Semiautomated suppression of above-surface diffractions in GPR data

Geophysics ◽  
2010 ◽  
Vol 75 (6) ◽  
pp. J43-J50 ◽  
Author(s):  
Stefan F. Carpentier ◽  
Heinrich Horstmeyer ◽  
Alan G. Green ◽  
Joseph Doetsch ◽  
Ilaria Coscia
Keyword(s):  
Ground Penetrating Radar ◽  
Synthetic Data ◽  
Complete Removal ◽  
Original Data ◽  
High Amplitude ◽  
Air Velocity ◽  
Efficient Suppression ◽  
Useful Signal ◽  
Multichannel Filtering ◽  
Ground Penetrating

Diffractions from above-surface objects can be a major problem in the processing and interpretation of ground-penetrating radar (GPR) data. Whereas methods to reduce random and many other types of source-generated noise are available, the efficient suppression of above-surface diffractions (ASDs) continues to be challenging. We have developed a scheme for semiautomatically detecting and suppressing ASDs. Initially, an accurate representation of ASDs is obtained by (1) Stolt [Formula: see text] migrating the GPR data using the air velocity to focus ASDs, (2) multichannel filtering to minimize other signals, (3) setting an amplitude threshold that targets the high-amplitude ASDs and effectively eliminates other signals, and (4) Stolt [Formula: see text] demigrating the ASDs using the air velocity, and remigrating them using the ground velocity. By excluding the obliquity correction in the Stolt algorithms and avoiding intermediate amplitude scaling, we preserve the ASDs’ amplitude and phase information. The final stepinvolves subtracting this image of ASDs from a standard migrated version of the original data. This scheme, which includes some important extensions to a previously proposed method, makes it possible to semiautomatically process large volumes of GPR data characterized by numerous highly clustered and overlapping ASDs. The user has control over the tradeoff between ASD suppression and undesired removal of useful signal. It achieves nearly complete removal of ASDs in synthetic data and significant suppression in field data. Once ASDs have been suppressed, their influence can be reduced further by applying relatively gentle multichannel filters. It is not possible to remove line diffractions that resemble subhorizontal reflections or retrieve subsurface signals from data saturated by ASDs, such that some blank regions may be left after applying the suppression scheme. Nevertheless, subsequent processing and interpretation of the GPR data benefit significantly from the suppression of ASDs, which otherwise would clutter the final images.

scholarly journals High-Resolution Coherency Functionals for Improving the Velocity Analysis of Ground-Penetrating Radar Data

2020 ◽  
Vol 12 (13) ◽  
pp. 2146
Author(s):  
Eusebio Stucchi ◽  
Adriano Ribolini ◽  
Andrea Tognarelli
Keyword(s):  
High Resolution ◽  
Velocity Field ◽  
Ground Penetrating Radar ◽  
Energy Content ◽  
Signal To Noise Ratio ◽  
Synthetic Data ◽  
Radar Data ◽  
Position Type ◽  
Reliable Interpretation ◽  
Ground Penetrating

We aim at verifying whether the use of high-resolution coherency functionals could improve the signal-to-noise ratio (S/N) of Ground-Penetrating Radar data by introducing a variable and precisely picked velocity field in the migration process. After carrying out tests on synthetic data to schematically simulate the problem, assessing the types of functionals most suitable for GPR data analysis, we estimated a varying velocity field relative to a real dataset. This dataset was acquired in an archaeological area where an excavation after a GPR survey made it possible to define the position, type, and composition of the detected targets. Two functionals, the Complex Matched Coherency Measure and the Complex Matched Analysis, turned out to be effective in computing coherency maps characterized by high-resolution and strong noise rejection, where velocity picking can be done with high precision. By using the 2D velocity field thus obtained, migration algorithms performed better than in the case of constant or 1D velocity field, with satisfactory collapsing of the diffracted events and moving of the reflected energy in the correct position. The varying velocity field was estimated on different lines and used to migrate all the GPR profiles composing the survey covering the entire archaeological area. The time slices built with the migrated profiles resulted in a higher S/N than those obtained from non-migrated or migrated at constant velocity GPR profiles. The improvements are inherent to the resolution, continuity, and energy content of linear reflective areas. On the basis of our experience, we can state that the use of high-resolution coherency functionals leads to migrated GPR profiles with a high-grade of hyperbolas focusing. These profiles favor better imaging of the targets of interest, thereby allowing for a more reliable interpretation.

