Characterizing the Influence of Fracture Density on Network Scale Transport

Journal Article · 19 December 2019 · Journal of Geophysical Research. Solid Earth

DOI: https://doi.org/10.1029/2019jb018547 · OSTI ID:1645084

Sherman, Thomas ^[1]; Hyman, Jeffrey  ^[2]; Dentz, Marco ^[3]; Bolster, Diogo ^[1]

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1. Univ. of Notre Dame, IN (United States)
2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
3. Spanish National Research Council (IDAEA‐CSIC), Barcelona (Spain)

The topology of natural fracture networks is inherently linked to the structure of the fluid velocity field and transport therein. Here we study the impact of network density on flow and transport behaviors. We stochastically generate fracture networks of varying density and simulate flow and transport with a discrete fracture network model, which fully resolves network topology at the fracture scale. We study conservative solute trajectories with Lagrangian particle tracking and find that as fracture density decreases, solute channelization to large local fractures increases, thereby reducing plume spreading. Furthermore, in sparse networks mean particle travel distance increases and local network features, such as velocity zones where flow is counter to the primary pressure gradient, become increasingly important for transport. As the network density increases, network statistics homogenize and such local features have a reduced impact. We quantify local topological influence on transport behavior with an effective tortuosity parameter, which measures the ratio of total advective distance to linear distance at the fracture scale; large tortuosity values are correlated to slow-velocity regions. Additionally, these large tortuosity, slow-velocity regions delay downstream transport and enhance tailing on particle breakthrough curves. Finally, we predict transport with an upscaled, Bernoulli spatial Markov random walk model and parameterize local topological influences with a novel tortuosity parameter. Furthermore, Bernoulli model predictions improve when sampling from a tortuosity distribution, as opposed to a fixed value as has previously been done, suggesting that local network topological features must be carefully considered in upscaled modeling efforts of fracture network systems.

• Research Organization: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES); National Science Foundation (NSF); US Army Research Office (ARO); European Research Council (ERC)
• Grant/Contract Number: 89233218CNA000001; DGE-1841556; W911NF-18-1-0338; CBET-1803989; 0180621ECR; FP7/2007-2013; 617511; 20180621ECR
• OSTI ID: 1645084
• Alternate ID(s): OSTI ID: 1591983
• Report Number(s): LA-UR-19-27671
• Journal Information: Journal of Geophysical Research. Solid Earth, Vol. 125, Issue 1; ISSN 2169-9313
• Publisher: American Geophysical UnionCopyright Statement
• Country of Publication: United States
• Language: English