Minimum requirements for predictive pore-network modeling of solute transport in micromodels. (October 2017)

• Record Type: Journal Article
• Authors: Mehmani, Yashar; Tchelepi, Hamdi A.
• Is Part Of: Advances in water resources. Volume 108(2017)
• Page Start: 83
• Page End: 98
• Publication Date: 2017-10
• Subjects: Flow in porous media -- Transport -- Pore-network modeling -- Direct numerical simulation -- Pore-network extraction -- Micromodels; Hydrology -- Periodicals; Hydrodynamics -- Periodicals; Hydraulic engineering -- Periodicals; 551.48
• DOI: 10.1016/j.advwatres.2017.07.014
• Languages: English
• ISSNs: 0309-1708

Abstract

Highlights: Minimum requirements for predictive pore-network modeling of transport determined. Novel pore-network model and network extraction methods developed. Compared to direct numerical simulation for a range of micromodel heterogeneities. Impact of common network modeling practices on predictions assessed. Abstract: Pore-scale models are now an integral part of analyzing fluid dynamics in porous materials (e.g., rocks, soils, fuel cells). Pore network models (PNM) are particularly attractive due to their computational efficiency. However, quantitative predictions with PNM have not always been successful. We focus on single-phase transport of a passive tracer under advection-dominated regimes and compare PNM with high-fidelity direct numerical simulations (DNS) for a range of micromodel heterogeneities. We identify the minimum requirements for predictive PNM of transport. They are: (a) flow-based network extraction, i.e., discretizing the pore space based on the underlying velocity field, (b) a Lagrangian (particle tracking) simulation framework, and (c) accurate transfer of particles from one pore throat to the next. We develop novel network extraction and particle tracking PNM methods that meet these requirements. Moreover, we show that certain established PNM practices in the literature can result in first-order errors in modeling advection-dominated transport. They include: all Eulerian PNMs, networks extracted based on geometric metrics only, and flux-based nodal transfer probabilities. Preliminary results for a 3D sphere pack are also presented. The simulation inputs for this work are made public to serve as a benchmark for the research community.