Continuous and simultaneous measurement of reflector depth and average soil-water content with multichannel ground-penetrating radar

Geophysics ◽  
2008 ◽  
Vol 73 (4) ◽  
pp. J15-J23 ◽  
Author(s):  
Holger Gerhards ◽  
Ute Wollschläger ◽  
Qihao Yu ◽  
Philip Schiwek ◽  
Xicai Pan ◽  
...  
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Ground Penetrating Radar ◽  
Synthetic Data ◽  
Evaluation Procedure ◽  
Noninvasive Technique ◽  
Data Set ◽  
Large Variability ◽  
Ground Penetrating

Ground-penetrating radar is a fast noninvasive technique that can monitor subsurface structure and water-content distribution. To interpret traveltime information from single common-offset measurements, additional assumptions, such as constant permittivity, usually are required. We present a fast ground-penetrating-radar measurement technique using a multiple transmitter-and-receiver setup to measure simultaneously the reflector depth and average soil-water content. It can be considered a moving minicommon-midpoint measurement. For a simple analysis, we use a straightforward evaluation procedure that includes two traveltimes to the same reflector, obtained from different antenna separations. For a more accurate approach, an inverse evaluation procedure is added, using traveltimes obtained from all antenna separations at one position and its neighboring measurement locations. The evaluation of a synthetic data set with a lateral variability in reflector depth and an experimental example with a large variability in soil-water content are introduced to demonstrate the applicability for field-scale measurements. The crucial point for this application is the access to absolute traveltimes, which are difficult to determine accurately from common-offset measurements.

Synthesis of amplitude‐versus‐offset variations in ground‐penetrating radar data

Geophysics ◽  
2000 ◽  
Vol 65 (1) ◽  
pp. 113-125 ◽  
Author(s):  
Xiaoxian Zeng ◽  
George A. McMechan ◽  
Tong Xu
Keyword(s):  
Ground Penetrating Radar ◽  
Critical Incident ◽  
Incident Angle ◽  
High Amplitude ◽  
Radar Data ◽  
Electromagnetic Properties ◽  
Spectral Character ◽  
Amplitude Versus Offset ◽  
Ground Penetrating ◽  
Amplitude Versus

To evaluate the importance of amplitude‐versus‐offset information in the interpretation of ground‐penetrating radar (GPR) data, GPR reflections are synthesized as a function of antenna separation using a 2.5-D finite‐difference solution of Maxwell’s equations. The conductivity, the complex dielectric permittivity, and the complex magnetic permeability are varied systematically in nine suites of horizontally layered models. The source used is a horizontal transverse‐electric dipole situated at the air‐earth interface. Cole‐Cole relaxation mechanisms define the frequency dependence of the media. Reflection magnitudes and their variations with antenna separation differ substantially, depending on the contrast in electromagnetic properties that caused the reflection. The spectral character of the dielectric and magnetic relaxations produces only second‐order variations in reflection coefficients compared with those associated with contrasts in permittivity, conductivity, and permeability, so they may not be separable even when they are detected. In typical earth materials, attenuation of propagating GPR waves is influenced most strongly by conductivity, followed by dielectric relaxation, followed by magnetic relaxation. A pervasive feature of the simulated responses is a locally high amplitude associated with the critical incident angle at the air‐earth interface in the antenna radiation pattern. Full wavefield simulations of two field data sets from a fluvial/eolian environment are able to reproduce the main amplitude behaviors observed in the data.

scholarly journals Detection of Underground Anomalies Using Analysis of Ground Penetrating Radar Attribute

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Cuong Van Anh LE ◽  
Thuan Van NGUYEN
Keyword(s):  
Ground Penetrating Radar ◽  
Urban Areas ◽  
Geophysical Methods ◽  
Synthetic Data ◽  
Drainage System ◽  
Real Data ◽  
Building Structures ◽  
Water Drainage ◽  
Diffraction Curve ◽  
Ground Penetrating

Need of specifying underground construction works for supporting further tasks as maintenance, repairing, or setting up new underground structures. For these needs, ground penetrating radar, one of the efficient geophysical methods, can bring high-resolution and quick underground image revealing existence of both natural and artificial anomalies. Its fixed receiver-transmitter antennas setting as constant offset is commonly used in urban areas. Conventionally, hyperbolae events are crucial indicator for scattering objects as kinds of pipes, water drainage system, and concrete building structures as well as sink holes. Calculation of their depths and sizes requires migration analysis with the environment velocity. Migrated sections with different velocity show different chaos degrees of transformation from a hyperbola diffraction curve to its focused area. We have researched diagrams of different Ground Penetrating Radar attributes as energy, entropy, and varimax dependent on two variables, velocity and window zone covering diffraction events from a set of synthetic data and real data, in specifying the environment velocity. We have developed a novel technique for evaluation of the ground velocity and object’s size by combination of the new varimax diagram and the Kirchhoff migration method. The technique can define contribution of diffracted ground penetrating radar waves for building the diagram after removing the reflection contribution. The synthetic datasets consist of different random background noise levels and expressions of different-sized circular and rectangular pipes. The real data is measured for detecting two underground gas pipes in Ba Ria – Vung Tau province, Vietnam.

scholarly journals Ground Penetrating Radar digital imaging and modeling of microbialites from the Salitre Formation, Northeast Brazil

