Ground-penetrating radar data diffraction focusing without a velocity model

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. H13-H24
Author(s):  
Nikos Economou ◽  
Antonis Vafidis ◽  
Maksim Bano ◽  
Hamdan Hamdan ◽  
Jose Ortega-Ramirez
Keyword(s):  
Ground Penetrating Radar ◽  
Constant Velocity ◽  
Electromagnetic Waves ◽  
Ground Truth ◽  
Velocity Model ◽  
Migration Velocity ◽  
Dominant Frequency ◽  
Limited Information ◽  
Velocity Range ◽  
Ground Penetrating

Ground-penetrating Radar (GPR) sections commonly suffer from strong scattered energy and weak reflectors with distorted lateral continuity. This is mainly due to the gradual variation of moisture with depth, dense lateral sampling of common-offset GPR traces (which are considered as zero-offset data), along with the small wavelength of the electromagnetic waves that is comparable to the size of the shallow subsurface dielectric heterogeneities. Focusing of the diffractions requires efficient migration that, in the presence of highly heterogeneous subsurface formations, can be improved by a detailed migration velocity model. Such a velocity model is difficult to develop because the common-offset antenna array is mostly used for its reduced time and cost in the data acquisition and processing stages. In such cases, migration processes are based on limited information from velocity analysis of clear diffractions, cores, or other ground truth knowledge, often leading to insufficient imaging. We have developed a methodology to obtain GPR sections with focused diffractions that is based on multipath summation, using weighted stacking (summation) of constant-velocity migrated sections over a predefined velocity range. The success of this method depends on the assignment of an appropriate weight, for each constant-velocity migrated section to contribute to the final stack, and the optimal width of the velocity range used. Additionally, we develop a postmultipath summation processing step, which consists of time-varying spectral whitening, to deal with the decrease of the dominant frequency due to attenuation effects and the additional degraded resolution expected by the constant migration summed images. This imaging strategy leads to GPR sections with sufficiently focused diffractions, enhancing the lateral and the temporal resolution, without the need to explicitly build a migration velocity model.

Removal of wavelet dispersion from ground‐penetrating radar data

Geophysics ◽  
2003 ◽  
Vol 68 (3) ◽  
pp. 960-970 ◽  
Author(s):  
James D. Irving ◽  
Rosemary J. Knight
Keyword(s):  
Ground Penetrating Radar ◽  
Electromagnetic Waves ◽  
Radar Data ◽  
Dominant Frequency ◽  
Seismic Attenuation ◽  
Inverse Q Filtering ◽  
Damped Least Squares ◽  
Ground Penetrating ◽  
Seismic Attenuation Tomography

Wavelet dispersion caused by frequency‐dependent attenuation is a common occurrence in ground‐penetrating radar (GPR) data, and is displayed in the radar image as a characteristic “blurriness” that increases with depth. Correcting for wavelet dispersion is an important step that should be performed before GPR data are used for either qualitative interpretation or the quantitative determination of subsurface electrical properties. Over the bandwidth of a GPR wavelet, the attenuation of electromagnetic waves in many geological materials is approximately linear with frequency. As a result, the change in shape of a radar pulse as it propagates through these materials can be well described using one parameter, Q*, related to the slope of the linear region. Assuming that all subsurface materials can be characterized by some Q* value, the problem of estimating and correcting for wavelet dispersion becomes one of determining Q* in the subsurface and deconvolving its effects using an inverse‐Q filter. We present a method for the estimation of subsurface Q* from reflection GPR data based on a technique developed for seismic attenuation tomography. Essentially, Q* is computed from the downshift in the dominant frequency of the GPR signal with time. Once Q* has been obtained, we propose a damped‐least‐squares inverse‐Q filtering scheme based on a causal, linear model for constant‐Q wave propagation as a means of removing wavelet dispersion. Tests on synthetic and field data indicate that these steps can be very effective at enhancing the resolution of the GPR image.

