Speaker: Enrico Scarpa
Date: Thursday 28th of January 2021, 1:20 pm.
Abstract:
Nowadays, karst aquifers are strategic groundwater resources for the provision of drinking water all around the world. One-fourth of the population worldwide drinks water stored in karst aquifers, which are extremely vulnerable to various pollution sources. However, due to the complexity of karstification patterns and geometries, it is not easy to simulate groundwater flow in karstic aquifers. Over the last years, different techniques have been proposed to model karstic conduit networks (e.g., MODFLOW-CFP, GROUNDWATER). Those techniques include methods based on purely statistical approaches, object-based methods, genetic algorithms that mimic the physico-chemical processes that bring to conduit formation. Consequently, new possibilities have been introduced to evaluate the impact of karstic network architectures on groundwater flow accurately.
This work focuses on modeling the karst network stochastically using a geostatistical technique known as Multiple-Point Statistics (MPS) to characterize the karst architecture in the Dogger aquifer at the hydrogeological experimental site (HES) of Poitiers, France. In particular, here we apply the Direct Sampling (DS), an MPS simulation method, with the recent implementations proposed from the literature. Field data include core description, hydrogeological tests, and seismic surveys. A critical review of the available data set suggests the occurrence of cave patterns and several, well-identified, karst layers. The first step consists of reviewing all the (available data) collected in the last ten years and then studying the correlation between the geological, geophysical, and hydrogeological information. In the second step, DS simulations are performed to obtain several equiprobable realizations. These different DS outcomes can be compared and can estimate a global 3D karstic framework architecture of the Dogger aquifer. The resulting representation of the geological heterogeneity can support flow modeling at the HES and explore the impact of the karstic framework on the dynamic flow.