Hierarchical simulation of aquifer heterogeneity: implications of different simulation settings on solute-transport modeling | [Simulation hiérarchique de l’hétérogénéité des aquifères: implications de différentes configurations de simulation sur la modélisation du transport de solutés]

The fine-scale heterogeneity of porous media affects the large-scale transport of solutes and contaminants in groundwater and it can be reproduced by means of several geostatistical simulation tools. However, including the available geological information in these tools is often cumbersome. A hierarchical simulation procedure based on a binary tree is proposed and tested on two real-world blocks of alluvial sediments, of a few cubic meters volume, that represent small-scale aquifer analogs. The procedure is implemented using the sequential indicator simulation, but it is so general that it can be adapted to various geostatistical simulation tools, improving their capability to incorporate geological information, i.e., the sedimentological and architectural characterization of heterogeneity. When compared with a standard sequential indicator approach on bi-dimensional simulations, in terms of proportions and connectivity indicators, the proposed procedure yields reliable results, closer to the reference observations. Different ensembles of three-dimensional simulations based on different hierarchical sequences are used to perform numerical experiments of conservative solute transport and to obtain ensembles of equivalent pore velocity and dispersion coefficient at the scale length of the blocks (meter). Their statistics are used to estimate the impact of the variability of the transport properties of the simulated blocks on contaminant transport modeled on bigger domains (hectometer). This is investigated with a one-dimensional transport modeling based on the Kolmogorov-Dmitriev theory of branching stochastic processes. Applying the proposed approach with diverse binary trees and different simulation settings provides a great flexibility, which is revealed by the differences in the breakthrough curves.