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Title: Influence of injection mode on transport properties in kilometer-scale three-dimensional discrete fracture networks

Journal Article · · Water Resources Research
DOI:https://doi.org/10.1002/2015WR017151· OSTI ID:1255226
 [1];  [2];  [1];  [1];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

We investigate how the choice of injection mode impacts transport properties in kilometer-scale three-dimensional discrete fracture networks (DFN). The choice of injection mode, resident and flux-weighted, is designed to mimic different physical phenomena. It has been hypothesized that solute plumes injected under resident conditions evolve to behave similarly to solutes injected under flux-weighted conditions. Previously, computational limitations have prohibited the large-scale simulations required to investigate this hypothesis. We investigate this hypothesis by using a high-performance DFN suite, dfnWorks, to simulate flow in kilometer-scale three-dimensional DFNs based on fractured granite at the Forsmark site in Sweden, and adopt a Lagrangian approach to simulate transport therein. Results show that after traveling through a pre-equilibrium region, both injection methods exhibit linear scaling of the first moment of travel time and power law scaling of the breakthrough curve with similar exponents, slightly larger than 2. Lastly, the physical mechanisms behind this evolution appear to be the combination of in-network channeling of mass into larger fractures, which offer reduced resistance to flow, and in-fracture channeling, which results from the topology of the DFN.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
20140002DR; AC52-06NA25396; AC05-00OR22725
OSTI ID:
1255226
Alternate ID(s):
OSTI ID: 1265639
Report Number(s):
LA-UR-14-28670
Journal Information:
Water Resources Research, Vol. 51, Issue 9; Conference: AGU Fall Meeting, San Fransisco, California, United States; 2014-12-15; ISSN 0043-1397
Publisher:
American Geophysical Union (AGU)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 67 works
Citation information provided by
Web of Science

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Cited By (8)

Characterizing the heterogeneity of karst critical zone and its hydrological function: An integrated approach journal August 2018
Machine learning for graph-based representations of three-dimensional discrete fracture networks journal January 2018
Robust system size reduction of discrete fracture networks: a multi-fidelity method that preserves transport characteristics journal September 2018
Model reduction for fractured porous media: a machine learning approach for identifying main flow pathways journal March 2019
Upscaling and Prediction of Lagrangian Velocity Dynamics in Heterogeneous Porous Media journal May 2019
Stochastic modeling of flow and conservative transport in three-dimensional discrete fracture networks journal January 2019
Stochastic modeling of flow and conservative transport in three-dimensional discrete fracture networks posted_content August 2018
Machine learning for graph-based representations of three-dimensional discrete fracture networks text January 2017