Structural and hydrodynamic controls on fluid travel time distributions across fracture networks

• 成果类型: Article
• 署名作者: Davy, Philippe; Le Goc, Romain; Darcel, Caroline; Pinier, Benoit; Selroos, Jan-Olof; Le Borgne, Tanguy
• 署名单位: Universite de Rennes; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Earth Sciences & Astronomy (INSU); Swedish Nuclear Fuel & Waste Management Company (SKB); Royal Institute of Technology
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-13197
• DOI: 10.1073/pnas.2414901121
• 发表日期: 2024-11-19
• 关键词: nuclear-waste repository; non-fickian transport; anomalous transport; crystalline rock; FLOW; MODEL; media; dispersion; connectivity; permeability

摘要

Fracture networks are preferential flow paths playing a critical role in a wide range of environmental and industrial problems. Their complex multiscale structure leads to broad distributions of fluid travel times, affecting many biogeochemical processes. Yet, the relationship between the fracture network structures, their hydrodynamic properties, and the resulting anomalous transport dynamics remains unclear. We use a large database of fracture network models to investigate the factors controlling fluid velocity and travel- time distributions across a wide range of networks, from synthetic to field- calibrated models, with aperture variability at both fracture and network scales. Analysis reveals that transport statistics have generic properties across investigated networks, including notably heavy- tailed travel time distributions. Networks of increasing complexity and heterogeneity lead to broader velocity distributions and more channeled velocity fields, where flow concentrates in a narrow channel web in the three- dimensional (3D) fracture structure. While heterogeneity in point- velocity statistics increases travel- time variability, channeling tends to reduce it. This counterintuitive phenomenon challenges current theories, which assume that long travel time power law exponents are determined solely by point- velocity statistics. By analyzing velocity and travel time statistics for different flow structures, we develop a coupled Continuous Time Random Walk framework capturing the unexpected control of the velocity field's spatial structure on anomalous transport in fracture networks. This leads to a unique class of random walk models capturing the respective roles of velocity heterogeneity and spatial structure on transport in networks. These findings open a prospective for characterizing, modeling, and predicting transport dynamics in complex networks, with potential applications to geological, biological, and engineered networks.