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Modeling fracture flow with a stochastic discrete fracture network: calibration and validation: 1. The flow model

Modeling fracture flow with a stochastic discrete fracture network: calibration and validation:... A large‐scale investigation of fracture flow was recently conducted in a granite uranium mine at Fanay‐Augères, France. Its aim was to develop a methodology for the investigation of possible nuclear waste repository sites in crystalline environments, and thus to determine what measurements to make and what models to use in order to predict the flow and transport properties of the medium, i.e., their average behaviors and spatial variabilities at different scales. Four types of data were collected: (1) geometry of the fracture network; (2) local hydraulic properties measured by injection tests in boreholes; (3) global hydraulic behavior from flow rate and piezometric head distribution at a 106 m3 scale; and (4) tracer tests performed at a scale of up to 40 m. A stochastic fracture network model assuming negligible matrix permeability was developed and calibrated essentially on data 1 and 2 above; this was then used to predict data 3 and 4 in an attempt to validate both the parameters and the structure of the model. In this first part, only the flow problem (data 1) is discussed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Water Resources Research Wiley

Modeling fracture flow with a stochastic discrete fracture network: calibration and validation: 1. The flow model

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References (26)

Publisher
Wiley
Copyright
Copyright © 1990 by the American Geophysical Union.
ISSN
0043-1397
eISSN
1944-7973
DOI
10.1029/WR026i003p00479
Publisher site
See Article on Publisher Site

Abstract

A large‐scale investigation of fracture flow was recently conducted in a granite uranium mine at Fanay‐Augères, France. Its aim was to develop a methodology for the investigation of possible nuclear waste repository sites in crystalline environments, and thus to determine what measurements to make and what models to use in order to predict the flow and transport properties of the medium, i.e., their average behaviors and spatial variabilities at different scales. Four types of data were collected: (1) geometry of the fracture network; (2) local hydraulic properties measured by injection tests in boreholes; (3) global hydraulic behavior from flow rate and piezometric head distribution at a 106 m3 scale; and (4) tracer tests performed at a scale of up to 40 m. A stochastic fracture network model assuming negligible matrix permeability was developed and calibrated essentially on data 1 and 2 above; this was then used to predict data 3 and 4 in an attempt to validate both the parameters and the structure of the model. In this first part, only the flow problem (data 1) is discussed.

Journal

Water Resources Research – Wiley

Published: Mar 1, 1990

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