PhD 5 : Monitoring spatio-temporal water redistribution in the subsurface with seismic methods

Objectives: Estimate water content in the vadose zone/aquifer continuum and its evolution over time from active and passive seismic wave methods. Assess the coeval changes of water content and estimated velocity information from seismic records. Evaluate the sensitivities of these proxies to hydrodynamic parameters

Expected Results: The seismic signal is related to mechanical properties that partly depend on porosity and saturation. The behaviour of shear (S) and pressure (P) waves in the presence of water is partially decoupled, such that the ratio of their propagation velocities Vp/Vs is strongly linked to water saturation. Both Vp and Vs can be recovered by analysing both first arrival and surface waves, hence allowing for estimation of water content variability over decametric spatial scales. Seismic noise interferometry has recently emerged as a promising tool to monitor Vs continuously. We will monitor the subsurface with 3D continuous seismic noise interferometry from a dense network that is referenced to time-lapse active methods and soil moisture observations. Controlled experiments will be carried out (infiltration test, pumping test) to focus on infiltration processes and to enable quantitative comparisons with GPR. Developments will be carried out on Ploemeur site and further applied on Krauthausen and LSBB sites. The full wealth of seismic signals is still underexploited, particularly the temporal evolution of dispersion and attenuation related to wave-induced fluid flow. The experimental approach is here an opportunity to prepare adequate field data to tackle these challenging questions in further work. Finally, we will evaluate the potential of iDAS (Distributed Acoustic Sensing) for continuous monitoring of subsurface water content over long distances.

Supervisors: CNRS Rennes/ Co-Supervisors: UNIL Lausanne, SKB Sweden
Contact : Laurent Longuevergne, laurent.longuevergne(at)univ-rennes1.fr and Ludovic Bodet, ludovic.bodet(at)upmc.fr

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