Spatial Dependency of Clogged Throats in Porous Media: A Microscale Investigation

Summary The understanding of clogging, a pivotal process causing permeability reduction in natural porous media, holds significant implications for the dynamics of subsurface fluid flow. The existing literature falls short in providing comprehensive insights into the nonrandom development of clogging, primarily attributed to the use of simplified pore systems, fragmented understanding of the mechanisms, and a restricted exploration of diverse porous media conditions. This study aims to contribute to a comprehensive understanding of clogging phenomena by specifically validating the hypothesis that clogging events in one throat trigger a spatially dependent influence, thereby enhancing the likelihood of similar occurrences in neighboring throats. To accomplish this, we use robust statistical testing methods to rigorously examine and validate the proposed hypothesis. The research, characterizing two distinct mechanisms for clogging development (i.e., changes in flow path and pore filling), aims to identify governing parameters that dictate their prevalence under varied conditions. Utilizing a pretrained machine learning model (MLM), we classified clogged throats in natural porous media images, predicting clogging pore volumes (PVs) and resulting permeability reduction. Fifty MLM simulations systematically explored porous media geometry impacts, using Latin hypercube sampling (LHS) for key parameter values. Findings reveal spatial correlation between clogged throats, suggesting dependent clogging near each other simultaneously. Hydrophysical parameters, represented by Stokes number, and pore aspect ratio, play a pivotal role in determining the shift between dependent clogging mechanisms. The fine particles’ ability to change direction significantly influences observed clogging behaviors. Examining permeability reduction showcases higher impacts from the pore filling mechanism compared with changes in flow path. This investigation provides valuable insights into spatial correlations, dependent clogging mechanisms, and their effects on permeability in natural porous media, shedding light on crucial factors influencing fluid flow in subsurface formations.