DarSIA: An open-source Python toolbox for two-scale image processing of dynamics in porous media

TL;DR

DarSIA is an open-source Python toolbox designed for two-scale image processing of porous media dynamics, bridging pore-level details and continuum descriptions to improve analysis of porous materials over time.

Contribution

The paper introduces DarSIA, a novel Python toolbox that adapts classical image processing to physical images of porous media, enabling multi-scale analysis of flow dynamics.

Findings

Effective multi-scale image analysis of porous media

Open-source toolbox facilitates reproducible research

Improves measurement of physical parameters in porous materials

Abstract

Understanding porous media flow is inherently a multi-scale challenge, where at the core lies the aggregation of pore-level processes to a continuum, or Darcy-scale, description. This challenge is directly mirrored in image processing, where grains and interfaces may be clearly visible, yet continuous parameters are desirable to measure. Classical image processing is poorly adapted to this setting, as most techniques do not explicitly utilize the fact that the image contains explicit physical processes. Here, we adapt classical image processing concepts to what we define as physical images of porous materials and processes within them. This is realized through the development of a new open-source image analysis toolbox specifically adapted to time-series of images of porous materials.