Title: Advective Transport in Discrete Fracture Networks With Connected and Disconnected Textures Representing Internal Aperture Variability

Abstract

Flow and transport in three–dimensional discrete fracture networks with internal variability in aperture and permeability are investigated using a numerical model. The analysis is conducted for three different texture types representing internal variability considering various correlation lengths and for an increase in domain size corresponding to an increase in network complexity. Internal variability in discrete fracture networks generally increases median travel times and delays arrival of bulk mass transport when compared against reference cases without texture, corresponding to smooth fractures. In particular, internal variability textures with weak connectivity increase travel times nonlinearly with domain size increase, further delaying bulk mass arrival. Textures with strong connectivity can however decrease median travel times, accelerating bulk mass arrival, but only for limited ranges of correlation length and domain size. As domain size increases, travel times of textures with strong connectivity converge toward travel times obtained for classical multivariant Gaussian textures. Thus, accounting for internal fracture variability is potentially significant for improving conservative estimates of bulk mass arrival, flow channeling, and advective and reactive transport in large–scale discrete fracture networks. Further, early mass arrival can arrive significantly earlier for textures with strong connectivity and classical Gaussian textures corresponding to intermediate connectivity but are onlymore » slightly affected by textures with weak connectivity. Thus, accounting for internal variability in fractures is also important for accurate estimates of early solute mass arrival. Here, the overall impact on predictive transport modeling will depend on the extent of, or lack of, internal fracture connectivity structure in real–world fractured rocks.« less

Authors:

Frampton, A.  ^[1];

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• Search DOE PAGES for ORCID "0000-0002-4587-6706"
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Hyman, J. D.  ^[2];

• Search DOE PAGES for author "Hyman, J. D."
• Search DOE PAGES for ORCID "0000-0002-4224-2847"
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Zou, L.  ^[3]

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• Search DOE PAGES for ORCID "0000-0002-0958-7181"
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+ Show Author Affiliations

1. Department of Physical GeographyStockholm University Stockholm Sweden, Bolin Centre for Climate ResearchStockholm University Stockholm Sweden
2. Computational Earth Science (EES‐16), Earth and Environmental Sciences DivisionLos Alamos National Laboratory Los Alamos NM USA
3. Department of Physical GeographyStockholm University Stockholm Sweden, Department of Sustainable Development, Environmental Science and EngineeringRoyal Institute of Technology (KTH) Stockholm Sweden

Publication Date:

2019-07-06

Research Org.:

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Sponsoring Org.:

USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)

OSTI Identifier:

1560167

Alternate Identifier(s):

OSTI ID: 1560169; OSTI ID: 1565895

Report Number(s):

LA-UR-18-29968
Journal ID: ISSN 0043-1397

Grant/Contract Number:  

AC52‐06NA25396; 89233218CNA000001

Resource Type:

Published Article

Journal Name:

Water Resources Research

Additional Journal Information:

Journal Name: Water Resources Research Journal Volume: 55 Journal Issue: 7; Journal ID: ISSN 0043-1397

Publisher:

American Geophysical Union (AGU)

Country of Publication:

United States

Language:

English

Subject:

54 ENVIRONMENTAL SCIENCES; Earth Sciences; decision support; analytical models; streamflow depletion; irrigation; stream‐aquifer interactions; California