Processing GPR Surveys in Civil Engineering to Locate Buried Structures in Highly Conductive Subsoils
Many studies have illustrated the great benefit of ground-penetrating radar (GPR) in civil engineering. However, in some cases, this geophysical survey method does not produce the desired results due to the electromagnetic characteristics of the subsoil. This study presents the results obtained in t...
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MDPI AG
2023-08-01
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Online Access: | https://www.mdpi.com/2072-4292/15/16/4019 |
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author | Rosendo Mendoza Carlos Araque-Perez Bruna Marinho Javier Rey Mari Carmen Hidalgo |
author_facet | Rosendo Mendoza Carlos Araque-Perez Bruna Marinho Javier Rey Mari Carmen Hidalgo |
author_sort | Rosendo Mendoza |
collection | DOAJ |
description | Many studies have illustrated the great benefit of ground-penetrating radar (GPR) in civil engineering. However, in some cases, this geophysical survey method does not produce the desired results due to the electromagnetic characteristics of the subsoil. This study presents the results obtained in two locations near Linares (southern Spain), evaluating the detection of structures buried in conductive host materials (0.02 S/m in site 1 and 0.015 S/m in site 2) characterized by strong signal attenuation. Accounting for the study depth, which was 1.5 m, a 500 MHz shielded GPR antenna was used at both sites. At the first site, a controlled experiment was planned, and it consisted of burying three linear elements. An iron pipe, a PVC pipe, and a series of precast blocks were buried at a depth of 0.5 m in a subsoil composed of highly conductive clayey facies. To eliminate additional multiples caused by other superficial structures and increasing the high-frequency content, the predictive deconvolution flow was applied. In the 3D processing, the cover surfaces technique was used. Once the acquired GPR signals was analyzed and the optimal processing flow established, a second site in which different infrastructures in a conductive host medium formed by marly facies was explored. The 2D flow and 3D processing applied in this work allows to detect and see the continuity of some structures not visible for the default processing. |
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format | Article |
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institution | Directory Open Access Journal |
issn | 2072-4292 |
language | English |
last_indexed | 2024-03-10T23:36:46Z |
publishDate | 2023-08-01 |
publisher | MDPI AG |
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series | Remote Sensing |
spelling | doaj.art-884a671ebd504704b7c2b0ef81d52b5f2023-11-19T02:53:25ZengMDPI AGRemote Sensing2072-42922023-08-011516401910.3390/rs15164019Processing GPR Surveys in Civil Engineering to Locate Buried Structures in Highly Conductive SubsoilsRosendo Mendoza0Carlos Araque-Perez1Bruna Marinho2Javier Rey3Mari Carmen Hidalgo4Mechanical and Mining Engineering Department and CEACTEMA, Higher Polytechnic School of Linares, Technological Scientific Campus, University of Jaen, 23700 Linares, SpainAndalusian Institute of Geophysics, Campus de Cartuja, University of Granada, 18071 Granada, SpainGeology Department and CEACTEMA, Higher Polytechnic School of Linares, Technological Scientific Campus, University of Jaen, 23700 Linares, SpainGeology Department and CEACTEMA, Higher Polytechnic School of Linares, Technological Scientific Campus, University of Jaen, 23700 Linares, SpainGeology Department and CEACTEMA, Higher Polytechnic School of Linares, Technological Scientific Campus, University of Jaen, 23700 Linares, SpainMany studies have illustrated the great benefit of ground-penetrating radar (GPR) in civil engineering. However, in some cases, this geophysical survey method does not produce the desired results due to the electromagnetic characteristics of the subsoil. This study presents the results obtained in two locations near Linares (southern Spain), evaluating the detection of structures buried in conductive host materials (0.02 S/m in site 1 and 0.015 S/m in site 2) characterized by strong signal attenuation. Accounting for the study depth, which was 1.5 m, a 500 MHz shielded GPR antenna was used at both sites. At the first site, a controlled experiment was planned, and it consisted of burying three linear elements. An iron pipe, a PVC pipe, and a series of precast blocks were buried at a depth of 0.5 m in a subsoil composed of highly conductive clayey facies. To eliminate additional multiples caused by other superficial structures and increasing the high-frequency content, the predictive deconvolution flow was applied. In the 3D processing, the cover surfaces technique was used. Once the acquired GPR signals was analyzed and the optimal processing flow established, a second site in which different infrastructures in a conductive host medium formed by marly facies was explored. The 2D flow and 3D processing applied in this work allows to detect and see the continuity of some structures not visible for the default processing.https://www.mdpi.com/2072-4292/15/16/4019non-destructive surveyground-penetrating radarcivil-engineering applicationsGPR signal attenuation |
spellingShingle | Rosendo Mendoza Carlos Araque-Perez Bruna Marinho Javier Rey Mari Carmen Hidalgo Processing GPR Surveys in Civil Engineering to Locate Buried Structures in Highly Conductive Subsoils Remote Sensing non-destructive survey ground-penetrating radar civil-engineering applications GPR signal attenuation |
title | Processing GPR Surveys in Civil Engineering to Locate Buried Structures in Highly Conductive Subsoils |
title_full | Processing GPR Surveys in Civil Engineering to Locate Buried Structures in Highly Conductive Subsoils |
title_fullStr | Processing GPR Surveys in Civil Engineering to Locate Buried Structures in Highly Conductive Subsoils |
title_full_unstemmed | Processing GPR Surveys in Civil Engineering to Locate Buried Structures in Highly Conductive Subsoils |
title_short | Processing GPR Surveys in Civil Engineering to Locate Buried Structures in Highly Conductive Subsoils |
title_sort | processing gpr surveys in civil engineering to locate buried structures in highly conductive subsoils |
topic | non-destructive survey ground-penetrating radar civil-engineering applications GPR signal attenuation |
url | https://www.mdpi.com/2072-4292/15/16/4019 |
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