Dynamic data integration for structural modeling: model screening approach using a distance-based model parameterization

• DOI: 10.1007/s10596-007-9063-9
• Publication Date: 2008-01-22T02:52:16Z
• Authors: Satomi Suzuki; Guillaume Caumon; Jef Caers
• Keywords: [SDU] Sciences of the Universe [physics]; History matching; Discrete-space optimization; Data assimilation; 01 natural sciences; Distance-based model parameterization; Distance function; Stochastic search; Structural uncertainty; 0105 earth and related environmental sciences

This paper proposes a novel history-matching method where reservoir structure is inverted from dynamic fluid flow response. The proposed workflow consists of searching for models that match production history from a large set of prior structural model realizations. This prior set represents the reservoir structural uncertainty because of interpretation uncertainty on seismic sections. To make such a search effective, we introduce a parameter space defined with a “similarity distance” for accommodating this large set of realizations. The inverse solutions are found using a stochastic search method. Realistic reservoir examples are presented to prove the applicability of the proposed method.