2018 ◽  
Vol 18 (2) ◽  
pp. 187-200 ◽  
Author(s):  
Rebeca Seabra de Lima ◽  
Washington Luiz Evangelista Teixeira ◽  
Filipe Ramos de Albuquerque ◽  
Francisco Pinheiro Lima-Filho
Keyword(s):  
Ground Penetrating Radar ◽  
High Amplitude ◽  
Oil Fields ◽  
Northeastern Brazil ◽  
Geometrical Characterization ◽  
Geophysical Imaging ◽  
Ground Penetrating ◽  
Low Amplitude ◽  
Seismic Scale

Thanks to the discovery of new giant oil fields in the South Hemisphere in the last decades, named Pre-salt, there has been a considerable interest in the geometrical and sedimentological characterization of microbial deposits, coquinas, and collapsed caves, which represent a considerable part of these reservoirs. It is known that exposures analogous to oil reservoirs are an important source of information at the sub-seismic scale, as this information is helpful in parametrizing and modeling reservoirs, especially microbial reservoirs. This scenario is more favorable when the Ground Penetrating Radar (GPR) method is used in analogous exposures located in arid regions with scarce or no soil, such as the Fazenda Arrecife, in the Chapada Diamantina (Salitre Formation), Northeastern Brazil. Although rarely mentioned in the literature on microbialite geophysical imaging, GPR has been used in microbial deposits associated with the Neoproterozoic storm deposits of the Salitre Formation. The results of 3D imaging of a microbial colony, using the 200 MHz antenna, with both conventional processing and processing using geophysical attributes, are presented in this study. The conventional processing produced a 3D digital model that allowed the geometrical characterization and parametrization of the imaged microbial colony. The use of four geophysical attributes yielded good results, establishing the contact between the microbial colony and tempestite deposits, and determining the internal geometry of microbial deposits. The processing with “instantaneous amplitude” and “Hilbert trace with energy” highlighted the contact between the microbialite colony (low amplitude) and tempestite deposits (high amplitude), whereas the processing with the “energy” attribute provided a better visualization of the internal lamination of columnar microbialites, result similar to that obtained in the processing with “Hilbert trace with similarity”. GPR obtained images of up to 10 m in depth, with excellent resolution for microbial deposits and tempestites associated with them. The processing using geophysical attributes achieved considerably better results when compared to conventional processing, allowing a better visualization of the internal and external geometry of the imaged colony.

Conditional stochastic inversion of common-offset GPR reflection data

Geophysics ◽  
2021 ◽  
pp. 1-49
Author(s):  
Zhiwei Xu ◽  
James Irving ◽  
Yu Liu ◽  
Zhu Peimin ◽  
Klaus Holliger
Keyword(s):  
Ground Penetrating Radar ◽  
Synthetic Data ◽  
Field Measurements ◽  
Data Set ◽  
Stochastic Inversion ◽  
Reflection Data ◽  
Inversion Procedure ◽  
Borehole Logs ◽  
Ground Penetrating ◽  
Porosity Measurements

We present a stochastic inversion procedure for common-offset ground-penetrating radar (GPR) reflection measurements. Stochastic realizations of subsurface properties that offer an acceptable fit to GPR data are generated via simulated annealing optimization. The realizations are conditioned to borehole porosity measurements available along the GPR profile, or equivalent measurements of another petrophysical property that can be related to the dielectric permittivity, as well as to geostatistical parameters derived from the borehole logs and the processed GPR image. Validation of our inversion procedure is performed on a pertinent synthetic data set and indicates that the proposed method is capable of reliably recovering strongly heterogeneous porosity structures associated with surficial alluvial aquifers. This finding is largely corroborated through application of the methodology to field measurements from the Boise Hydrogeophysical Research Site near Boise, Idaho, USA.

Time-domain inversion of GPR data containing attenuation due to conductive losses

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. K103-K109 ◽  
Author(s):  
Qingyun Di ◽  
Meigen Zhang ◽  
Maioyue Wang
Keyword(s):  
Time Domain ◽  
Ground Penetrating Radar ◽  
Seismic Data ◽  
Random Noise ◽  
Synthetic Data ◽  
The Time Domain ◽  
Ground Penetrating ◽  
Domain Inversion ◽  
Inversion Techniques ◽  
And Inversion

Many seismic data processing and inversion techniques have been applied to ground-penetrating radar (GPR) data without including the wave field attenuation caused by conductive ground. Neglecting this attenuation often reduces inversion resolution. This paper introduces a GPR inversion technique that accounts for the effects of attenuation. The inversion is formulated in the time domain with the synthetic GPR waveforms calculated by a finite-element method (FEM). The Jacobian matrix can be computed efficiently with the same FEM forward modeling procedure. Synthetic data tests show that the inversion can generate high-resolution subsurface velocity profiles even with data containing strong random noise. The inversion can resolve small objects not readily visible in the waveforms. Further, the inversion yields a dielectric constant that can help to determine the types of material filling underground cavities.

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