Pore-network modeling of particle retention in porous media

Transport and filtration of micron and submicron particles in porous media is important in applications such as water purification, contaminants dispersion, and drilling mud invasion. Existing macroscopic models often fail to be predictive without empirical adjustments and a more fundamental approach may be required. We develop a physically-representative, 3D pore network model based on a particle tracking method to simulate particle retention and permeability impairment in polydisperse particle systems. The model includes the effect of hydraulic drag, gravity, electrostatic and van der Waals forces, as well as Brownian motion. A converging-diverging pore throat geometry is used to capture the mechanism of interception. With the analytical solution of fluid velocity within a pore throat, the trajectory of each particle is calculated explicitly. We also incorporate surface roughness and particle-surface interaction to determine particle attachment and detachment. Pore throat structure and conductivity are updated dynamically to account for the effect of deposited particles. Predictions of effluent concentration and macroscopic filtration coefficient are in good agreement with published experimental data. We find that the filtration coefficient is dependent on the relative angle between fluid flow and gravity. Particle deposition by interception is significant for large particle/grain size ratios. Brownian diffusion is the primary cause of retention at low Peclet numbers, especially for small gravity numbers. Particle size distribution is found to be a cause of hyperexponential deposition often observed in experiments. Permeability reduction was small for strong repulsive forces because particles only deposited in paths of slow velocity. (c) 2017 American Institute of Chemical Engineers AIChE J, 63: 3118-3131, 2017