English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

As global groundwater levels continue to decline rapidly, there is a growingneed for advanced techniques to monitor and manage aquifers effectively. Thisstudy focuses on validating a numerical model using seismic data from asmall-scale experimental setup designed to estimate water volume in a porousreservoir. Expanding on previous work with synthetic data, we analyze seismicdata acquired from a controlled experimental site in Laukaa, Finland. Byemploying neural networks, we directly estimate water volume from seismicresponses, bypassing the traditional need for separate determinations, forexample, of reservoir water table level and porosity. The study models wavepropagation through a coupled poroviscoelastic-viscoelastic medium using athree-dimensional discontinuous Galerkin method. The proposed methodology isvalidated against experimental data, aiming to improve precision in mappingcurrent water volumes and contributing to the development of sustainablegroundwater management practices.

Monitoring of water volume in a porous reservoir using seismic data: Validation of a numerical model with a field experiment