Journal
ADVANCES IN WATER RESOURCES
Volume 94, Issue -, Pages 486-497Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.advwatres.2016.06.010
Keywords
Discrete fracture networks; Subsurface flow and transport; Heterogeneity; Advective transport; Aperture variability; High-performance computing; Fractured rock
Categories
Funding
- U.S. Department of Energy (DOE) Used Fuel Disposition Campaign and DOE Fossil Energy's Strategic Center for Natural Gas and Oil
- LANL Director's Postdoctoral Fellowship
- Center for Nonlinear studies
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The apertures of natural fractures in fractured rock are highly heterogeneous. However, in-fracture aperture variability is often neglected in flow and transport modeling and individual fractures are assumed to have uniform aperture distribution. The relative importance of in-fracture variability in flow and transport modeling within kilometer-scale field-scale fracture networks has been under a matter of debate for a long time because the flow in each single fracture is controlled not only by in-fracture variability but also by boundary conditions. Computational limitations have previously prohibited researchers from investigating the relative importance of in-fracture variability in flow and transport modeling within large-scale fracture networks. We address this question by incorporating internal heterogeneity of individual fractures into flow simulations within kilometer scale three-dimensional fracture networks, where fracture intensity, P-32 (ratio between total fracture area and domain volume) is between 0.027 and 0.031 [1/m]. A recently developed discrete fracture network (DFN) simulation capability, dfnWorks, is used to generate DFNs that include in-fracture aperture variability represented by a stationary log-normal stochastic field with various correlation lengths and variances. The Lagrangian transport parameters, non-reacting travel time and cumulative retention, are calculated along particles streamlines. It is observed that due to local flow channeling early particle travel times are more sensitive to in-fracture variability than the tails of travel time distributions, where no significant effect of the in-fracture transmissivity variations and spatial correlation length is observed. Published by Elsevier Ltd.
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