scholarly journals The application of split step fourier migration to interpreting GPR data in Vietnam

2017 ◽  
Vol 17 (4B) ◽  
pp. 161-166
Author(s):  
Dang Hoai Trung ◽  
Nguyen Van Giang ◽  
Nguyen Thanh Van ◽  
Nguyen Van Thuan ◽  
Vo Minh Triet
Keyword(s):  
Ground Penetrating Radar ◽  
Field Data ◽  
Real Data ◽  
Radar Data ◽  
Electromagnetic Propagation ◽  
Energy Diagram ◽  
Subsurface Structures ◽  
Reliable Performance ◽  
Calculated Velocity ◽  
Ground Penetrating

Migration methods play an essential role in processing ground penetrating radar data. For estimating electromagnetic propagation velocity distribution, the finite - difference migration is used because of its reliable performance with high noise conditions. To optimize this migration algorithm, we propose using energy diagram as a criterion of looking for the correct velocity. If the velocity varies laterally and vertically, split step Fourier migration is used for creating a true image of subsurface structures. We applied these steps to real data in Vietnam. The results verified on field data show that migrated images with calculated velocity from energy diagram have the best quality.

scholarly journals The Application of Depth Migration for Processing GPR Data

2018 ◽  
Vol 35 ◽  
pp. 03004
Author(s):  
Dang Hoai Trung ◽  
Nguyen Van Giang ◽  
Nguyen Thanh Van
Keyword(s):  
Significant Role ◽  
Ground Penetrating Radar ◽  
Field Data ◽  
Velocity Model ◽  
Radar Data ◽  
Energy Diagram ◽  
Depth Migration ◽  
Subsurface Structures ◽  
Calculated Velocity ◽  
Ground Penetrating

Migration methods play a significant role in processing ground penetrating radar data. Beside recovering the true image of subsurface structures from the prior designed velocity model and the raw GPR data, the migration algorithm could be an effective tool in bulding real environmental velocity model. In this paper, we have proposed one technique using energy diagram extracted from migrated data as a criterion of looking for the correct velocity. Split Step Fourier migration, a depth migration, is chosen for facing the challenge where the velocity varies laterally and vertically. Some results verified on field data on Vietnam show that migrated sections with calculated velocity from energy diagram have the best quality.

scholarly journals Combination of Kirchhoff migration method and the energy diagram in the process of ground penetrating radar data

2015 ◽  
Vol 18 (4) ◽  
pp. 42-50
Author(s):  
Van Thanh Nguyen ◽  
Thuan Van Nguyen ◽  
Trung Hoai Dang
Keyword(s):  
Ground Penetrating Radar ◽  
High Reliability ◽  
Theoretical Models ◽  
Radar Data ◽  
Velocity Estimation ◽  
Energy Diagram ◽  
Subsurface Structures ◽  
Kirchhoff Migration ◽  
Migration Method ◽  
Ground Penetrating

Kirchhoff migration in ground penetrating radar (GPR) has been the technique of collapsing diffraction events on unmigrated records to points, thus moving reflection events to their proper locations and creating a true image of subsurface structures. Today, the scope of Kirchhoff migration has been broadened and is a tool for electromagnetic wave velocity estimation. To optimize this algorithm, we propose using the energy diagram as a criterion of looking for the correct propagation velocity. Using theoretical models, we demonstrated that the calculated velocities were the same as the root mean square ones up to the top of objects. The results verified on field data showed that improved sections could be obtained and the size as well as depth of anomalies were determined with high reliability.

scholarly journals Researching migration methods, entropy and energy diagram to process ground penetrating radar data

2017 ◽  
Vol 17 (4B) ◽  
pp. 167-174
Author(s):  
Van Nguyen Thanh ◽  
Thuan Van Nguyen ◽  
Trung Hoai Dang ◽  
Triet Minh Vo ◽  
Lieu Nguyen Nhu Vo
Keyword(s):  
Electromagnetic Wave ◽  
Wave Velocity ◽  
Ground Penetrating Radar ◽  
Radar Data ◽  
Maximum Energy ◽  
Velocity Estimation ◽  
Data Migration ◽  
Minimum Entropy ◽  
Energy Diagram ◽  
Ground Penetrating

Electromagnetic wave velocity is the most important parameter in processing ground penetrating radar data. Migration algorithm which heavily depends on wave velocity is used to concentrate scattered signals back to their correct locations. Depending wave velocity in urban area is not easy task by using traditional methods (i.e., common midpoint). We suggest using entropy and energy diagram as standard for achieving suitable velocity estimation. The results of one numerical model and areal data indicate that migrated section using accurate velocity has minimum entropy or maximum energy. From the interpretation, size and depth of anomalies are reliably identified.

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.

Reconstructing Properties of Subsurface from Ground-Penetrating Radar Data

PIERS Online ◽  
2006 ◽  
Vol 2 (6) ◽  
pp. 567-572
Author(s):  
Hui Zhou ◽  
Dongling Qiu ◽  
Takashi Takenaka
Keyword(s):  
Ground Penetrating Radar ◽  
Radar Data ◽  
Ground Penetrating

scholarly journals Ice thickness distribution of all Swiss glaciers based on extended ground-penetrating radar data and glaciological modeling

2021 ◽  
pp. 1-19
Author(s):  
Melchior Grab ◽  
Enrico Mattea ◽  
Andreas Bauder ◽  
Matthias Huss ◽  
Lasse Rabenstein ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Thickness Distribution ◽  
Radar Data ◽  
Tourism Industry ◽  
Swiss Alps ◽  
Ice Thickness ◽  
Hazard Management ◽  
Bed Topography ◽  
Ice Volume ◽  
Ground Penetrating

Abstract Accurate knowledge of the ice thickness distribution and glacier bed topography is essential for predicting dynamic glacier changes and the future developments of downstream hydrology, which are impacting the energy sector, tourism industry and natural hazard management. Using AIR-ETH, a new helicopter-borne ground-penetrating radar (GPR) platform, we measured the ice thickness of all large and most medium-sized glaciers in the Swiss Alps during the years 2016–20. Most of these had either never or only partially been surveyed before. With this new dataset, 251 glaciers – making up 81% of the glacierized area – are now covered by GPR surveys. For obtaining a comprehensive estimate of the overall glacier ice volume, ice thickness distribution and glacier bed topography, we combined this large amount of data with two independent modeling algorithms. This resulted in new maps of the glacier bed topography with unprecedented accuracy. The total glacier volume in the Swiss Alps was determined to be 58.7 ± 2.5 km3 in the year 2016. By projecting these results based on mass-balance data, we estimated a total ice volume of 52.9 ± 2.7 km3 for the year 2020. Data and modeling results are accessible in the form of the SwissGlacierThickness-R2020 data package.

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