Pore Network and Medial Axis simultaneous extraction through Maximal Ball Algorithm

TL;DR

This paper introduces a novel method combining Max Ball Algorithm and Medial Axis extraction to efficiently characterize pore structures in porous media, enabling improved flow simulations and morphological analysis.

Contribution

The work presents a new approach that integrates pore network and medial axis extraction within a single framework, enhancing pore structure characterization.

Findings

Effective extraction of medial axis networks from porous media

Preserves morphology while enabling flow simulation

Applicable to sandstone and carbonate rock samples

Abstract

Network Extraction algorithms from X-ray microcomputed tomography have become a routine method to obtain pore connectivity and pore morphology information from porous media. The main approaches for this extraction are either based on Max Ball Algorithm or Medial Axis Extraction. The first is a robust method to separate the pore space into pore and throats, which provides the pore and throat sizes distributions directly. The second simplifies the medium by thinning the volume into a one voxel wide centerline that preserves the volume's topological information. Since each method has drastically different implementations, it is not usual to use both to characterize the porous structure. This work presents a method to extract a simplified centerline of porous materials by adding few more steps to the well-established Max Ball algorithm. Results for sandstones and carbonate rock samples show that this Medial-Axis network can be used for single phase flow simulations, as well as preserves the mediums morphology.