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A parallel scientific software for heterogeneous hydrogeoloy

Part of the Lecture Notes in Computational Science and Engineering book series (LNCSE,volume 67)

Abstract

Numerical modelling is an important key for the management and remediation of groundwater resources [28]. As opposed to surface water and to highly karstic geologies, groundwater does not flow in well-identified open streams but is like water flowing in the voids of a sponge. Groundwater is highly dependent on the percentage of pores (porosity), size and connectivity of the pores that controls the permeability of the medium. Its quality depends on the biochemical reactivity of the crossed geological media and on the kinetics of the biochemical reactions. These parameters (porosity, permeability, reactivity) are highly variable. Several field experiments show that the natural geological formations are highly heterogeneous, leading to preferential flow paths and stagnant regions. The contaminant migration is strongly affected by these irregular water velocity distributions. Transport of contaminant by advection and dispersion induce a large spreading of the particles generally called plume. The characterization of the plume remains a much debated topic [7,16,25]. Fractures and heterogeneous sedimentary units cannot be identified whatever the remote data, whether geophysical, geological or hydraulic. Because data give a rather scarce description of the medium hydraulic properties, predictions rely heavily on numerical modelling. Numerical modelling should integrate the multi-scale geological heterogeneity, simulate the hydraulic flow and transport phenomena and quantify uncertainty coming from the lack of data. Analytical techniques like homogenization or perturbations are in general not relevant. Modelling must thus be performed in a probabilistic framework that transfers the lack of data on prediction variability [1]. Practically, random studies require running a large number of simulations, for two reasons. First, non intrusive Uncertainty Quantification methods rely on sampling of data. Second, the questions addressed must consider a large panel of parameters (Peclet number, variance of probabilistic models, etc). The hydraulic simulations must be performed on domains of a large size, at the scale of management of the groundwater resource or at the scale of the homogeneous medium type in terms of geology. This domain must be discretized at a fine resolution to take into account the scale of geological heterogeneities. Also, large time ranges must be considered in order to determine an asymptotic behaviour. High performance computing is thus necessary to carry out these large scale simulations.

Keywords

  • Fracture Network
  • Peclet Number
  • Fracture Medium
  • Discrete Fracture Network
  • Heterogeneous Porous Medium

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Erhel, J., de Dreuzy, R., Beaudoin, ., Bresciani, E., Tromeur-Dervout, . (2009). A parallel scientific software for heterogeneous hydrogeoloy. In: Parallel Computational Fluid Dynamics 2007. Lecture Notes in Computational Science and Engineering, vol 67. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92744-0_5

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