Effect of image segmentation & voxel size on micro-CT computed effective transport & elastic properties

Abstract

Digital rock technology is rapidly evolving interdisciplinary field with many promises, including fast turnaround times for core analysis, repeatable analysis, and multiphysics simulation. We study the impact of the image segmentation threshold and image voxel size on image-computed permeability, elastic moduli, and electrical conductivity. Improved quantitative understanding of such effects is critically important when comparing laboratory-measured rock properties with those computed on digital images of rocks. We analyze properties of over 500 binary microstructures (each of size 10243 voxels) segmented using different segmentation algorithms. We find that uncertainty in computed rock properties, induced due to the choice of segmentation threshold, increases with coarsening of image voxels. Segmentation of the same rock, acquired with different voxels sizes, lead to small variations in porosity but induces relatively large variation in flow and electrical rock properties. This uncertainty is larger for rocks of lower porosity. We find that coarsening of image voxels also leads to rounding and smoothing of pore throats and a sharp decline in specific surface area which results in an increase in computed permeability. We propose simple models to remove the bias in rock properties when image-derived porosity is either overestimated or underestimated due to the choice of the segmentation threshold. This approach is particularly useful when comparing laboratory-measured rock properties to those derived from digital rocks since often the image calculated porosity and the laboratory-measured porosity are not the same. Even after such corrections, the impact of finite image voxel size would still need to be compensated.