REFLECTION COEFFICIENT OF AN ELECTROMAGNETIC WAVE IN CONDUCTIVE MEDIA

2018 ◽  
pp. 100-106
Author(s):  
M. S. Sudakova ◽  
M. L. Vladov ◽  
M. R. Sadurtdinov
Keyword(s):  
Reflection Coefficient ◽  
Ground Penetrating Radar ◽  
Electromagnetic Waves ◽  
Water Contamination ◽  
Survey Design ◽  
Direct And Inverse Problems ◽  
The Difference ◽  
Ground Penetrating ◽  
Ideal Dielectric

Within the ground penetrating radar bandwidth the medium is considered to be an ideal dielectric, which is not always true. Electromagnetic waves reflection coefficient conductivity dependence showed a significant role of the difference in conductivity in reflection strength. It was confirmed by physical modeling. Conductivity of geological media should be taken into account when solving direct and inverse problems, survey design planning, etc. Ground penetrating radar can be used to solve the problem of mapping of halocline or determine water contamination.

Marchenko multiple elimination and full wavefield migration in a resonant pinch-out model

Geophysics ◽  
2021 ◽  
pp. 1-59
Author(s):  
Evert Slob ◽  
Lele Zhang ◽  
Eric Verschuur
Keyword(s):  
Constant Velocity ◽  
Local Minimum ◽  
Velocity Model ◽  
Dominant Frequency ◽  
Data Sampling ◽  
Multiple Reflections ◽  
Linear Inversion ◽  
Acoustic Reflection ◽  
Reflection Data ◽  
Multiple Elimination

Marchenko multiple elimination schemes are able to attenuate all internal multiple reflections in acoustic reflection data. These can be implemented with and without compensation for two-way transmission effects in the resulting primary reflection dataset. The methods are fully automated and run without human intervention, but require the data to be properly sampled and pre-processed. Even when several primary reflections are invisible in the data because they are masked by overlapping primaries, such as in the resonant wedge model, all missing primary reflections are restored and recovered with the proper amplitudes. Investigating the amplitudes in the primary reflections after multiple elimination with and without compensation for transmission effects shows that transmission effects are properly accounted for in a constant velocity model. When the layer thickness is one quarter of the wavelength at the dominant frequency of the source wavelet, the methods cease to work properly. Full wavefield migration relies on a velocity model and runs a non-linear inversion to obtain a reflectivity model which results in the migration image. The primary reflections that are masked by interference with multiples in the resonant wedge model, are not recovered. In this case, minimizing the data misfit function leads to the incorrect reflector model even though the data fit is optimal. This method has much lower demands on data sampling than the multiple elimination schemes, but is prone to get stuck in a local minimum even when the correct velocity model is available. A hybrid method that exploits the strengths of each of these methods could be worth investigating.

scholarly journals Study Effect of Objects Orientation in the Mediums On GPR Signal Reflections Using FDTD Simulation

2018 ◽  
Vol 3 (11) ◽  
pp. 73-77
Author(s):  
Aye Mint Mohamed Mostapha ◽  
Gamil Alsharahi ◽  
Abdellah Driouach
Keyword(s):  
Finite Difference ◽  
Time Domain ◽  
Ground Penetrating Radar ◽  
High Frequency ◽  
Electromagnetic Waves ◽  
Ground Surface ◽  
Propagation Path ◽  
Fdtd Simulation ◽  
Ground Penetrating ◽  
Dielectric Objects

Ground penetrating radar (GPR) is a very effective tool for detecting and identifying objects below the ground surface.  based on  the propagation and reflection of high-frequency electromagnetic waves. The GPR reflection can be affected by many things like the type of objects orientation, their shapes ..ect. The purpose of this paper is to  study by simulation the effect of objects orientation in two different mediums (dry and wet sand) on the GPR signal reflection using Reflexw software which is based on a numerical method known as finite difference in time domain (FDTD).  The simulations that have been realized included a conductor  and dielectric objects. The results obtained have led us to find that the propagation path, the reflection strength and the signal form change with the change of object orientation and nature. To confirm the validity of the results, we compared them with experimental results previously published by researchers under the same conditions.

