Velocity variations and water content estimated from multi‐offset, ground‐penetrating radar

Geophysics ◽  
1996 ◽  
Vol 61 (3) ◽  
pp. 683-695 ◽  
Author(s):  
Robert J. Greaves ◽  
David P. Lesmes ◽  
Jung Mo Lee ◽  
M. Nafi Toksöz
Keyword(s):  
Water Content ◽  
Ground Penetrating Radar ◽  
Velocity Structure ◽  
Signal To Noise Ratio ◽  
Radar Data ◽  
Processing Technique ◽  
Subsurface Water ◽  
Velocity Analysis ◽  
Radar Velocity ◽  
Ground Penetrating

The common midpoint (CMP) processing technique has been shown to be effective in improving the results of ground‐penetrating radar (GPR) profiling. When radar data are collected with the CMP multioffset geometry, stacking increases the signal‐to‐noise ratio of subsurface radar reflections and results in an improved subsurface image. An important aspect of CMP processing is normal‐moveout velocity analysis. Our objectives are to show the effect of multiple velocity analyses on the stacked radar image and particularly, to demonstrate that this velocity information can also be used to determine subsurface water content. Most GPR surveys are very limited in spatial extent and assume that within the survey range, radar velocity structure in the shallow subsurface can be adequately approximated by a single velocity function in data processing. In this study, we show that variation in radar velocity can be quite significant and that the stacked profile improves as the number of velocity analysis locations is increased. Interval velocities can be calculated from the normal moveout velocities derived in the CMP velocity analysis. With some reasonable assumptions about subsurface conditions necessary for radar propagation, interval velocity can be converted to an estimate of volumetric water content. Therefore, by collecting GPR data in the multioffset CMP geometry, not only is the radar profile improved but it also allows for an interpretation of subsurface variation in water content. We show the application of these techniques to multioffset GPR data from the Chalk River test area operated by Atomic Energy of Canada Limited.

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.

scholarly journals Measuring vertical soil water content profiles by combining horizontal borehole and dispersive surface ground penetrating radar data

2020 ◽  
Vol 18 (3) ◽  
pp. 275-294
Author(s):  
Yi Yu ◽  
Anja Klotzsche ◽  
Lutz Weihermüller ◽  
Johan Alexander Huisman ◽  
Jan Vanderborght ◽  
...  
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Ground Penetrating Radar ◽  
Radar Data ◽  
Ground Penetrating

Ground Penetrating Radar for Water Content and Compaction Evaluation: A Laboratory Test on Construction Material

2020 ◽  
Vol 25 (2) ◽  
pp. 169-179
Author(s):  
Hashem Ranjy Roodposhti ◽  
Mohammad Kazem Hafizi ◽  
Mohammad Reza Soleymani Kermani
Keyword(s):  
Dielectric Constant ◽  
Water Content ◽  
Ground Penetrating Radar ◽  
Large Scale ◽  
Construction Material ◽  
Construction Materials ◽  
Dielectric Constants ◽  
Base Layer ◽  
Subsurface Water ◽  
Ground Penetrating

With the aid of ground penetrating radar (GPR), it is possible to evaluate physical properties of a constructed base layer in engineered structures (pavement, land consolidation projects, etc.) non-destructively, quickly, and accurately. High spatial variations of subsurface water content and deficient compaction can lead to unexpected damage and structural instability. In this research, we established a relationship between the dielectric constant, water content, and compaction, whereby, an interactive relationship between these parameters is presented. To achieve this, large-scale laboratory experiments were carried out on construction materials to simulate field conditions. According to USCS, the tested soil type was GW-GM (type E base layer according to Iran's highway specifications code). Furthermore, water content and compaction were changed between 4% -12.9% and 84.7% -94.9%, respectively. The travel-times in each test, including three profiles with more than 210 traces, are measured automatically. Additionally, the calculated dielectric constants were compared with the Topp and Roth equations. R-square and RMS error of the final interactive equation between dielectric constant and water content-compaction were 0.95 and 0.41, respectively. Moreover, the sensitivity analysis of the proposed interactive equation shows that changes in water content of soil have greater impact on dielectric constant than soil compaction changes. The data also indicate the importance of considering the compaction changes of soil to reduce the error in dielectric constant estimation.

Resolving Infiltration-Induced Water Content Profiles by Inversion of Dispersive Ground-Penetrating Radar Data

2017 ◽  
Vol 16 (10) ◽  
pp. vzj2017.02.0037 ◽  
Author(s):  
Adam R. Mangel ◽  
Stephen M.J. Moysey ◽  
Jan van der Kruk
Keyword(s):  
Water Content ◽  
Ground Penetrating Radar ◽  
Radar Data ◽  
Ground Penetrating

scholarly journals Englacial water distribution in a temperate glacier from surface and borehole radar velocity analysis

2000 ◽  
Vol 46 (154) ◽  
pp. 389-398 ◽  
Author(s):  
Tavi Murray ◽  
Graham W. Stuart ◽  
Matt Fry ◽  
Nicola H. Gamble ◽  
Mike D. Crabtree
Keyword(s):  
Water Content ◽  
Water Distribution ◽  
Velocity Model ◽  
Velocity Analysis ◽  
Glacier Surface ◽  
Seismic Surveys ◽  
Glacier Ice ◽  
Piezometric Surface ◽  
Radar Velocity ◽  
Ground Penetrating

AbstractWe have obtained common offset, common midpoint (CMP) and borehole vertical (VRP) ground-penetrating radar profiles close to the margin of Falljökull, a small, steep temperate valley glacier situated in southeast Iceland. Velocity analysis of CMP and VRP surveys provided a four-layered velocity model. This model was verified by comparison between the depths of englacial reflectors and water channels seen in borehole video, and from the depths of boreholes drilled to the bed. In the absence of sediment within the glacier ice, radar velocity is inversely proportional to water content. Using mixture models developed by Paren and Looyenga, the variation of water content with depth was determined from the radar velocity profile. At the glacier surface the calculated water content is 0.23–0.34% (velocity 0.166 m ns−1), which rises sharply to 3.0–4.1% (velocity 0.149 m ns−1) at 28 m depth, interpreted to be the level of the piezometric surface. Below the piezometric surface the water content drops slowly to 2.4–3.3% (velocity 0.152 m ns−1) until ∼102 m depth where it falls to 0.09–0.14% (velocity 0.167 m ns−1). The water content of the ice then remains low to the glacier bed at about 112 m. These results suggest storage of a substantial volume of water within the glacier ice, which has significant implications for glacier hydrology, ice rheology and interpretations of both radar and seismic surveys.

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