Rock physics and multiple‐point geostatistics for seismic inversion

Abstract

Summary This paper presents a novel inversion technique that combines rock physics and multiple-point geostatistics (MPG) in a Bayesian framework. The proposed method can be applied in its current implementation to any inverse problem that can be approximated as a series of 1D forward-modeling operators. Rock-physics principles are incorporated at the beginning of the process, defining the links between reservoir properties (e.g., lithology, saturation) and physical properties (e.g., compressibility, electrical conductivity). MPG is used to define and explore the space of solutions. The method can be extended to satisfy multiple physical constraints simultaneously; in other words, the solutions can be conditioned with different types of geophysical data. Results of two synthetic tests and a real data application are presented to demonstrate the validity and applicability of the proposed inversion technique.