WISDOM Antenna Pattern in the presence of Rover and Soil

2021 ◽  
Author(s):  
Wolf-Stefan Benedix ◽  
Dirk Plettemeier ◽  
Christoph Statz ◽  
Yun Lu ◽  
Ronny Hahnel ◽  
...  
Keyword(s):  
Pattern Matching ◽  
Ground Penetrating Radar ◽  
Electromagnetic Waves ◽  
Complete System ◽  
Near Field ◽  
System Model ◽  
Soil Types ◽  
Broadband Antenna ◽  
Shallow Subsurface ◽  
Ground Penetrating

<p>The WISDOM ground-penetrating radar aboard the 2022 ESA-Roscosmos Rosalind-Franklin ExoMars Rover will probe the shallow subsurface of Oxia Planum using electromagnetic waves. A dual-polarized broadband antenna assembly transmits the WISDOM signal into the Martian subsurface and receives the return signal. This antenna assembly has been extensively tested and characterized w.r.t. the most significant antenna parameters (gain, pattern, matching). However, during the design phase, these parameters were simulated or measured without the environment, i.e., in the absence of other objects like brackets, rover vehicle, or soil. Some measurements of the rover's influence on the WISDOM data were performed during the instrument's integration.</p><p>It was shown that the rover structure and close surroundings in the near-field region of the WISDOM antenna assembly have a significant impact on the WISDOM signal and sounding performance. Hence, it is essential to include the simulations' environment, especially with varying surface and underground.</p><p>With this contribution, we outline the influences of rover and ground on the antenna's pattern and particularly on the footprint. We employ a 3D field solver with a complete system model above different soil types, i.e., subsurface materials with various combinations of permittivity and conductivity.</p>

Ground‐penetrating radar velocity tomography in heterogeneous and anisotropic media

Geophysics ◽  
1997 ◽  
Vol 62 (6) ◽  
pp. 1758-1773 ◽  
Author(s):  
Don W. Vasco ◽  
John E. Peterson ◽  
Ki Ha Lee
Keyword(s):  
Ground Penetrating Radar ◽  
Electromagnetic Waves ◽  
Numerical Technique ◽  
Anisotropic Media ◽  
Perturbation Approach ◽  
Low Velocity ◽  
Weak Anisotropy ◽  
Geological Features ◽  
Velocity Anomalies ◽  
Ground Penetrating

A ray series solution for Maxwell's equations provides an efficient numerical technique for calculating wavefronts and raypaths associated with electromagnetic waves in anisotropic media. Using this methodology and assuming weak anisotropy, we show that a perturbation of the anisotropic structure may be related linearly to a variation in the traveltime of an electromagnetic wave. Thus, it is possible to infer lateral variations in the dielectric permittivity and magnetic permeability matrices. The perturbation approach is used to analyze a series of crosswell ground‐penetrating radar surveys conducted at the Idaho National Engineering Laboratory. Several important geological features are imaged, including a rubble zone at the interface between two basalt flows. Linear low‐velocity anomalies are imaged clearly and are continuous across well pairs.

Interpolating wide-aperture ground-penetrating radar beyond aliasing

Geophysics ◽  
2015 ◽  
Vol 80 (2) ◽  
pp. H13-H22 ◽  
Author(s):  
Saulo S. Martins ◽  
Jandyr M. Travassos
Keyword(s):  
Ground Penetrating Radar ◽  
Real Data ◽  
Velocity Model ◽  
Data Sets ◽  
Inversion Problem ◽  
Data Set ◽  
Isolated Points ◽  
Antarctic Continent ◽  
Ground Penetrating ◽  
The Antarctic

Most of the data acquisition in ground-penetrating radar is done along fixed-offset profiles, in which velocity is known only at isolated points in the survey area, at the locations of variable offset gathers such as a common midpoint. We have constructed sparse, heavily aliased, variable offset gathers from several fixed-offset, collinear, profiles. We interpolated those gathers to produce properly sampled counterparts, thus pushing data beyond aliasing. The interpolation methodology estimated nonstationary, adaptive, filter coefficients at all trace locations, including at the missing traces’ corresponding positions, filled with zeroed traces. This is followed by an inversion problem that uses the previously estimated filter coefficients to insert the new, interpolated, traces between the original ones. We extended this two-step strategy to data interpolation by employing a device in which we used filter coefficients from a denser variable offset gather to interpolate the missing traces on a few independently constructed gathers. We applied the methodology on synthetic and real data sets, the latter acquired in the interior of the Antarctic continent. The variable-offset interpolated data opened the door to prestack processing, making feasible the production of a prestack time migrated section and a 2D velocity model for the entire profile. Notwithstanding, we have used a data set obtained in Antarctica; there is no reason the same methodology could not be used somewhere else.

