Full‐waveform inversion of cross‐hole ground‐penetrating radar data to characterize a gravel aquifer close to the Thur River, Switzerland

Abstract

Cross‐hole radar tomography is a useful tool for mapping shallow subsurface electrical properties viz. dielectric permittivity and electrical conductivity. Common practice is to invert cross‐hole radar data with ray‐based tomographic algorithms using first arrival traveltimes and first cycle amplitudes. However, the resolution of conventional standard ray‐based inversion schemes for cross‐hole ground‐penetrating radar (GPR) is limited because only a fraction of the information contained in the radar data is used. The resolution can be improved significantly by using a full‐waveform inversion that considers the entire waveform, or significant parts thereof. A recently developed 2D time‐domain vectorial full‐waveform cross‐hole radar inversion code has been modified in the present study by allowing optimized acquisition setups that reduce the acquisition time and computational costs significantly. This is achieved by minimizing the number of transmitter points and maximizing the number of receiver positions. The improved algorithm was employed to invert cross‐hole GPR data acquired within a gravel aquifer (4–10 m depth) in the Thur valley, Switzerland. The simulated traces of the final model obtained by the full‐waveform inversion fit the observed traces very well in the lower part of the section and reasonably well in the upper part of the section. Compared to the ray‐based inversion, the results from the full‐waveform inversion show significantly higher resolution images. At either side, 2.5 m distance away from the cross‐hole plane, borehole logs were acquired. There is a good correspondence between the conductivity tomograms and the natural gamma logs at the boundary of the gravel layer and the underlying lacustrine clay deposits. Using existing petrophysical models, the inversion results and neutron‐neutron logs are converted to porosity. Without any additional calibration, the values obtained for the converted neutron‐neutron logs and permittivity results are very close and similar vertical variations can be observed. The full‐waveform inversion provides in both cases additional information about the subsurface. Due to the presence of the water table and associated refracted/reflected waves, the upper traces are not well fitted and the upper 2 m in the permittivity and conductivity tomograms are not reliably reconstructed because the unsaturated zone is not incorporated into the inversion domain.

Monte Carlo full-waveform inversion of crosshole GPR data using multiple-point geostatistical a priori information

“…The adjoint-based method has been successfully tested on field data (Ernst et al, 2007a;Klotzsche et al, 2010). In addition the suggested probabilistic inversion strategy needs substantially more (computationally expensive) forward calculations than does the traditional adjoint-based approach.…”

“…Recently, the algorithm of Ernst et al (2007b) has been improved such that it exploits the full vector field of the electromagnetic wave propagation and allows for arbitrary antennae geometry . Klotzsche et al (2010) demonstrate an application of the improved code to crosshole GPR waveform data acquired in a gravel aquifer. Lately, Meles et al (2011) demonstrated that the adjoint-based method of Ernst et al (2007b) becomes less sensitive to the starting model when the inversion is conditioned to the long wavelengths of the signal in the initial part of the inversion and higher frequencies are gradually incorporated.…”

Mapping sand layers in clayey till using crosshole ground-penetrating radar

“…Both procedures are dependent on the electrical permittivity and conductivity starting models and must therefore be re-done when these are altered. A comprehensive description of how to apply the FWI approach to field data can be found in Klotzsche et al (2010) and Keskinen et al (2017).…”

“…The recorded EM signal provides information on the electrical permittivity and the electrical conductivity of the investigated formation, that can be related to velocity and the attenuation of the EM wave, respectively (Annan, 2005). To date, published field studies using crosshole GPR only include sediments with low electrical conductivity, e.g., unconsolidated sands (Cassiani et al, 2006;Irving et al, 2007;Haarder et al, 2015;Looms et al, 2008;Klotzsche et al, 2010;Gueting et al, 2015), sandstone (Binley et al, 2002), and chalk (Keskinen et al, 2017). In general, clayey environments have been avoided as the attenuation of the EM signal reduces the signal strength and thereby the possible distance between boreholes.…”

Underground structure defect detection and reconstruction using crosshole GPR and Bayesian waveform inversion

“…This approach much better extracts the information of the measured GPR data and can much more accurately simulate EM wave propagation, boundary conditions and antenna properties. This approach was first used in seismic inversion [24,25], then introduced to crosshole GPR inversion [26,27], and is an enormous improvement over ray-based inversion [5,6,[28][29][30][31][32][33][34][35].…”