Bridging scales in porous media: cDFT-informed pore network modelling for fluid transport with nanoconfined phase behavior

TL;DR

This paper presents a multiscale pore network modeling approach incorporating nanoconfined phase behavior via cDFT to better predict fluid transport and permeability in porous media.

Contribution

It introduces a novel multiscale framework that integrates classical DFT calculations into pore network models to account for capillary condensation effects.

Findings

Permeability decreases with pore blockage due to capillary condensation.

Porous media geometry and thermodynamic conditions significantly influence permeability.

The method improves understanding of multiscale transport phenomena in nanoporous materials.

Abstract

The simulation of fluid flow in real, multiscale porous media remains challenging due to the complexity of nanoscale phenomena and the difficulty of developing upscaling methodologies. In this study, we introduce a multiscale filtration framework based on quasi-static Pore Network Modelling, incorporating the effects of pore blockage resulting from capillary condensation of fluid in the nanoporous space. To accurately predict capillary condensation in nanoconfinement, we apply classical Density Functional Theory calculations considering capillary hysteresis. The pores blocked by condensate are excluded from the fluid flow, resulting in a decrease in permeability of the porous space. Our findings demonstrate that the resulting permeability is strongly dependent on the geometry of the porous space, including pore size distribution, throat size distribution, sample size, and the particular structure of the sample, as well as thermodynamic conditions and processes, specifically pressure growth or decrease. Overall, the presented research contributes valuable insights into multiscale transport phenomena and facilitates the advancement of upscaling techniques.