New seismic method cuts through guesswork on underground water reserves
Scientists have validated a faster way to measure how much water sits in aquifers using sound waves and artificial intelligence, bypassing the need for multiple separate measurements. The breakthrough could help water utilities and agricultural operators monitor depleting groundwater supplies more cheaply and accurately as global scarcity intensifies.
Originaltitel: Monitoring of water volume in a porous reservoir using seismic data: Validation of a numerical model with a field experiment
Abstract As global groundwater levels continue to decline rapidly, there is a growing need for advanced techniques to monitor and manage aquifers effectively. This study focuses on validating a numerical model using seismic data from a small‐scale experimental setup designed to estimate water volume in a porous reservoir. Expanding on previous work with synthetic data, we analyse seismic data acquired from a controlled experimental site in Laukaa, Finland. By employing neural networks, we directly estimate water volume from seismic responses, bypassing the traditional need for separate determinations, for example, of reservoir water‐table level and porosity. The study models wave propagation through a coupled poroviscoelastic–viscoelastic medium using a three‐dimensional discontinuous Galerkin method. The proposed methodology is validated against experimental data, aiming to improve precision in mapping current water volumes and contributing to the development of sustainable groundwater management practices.