Synthetic benchmark for modeling flow in 3D fractured media

Abstract : Intensity and localization of flows in fractured media have promoted the development of a large range of different modeling approaches including Discrete Fracture Networks, pipe networks and equivalent continuous media. While benchmarked usually within site studies, we propose an alternative numerical benchmark based on highly-resolved Discrete Fracture Networks (DFNs) and on a stochastic approach. Test cases are built on fractures of different lengths, orientations, aspect ratios and hydraulic apertures, issuing the broad ranges of topological structures and hydraulic properties classically observed. We present 18 DFN cases, with 10 random simulations by case. These 180 DFN structures are provided and fully documented. They display a representative variety of the configurations that challenge the numerical methods at the different stages of discretization, mesh generation and system solving. Using a previously assessed mixed hybrid finite element method (Erhel et al., 2009a), we systematically provide reference flow and head solutions. Because CPU and memory requirements stem mainly from system solving, we study direct and iterative sparse linear solvers. We show that the most cpu-time efficient method is a direct multifrontal method for small systems, while conjugate gradient preconditioned by algebraic multrigrid is more relevant at larger sizes. Available results can be used further as references for building up alternative numerical and physical models in both directions of improving accuracy and efficiency.
keyword : Stochastic model
Type de document :
Article dans une revue
Computers & Geosciences, Elsevier, 2013, 50, pp.59-71. 〈10.1016/j.cageo.2012.07.025〉
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Contributeur : Géraldine Pichot <>
Soumis le : mercredi 26 septembre 2012 - 14:51:17
Dernière modification le : mercredi 11 avril 2018 - 02:01:11



Jean-Raynald De Dreuzy, Géraldine Pichot, Baptiste Poirriez, Jocelyne Erhel. Synthetic benchmark for modeling flow in 3D fractured media. Computers & Geosciences, Elsevier, 2013, 50, pp.59-71. 〈10.1016/j.cageo.2012.07.025〉. 〈hal-00735675〉



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