Prediction of Pore Geometry Based on Air Permeability Measurements Using a Genetic Algorithm

Pore size distributions can be used to determine fluid retention and permeability relationships of porous media. However, the available test methods are time-consuming and expensive. This study consists of experimental and numerical work. In the experimental part we determine air permeability of a sandstone rock core as a function of water content. In the numerical part we present an extension of the capillary model, which was modified include capillaries composed of sections with different diameters. An optimization scheme that uses a genetic algorithm to predict the best possible pore size distribution from the air permeability measurements was developed.