Permeability Prediction from Geological Models

Abstract

We present a new approach to permeability modelling and prediction in sandstones. By simulating a range of geological processes which operate to form a sandstone, we obtain physically representative model porous media. The geometry of the models is completely specified, so that permeability can be calculated directly using a flow path network approach. In contrast to previous efforts to predict permeability, our approach is based on first principles. There are no adjustable parameters in the calculations, and no requirement for additional measurements or correlations (e.g. capillary pressure data or pore system data from thin sections). Model predictions match measurements on Fontainebleau sandstone samples whose permeabilities span nearly five orders of magnitude. We have also been able to correctly predict pore throat size distributions to match mercury injection measurements. Pore-scale geometrical features of the model are found to be spatially correlated, and this departure from randomness significantly affects macroscopic properties. The agreement between predictions and measurements suggests that spatial correlation is inherent in granular porous media, and that uncorrelated (or arbitrarily correlated) models of transport in such media are unlikely to be physically representative.