters are derived from the analysis of the seismic faults. A stochastic algorithm is used to generate 3D subseismic fault realizations that are constrained to the seismic faults. The fracture network is then discretized on a dual porosity simulation grid. Equivalent flow parameters are computed using an analytical method. Last, full field simulations are performed using a multiphase flow simulator. Then, we introduce a method to gradually change the locations of faults while preserving multifractal properties. Changes in locations are driven from a reduced number of parameters. These parameters are gradually modified to optimize the geometry of the realization and compel the initial fault model to reproduce the hydrodynamic behaviour observed on the field. The potential of the methodology is demonstrated on a 3D case study.