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TitleSimulations of solute transport in fractured porous media using 2D percolation networks with uncorrelated hydraulic conductivity fields
AuthorRivard, C; Delay, F
SourceHydrogeology Journal vol. 12, no. 6, 2004 p. 613-627, https://doi.org/10.1007/s10040-004-0363-z
Year2004
Alt SeriesEarth Sciences Sector, Contribution Series 2005609
PublisherSpringer Nature
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
Subjectshydrogeology; groundwater; groundwater flow; hydraulic conductivity; porosity; fractures; dispersal patterns; permeability; hydrodynamics; models; percolation theory; heterogeneity; connectivity
Illustrationssimulations; frequency distribution diagrams; plots
ProgramNSERC Natural Sciences and Engineering Research Council of Canada
ProgramFCAR - Fonds pour la Formation de Chercheurs et l'Aide à la Recherche
Released2004 09 10
AbstractTwo-dimensional percolation networks have been used to model a disordered and fractured porous medium. The advantage of percolation networks is that they allow the flow and transport properties of the system to be systematically studied as a function of the connectivity of the fractures and/or the permeable regions. The aim of this research is to study hydrodynamic dispersion in such networks, and to investigate the behavior of the longitudinal dispersion coefficient DL with binary and log-normally distributed hydraulic conductivity fields. In particular, the study focuses on the behavior of DL at the percolation threshold pc, where the insufficiency of flow field homogenization and the limited number of tortuous paths for flow and transport force DL to behave anomalously, i.e., to be scale- and time-dependent. The simulations indicate that the DL population taken over a large number of the network realizations resembles a log-normal distribution, hence indicating that, unlike the hydraulic conductivity, DL is not a self-averaged property whose variance should tend to zero when the size of the system tends to infinity. In addition, it was found that the power law that characterizes the scale dependence of DL is contingent upon its computation method. Moreover, DL is found to have a completely different behavior in networks with low and high connectivities.
GEOSCAN ID221637