Adaptive Pilot-point Strategy for History Matching of 3D Seismic Data

Matching seismic data in assisted history matching can be a challenging task. Local parameterization techniques such as pilot-point or gradual deformation methods can be introduced. While information related to seismic data is sometimes considered to initialize such local methods, it is no longer used for further steps and this results in non-adaptive procedures. We propose to use the residual maps related to the 3D seismic data to drive the generation of pilot point locations in an adaptive way. Residual maps are considered as probability density functions of the pilot point locations. Once generated, these locations are changed according to a gradual deformation method which is applied to the random numbers associated to the locations. Last, the optimal locations and values provide a reservoir model which is used to build a new residual map and the procedure is repeated until convergence. A straightforward application of this technique leads to successive optimizations of a discontinuous objective function since locations jump from a high probability region to another. Consequently, we develop an innovative pre-treatment of residual maps based on Gaussian mixtures. The combination of these steps leads to a highly flexible perturbation technique for 3D seismic matching.