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True amplitude recovery of multifold multicomponent georadar data

English title True amplitude recovery of multifold multicomponent georadar data
Applicant Green Alan G.
Number 113669
Funding scheme Project funding
Research institution Institut für Geophysik ETH Zürich
Institution of higher education ETH Zurich - ETHZ
Main discipline Geophysics
Start/End 01.01.2007 - 31.12.2009
Approved amount 142'322.00
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Keywords (17)

georadar; GPR; inversion; imaging; true-amplitude; wavelet; electromagnetic; TE; TM; migration; algorithms; ground-penetrating; radar; full-waveform inversion; ground-penetrating radar; permittivity; electrical conductivitiy

Lay Summary (English)

Lay summary
We have developed a new, full-waveform ground-penetrating radar (GPR) multi-component inversion scheme for imaging the shallow subsurface using arbitrary recording confgurations. It yields significantly higher resolution images than conventional tomographic techniques based on first-arrival times and pulse amplitudes. The inversion is formulated as a non-linear least-squares problem in which the missfit between observed and modelled data is minimized. The full-waveform modelling is implemented by means of a finite-difference time-domain solution of Maxwell's equations. We derive an iterative gradient method in which the steepest descent direction, used to update iteratively the permittivity and conductivity distributions in an optimal way, is found by cross-correlating the forward vector wavefield and the backward-propagated residual wavefield. The formulation of the solution is given in a very general, albeit compact and elegant fashion. Each iteration step of our inversion scheme requires several calculations of propagating wavefields. Novel features of the scheme compared to previous full-waveform GPR inversions are that (i) the permittivity and conductivity distributions are updated simultaneously (rather than consecutively) at each iterative step using improved gradient and step length formulations, (ii) the scheme is able to exploit the full vector wavefield, and consequently (iii) various data sets/survey types (e.g., crosshole, borehole-to-surface) can be individually or jointly inverted. Several synthetic examples involving both homogeneous and layered stochastic background models with embedded anomalous inclusions demonstrate the superiority of the new scheme over previous approaches.
Direct link to Lay Summary Last update: 21.02.2013

Responsible applicant and co-applicants


Associated projects

Number Title Start Funding scheme
129615 True amplitude recovery of multifold multicomponent georadar data 01.04.2010 Project funding
129615 True amplitude recovery of multifold multicomponent georadar data 01.04.2010 Project funding


True amplitude processing and imaging (migration) algorithms for multifold multicomponent georadar (GPR) data will be developed. The aim is to directly extract subsurface properties from reflector amplitudes. Most existing imaging algorithms for georadar data only use reflection traveltimes. They do not usually account for the polarization and amplitudes of the electromagnetic waves. Other imaging algorithms use far-field radiation patterns that can differ significantly from the actual radiation patterns. To relate reflector amplitudes directly to changes of subsurface properties, special processing steps that compensate accurately for attenuation, spherical divergence and the radiation characteristics of source and receiver antennas are required.

Recently, an improved multicomponent imaging algorithm was developed that accounts for the vectorial radiation characteristics of point-source and point-receiver antennas on the surface and the polarization characteristics of electromagnetic waves traveling through the shallow subsurface. Instead of using far-field expressions, it is now based on a forward model with total-field radiation characteristics that accurately describe the traveltimes, polarizations and amplitudes of reflections. To extract reliable information on the physical property contrasts in the shallow underground, we propose to extend the present common-offset multicomponent imaging algorithm and to develop true amplitude multifold multicomponent processing and imaging algorithms that will exploit all information contained in recorded georadar data.

Our true amplitude multifold multicomponent processing and imaging algorithms will be based on improved forward models. We will investigate the possibility of including velocity variations with depth (presently a homogeneous half-space is employed). We will take advantage of increases in computer power by considering hybrid techniques that include finite-difference time-domain modeling for calculating the three-dimensional radiation characteristics in the presence of topography.Robust and fast procedures to describe finite length antennas from the recorded data will be developed. We shall carefully test the new multifold multicomponent processing and imaging algorithms on synthetic data.Finally, two multifold multicomponent 3-D georadar data sets will be recorded, processed and imaged. One will be acquired under controlled conditions and one will be recorded across a well-understood geological/hydrogeological field site within Switzerland.

In principle, the new true amplitude multifold multicomponent processing and imaging algorithms will enable improved characterizations of physical property contrasts in the shallow underground to be made. A wide variety of projects are expected to benefit eventually from this technique, including material property evaluation, contaminant transport studies, agricultural surveys, landfill investigations, and the detection of underground cables, cavities, pipes, tunnels and unexploded ordnance.