Voxel agglomeration for accelerated estimation of permeability from micro-CT images

Abstract

Direct numerical methods are widely used to solve for flow on micro-computed tomography (micro-CT) images of rocks. Generally, direct numerical methods are computationally demanding, especially on large micro-CT images (10003 voxels and more). We develop a fast, direct numerical approach to solve the elliptic flow equation and estimate the absolute permeability of micro-CT images of rocks. The approach involves voxel agglomeration, which is a common technique in computational fluid dynamics. By allowing specific locations of the pore voxels to be agglomerated, the number of pore voxels or active cells in a sparse matrix can be reduced by approximately 60%–80% depending on the type of rock and its pore size distribution. Nevertheless, the fine details obtained from the micro-CT scan are maintained. The results compared with the Pore-scale Finite Volume Solver (PFVS) are within 1.6% difference on level 1 agglomerated grids and 1.9% for level 2 agglomerated grids without loss of the flux conservation. Moreover, the computation time reductions are at least 59% for the micro-CT images tested in this study. This approach is suitable for rapid estimation of absolute permeability from micro-CT images of rocks, particularly on large systems with high pore voxel counts.