Merge pore clusters: A novel method to construct pore networks and predict permeability from 2D rock images

Abstract

We propose a novel method to predict fluid flow properties of reservoir rocks from 2D rock images by connecting pore clusters based on their intrinsic properties. Spatial proximity and connecting large clusters with priority are the two basic connecting principles of this method. A few methods from complex networks were used to analyze the topology and connectivity of the connected pore networks, resulting in more realistic and optimal pore networks from 2D images. A new topological descriptor is proposed and was found to perform well in quantifying the network topology by considering both the isolated pore cluster number and the Euler characteristic. The new method can predict permeability from the 2D rock images with a reasonable agreement compared to the reference cases for different rock types and complex pore structures.