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Full-waveform inversion of GPR data acquired between boreholes in Rustrel carbonates

Abstract : Full waveform inversion (FWI) of seismic or Ground Penetrating Radar data provides high-resolution quantitative images of the constitutive parameters of the rock/soil which control seismic/GPR wave propagation. We developed a 2D inversion tool in the frequency domain adapted to the multi-parameter physics controlling GPR propagation in isotropic non dispersive media, i.e. dielectric permittivity and electrical conductivity. This inversion engine was previously tested using synthetic 2D data to mitigate the trade-off between the two parameter classes. In this paper, we present the required processing techniques and first inversion results obtained on a real GPR dataset acquired in carbonates with a cross-hole configuration. The presence of the 2 m diameter underground gallery at depth constitutes a nice target to test the robustness, efficiency and resolution of the inversion in such high-contrasts context. Starting from a time tomographic image for the dielectric permittivity and from a homogeneous conductivity, we show that FWI is efficient to retrieve high resolution images of dielectric permittivity but struggles with electrical conductivity. As a quality control, we compare real and synthetic radargrams computed from the tomography and final images, showing the efficiency of the process to reconstruct some events but also underlying some issues, particularly on large incidence angles amplitude traces.
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https://hal.archives-ouvertes.fr/hal-02009517
Contributor : Ludovic Métivier Connect in order to contact the contributor
Submitted on : Thursday, March 17, 2022 - 4:19:39 PM
Last modification on : Sunday, April 24, 2022 - 3:11:26 PM
Long-term archiving on: : Saturday, June 18, 2022 - 7:38:26 PM

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Hugo Pinard, Stéphane Garambois, Ludovic Métivier, Michel Dietrich, G. Sénéchal, et al.. Full-waveform inversion of GPR data acquired between boreholes in Rustrel carbonates. E3S Web of Conferences, EDP Sciences, 2016, Special Issue: i-DUST 2016 – Inter-Disciplinary Underground Science & Technology, Avignon, June 1-3, 2016, 12, pp.01002:1--7. ⟨10.1051/e3sconf/20161201002⟩. ⟨hal-02009517⟩

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