Volume 8, Issue 4
Conditioning Discrete Fracture Network Models of Groundwater Flow

K. Cliffe, D. Holton, P. Houston, C. Jackson, S. Joyce & A. Milne

DOI:

Int. J. Numer. Anal. Mod., 8 (2011), pp. 543-565

Published online: 2011-08

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  • Abstract

Many geological formations consist of crystalline rock that have very low matrix permeability but allow flow through an interconnected network of fractures. Understanding the flow of groundwater through such rocks is important in considering disposal of radioactive waste in underground repositories. A specific area of interest is the conditioning of fracture transmissivities on measured values of pressure in these formations. While there are existing methods to condition transmissivity fields on transmissivity, pressure and flow measurements for a continuous porous medium, considerably less work has been devoted to conditioning discrete fracture networks. This article presents two new methods for conditioning fracture transmissivities on measured pressures in a discrete fracture network. The first approach adopts a linear approximation when fracture transmissivities are mildly heterogeneous, while the minimisation of a suitable objective function is undertaken when fracture transmissivities are highly heterogeneous. The second conditioning algorithm is a Bayesian method that finds a maximum a posteriori (MAP) estimator which maximises the posterior distribution defined by Bayes

  • Keywords

Conditioning Groundwater Flow Discrete Fracture Network Finite Element Methods

  • AMS Subject Headings

35L60 35Q35 76B15 76B65

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COPYRIGHT: © Global Science Press

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@Article{IJNAM-8-543, author = {K. Cliffe, D. Holton, P. Houston, C. Jackson, S. Joyce and A. Milne}, title = {Conditioning Discrete Fracture Network Models of Groundwater Flow}, journal = {International Journal of Numerical Analysis and Modeling}, year = {2011}, volume = {8}, number = {4}, pages = {543--565}, abstract = {Many geological formations consist of crystalline rock that have very low matrix permeability but allow flow through an interconnected network of fractures. Understanding the flow of groundwater through such rocks is important in considering disposal of radioactive waste in underground repositories. A specific area of interest is the conditioning of fracture transmissivities on measured values of pressure in these formations. While there are existing methods to condition transmissivity fields on transmissivity, pressure and flow measurements for a continuous porous medium, considerably less work has been devoted to conditioning discrete fracture networks. This article presents two new methods for conditioning fracture transmissivities on measured pressures in a discrete fracture network. The first approach adopts a linear approximation when fracture transmissivities are mildly heterogeneous, while the minimisation of a suitable objective function is undertaken when fracture transmissivities are highly heterogeneous. The second conditioning algorithm is a Bayesian method that finds a maximum a posteriori (MAP) estimator which maximises the posterior distribution defined by Bayes}, issn = {2617-8710}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/ijnam/700.html} }
TY - JOUR T1 - Conditioning Discrete Fracture Network Models of Groundwater Flow AU - K. Cliffe, D. Holton, P. Houston, C. Jackson, S. Joyce & A. Milne JO - International Journal of Numerical Analysis and Modeling VL - 4 SP - 543 EP - 565 PY - 2011 DA - 2011/08 SN - 8 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/ijnam/700.html KW - Conditioning KW - Groundwater Flow KW - Discrete Fracture Network KW - Finite Element Methods AB - Many geological formations consist of crystalline rock that have very low matrix permeability but allow flow through an interconnected network of fractures. Understanding the flow of groundwater through such rocks is important in considering disposal of radioactive waste in underground repositories. A specific area of interest is the conditioning of fracture transmissivities on measured values of pressure in these formations. While there are existing methods to condition transmissivity fields on transmissivity, pressure and flow measurements for a continuous porous medium, considerably less work has been devoted to conditioning discrete fracture networks. This article presents two new methods for conditioning fracture transmissivities on measured pressures in a discrete fracture network. The first approach adopts a linear approximation when fracture transmissivities are mildly heterogeneous, while the minimisation of a suitable objective function is undertaken when fracture transmissivities are highly heterogeneous. The second conditioning algorithm is a Bayesian method that finds a maximum a posteriori (MAP) estimator which maximises the posterior distribution defined by Bayes
K. Cliffe, D. Holton, P. Houston, C. Jackson, S. Joyce & A. Milne. (1970). Conditioning Discrete Fracture Network Models of Groundwater Flow. International Journal of Numerical Analysis and Modeling. 8 (4). 543-565. doi:
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