Crosshole reflection imaging with ground-penetrating radar data: Applications in near-surface sedimentary settings

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. H61-H69
Author(s):  
Niklas Allroggen ◽  
Stéphane Garambois ◽  
Guy Sénéchal ◽  
Dominique Rousset ◽  
Jens Tronicke
Keyword(s):  
Ground Penetrating Radar ◽  
Field Data ◽  
Electromagnetic Property ◽  
Velocity Model ◽  
Radar Data ◽  
Near Surface ◽  
Velocity Models ◽  
Reflection Image ◽  
Detailed Interpretation ◽  
Ground Penetrating

Crosshole ground-penetrating radar (GPR) is applied in areas that require a very detailed subsurface characterization. Analysis of such data typically relies on tomographic inversion approaches providing an image of subsurface parameters. We have developed an approach for processing the reflected energy in crosshole GPR data and applied it on GPR data acquired in different sedimentary settings. Our approach includes muting of the first arrivals, separating the up- and the downgoing wavefield components, and backpropagating the reflected energy by a generalized Kirchhoff migration scheme. We obtain a reflection image that contains information on the location of electromagnetic property contrasts, thus outlining subsurface architecture in the interborehole plane. In combination with velocity models derived from different tomographic approaches, these images allow for a more detailed interpretation of subsurface structures without the need to acquire additional field data. In particular, a combined interpretation of the reflection image and the tomographic velocity model improves the ability to locate layer boundaries and to distinguish different subsurface units. To support our interpretations of our field data examples, we compare our crosshole reflection results with independent information, including borehole logs and surface GPR data.

Kirchhoff migration for specifying velocity model in ground penetrating radar method

2012 ◽  
Author(s):  
Nguyen Thanh Van ◽  
Le Van Anh Cuong ◽  
Dang Hoai Trung ◽  
Vo Minh Triet ◽  
Huynh Kim Tuan ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Velocity Model ◽  
Kirchhoff Migration ◽  
Radar Method ◽  
Ground Penetrating

Seismic constant‐velocity remigration

Geophysics ◽  
1997 ◽  
Vol 62 (2) ◽  
pp. 589-597 ◽  
Author(s):  
Jörg Schleicher ◽  
Peter Hubral ◽  
German Höcht ◽  
Frank Liptow
Keyword(s):  
Constant Velocity ◽  
Wave Equations ◽  
Single Point ◽  
Velocity Model ◽  
Migration Velocity ◽  
Body Waves ◽  
Reflection Point ◽  
Ray Trajectories ◽  
Zero Offset ◽  
Migration Velocities

When a seismic common midpoint (CMP) stack or zero‐offset (ZO) section is depth or time migrated with different (constant) migration velocities, different reflector images of the subsurface are obtained. If the migration velocity is changed continuously, the (kinematically) migrated image of a single point on the reflector, constructed for one particular seismic ZO reflection signal, moves along a circle at depth, which we call the Thales circle. It degenerates to a vertical line for a nondipping event. For all other dips, the dislocation as a function of migration velocity depends on the reflector dip. In particular for reflectors with dips larger than 45°, the reflection point moves upward for increasing velocity. The corresponding curves in a Time‐migrated section are parabolas. These formulas will provide the seismic interpreter with a better understanding of where a reflector image might move when the velocity model is changed. Moreover, in that case, the reflector image as a whole behaves to some extent like an ensemble of body waves, which we therefore call remigration image waves. In the same way as physical waves propagate as a function of time, these image waves propagate as a function of migration velocity. Different migrated images can thus be considered as snapshots of image waves at different instants of migration velocity. By some simple plane‐wave considerations, image‐wave equations can be derived that describe the propagation of image waves as a function of the migration velocity. The Thales circles and parabolas then turn out to be the characteristics or ray trajectories for these image‐wave equations.

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