A Geostatistical Approach for Grid-Independent Geomodeling in Complex Tectonic Environments

Abstract

It is of major importance in geological modeling to account for the geometry of the volume to be modeled. Several methods are available for introducing tectonic deformations or paleo-topographic surface shapes in the geological modeling process. This chapter proposes a synthetic overview of these methods based on geometric deformations or specific geostatistical models. The first approach consists of distorting the modeling grid with a more or less sophisticated unflattening algorithm. Other approaches consist of using a geostatistical algorithm that can take into account geometric deformations when populating the grid with properties. Two algorithms of this type are detailed: local geostatistics (LGS) and multiple-point statistics (MPS). With such algorithms, which can work with any type of grid, the flattening step can be skipped. Special attention is paid to the possibility of modeling the average value of a property, instead of a point value, with the three approaches. It is shown that, in such a case, it is better to perform the modeling in regular grids. The different methods are not exclusive to each other and can be combined, offering a wide range of modeling possibilities, assuming that the inference of technical parameters has been made properly.