Advanced Workflows for Integration of Multiscale Data and Realistic Geological Modeling

Abstract

Numerical geological modeling classically uses different geostatistical techniques, which face two conflicting objectives: to make the model more geological from a descriptive point of view and to make it consistent with all available data. As it is well known, the more realistic the model, the more difficult the integration of data. Exploratory efforts are ongoing at IFPEN about the development of geostatistical methods to simulate models respecting constraints originating from seismic or from genetic modeling to obtain more realistic geological distributions of heterogeneities and provide more realistic images of the subsurface geological complexity. This paper focuses on three specific methods and workflows developed to generate geological models with an improved geological flavor and that respect the well and geological and seismic data characterizing the studied area. A first powerful approach is based upon the non-stationary plurigaussian simulation method. The non-stationary context through the computation of the 3D probability distributions of facies proportions offers numerous possibilities to use conceptual geological data and seismic derived information and to obtain at the end realistic geological models. A second method investigates the potential of the Bayesian sequential simulation. Recent developments have been proposed to extend this method to media including distinct facies. We suggest an improved variant to better account for the resolution differences between sonic logs and seismic data. This yields a more robust framework to integrate seismic data. A third innovative approach reconciles geostatistical multipoint simulation with texture synthesis principles. Geostatistical multipoint methods provide models, which better reproduce complex geological features. However, they still call for significant computation times. On the other hand, texture synthesis has been developed for computer graphics: it can help reduce computation time, but it does not account for data. We then envision a hybrid multiscale algorithm with improved computation performances and yet able to respect data and promising in terms of geological realism

AAPG Datapages/Search and Discovery Article #90216 ©2015 AAPG Annual Convention and Exhibition, Denver, CO., May 31 - June 3, 2015