On a workflow for efficient computation of the permeability of tight sandstones

TL;DR

This paper introduces a workflow combining specialized solvers and image classification techniques for efficient pore-scale simulation of flow in tight sandstones, addressing multiscale porosity challenges.

Contribution

It develops robust solvers for Stokes and Stokes-Brinkman equations tailored for low-porosity images and includes a classification method for pore connectivity, enhancing simulation efficiency.

Findings

Workflow is efficient and robust for tight reservoir images.

Solvers effectively handle multiscale porosity.

Preprocessing improves pore connectivity analysis.

Abstract

The paper presents a workflow for fast pore-scale simulation of single-phase flow in tight reservoirs typically characterized by low, multiscale porosity. Multiscale porosity implies that the computational domain contains porous voxels (unresolved porosity) in addition to pure fluid voxels. In this case, the Stokes-Brinkman equations govern the flow, with the Darcy term needed to account for the flow in the porous voxels. As the central part of our workflow, robust and efficient solvers for Stokes and Stokes-Brinkman equations are presented. The solvers are customized for low-porosity binary and multiclass images, respectively. Another essential component of the workflow is a preprocessing module for classifying images with respect to the connectivity of the multiscale pore space. Particularly, an approximation of the Stokes-Brinkman problem, namely, the Darcy problem, is investigated for the images that do not have pure fluid percolation paths. Thorough computational experiments demonstrate efficiency and robustness of the workflow for simulations on images from tight reservoirs. Raw files describing the used CT images are provided as supplementary materials to enable other researchers to use them.