The Application of Fuzzy Logic and Genetic Algorithms to Reservoir Characterization and Modeling

Abstract

A 3D model of oil and gas fields is important for reserves estimation, for cost effective well placing and for input into reservoir simulators. Reservoir characterization of permeability, litho-facies and other properties of the rocks is essential. A good model depends on calibration at the well locations, with cored wells providing the best data. A subset of wells may contain specialized information such as shear velocity data, whereas other wells may contain only basic logs. We have developed techniques able to populate the entire field database with a complete set of log and core data using fuzzy Logic, genetic algorithms and hybrid models. Once the gaps in the well database have been filled, well logs can be imported to a 3D modeling software package, blocked and upscaled to match the geocellular model cell size.