Coherence-based GPR diffraction imaging and inversion

In both seismic and electromagnetic imaging the diffracted wavefield has gained importance in recent years. While seismic data is often acquired for a large range of different source-receiver offsets, ground-penetrating radar (GPR) acquisitions are mostly (near-) zero-offset. This characteristic inh...

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Main Authors: Bauer, A., Schwarz, B., Gajewski, D.
Format: Conference Object
Language:English
Published: 2022
Subjects:
Online Access:https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012205
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spelling ftgfzpotsdam:oai:gfzpublic.gfz-potsdam.de:item_5012205 2023-05-15T16:20:44+02:00 Coherence-based GPR diffraction imaging and inversion Bauer, A. Schwarz, B. Gajewski, D. 2022 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012205 eng eng info:eu-repo/semantics/altIdentifier/doi/10.5194/egusphere-egu22-5953 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012205 Abstracts info:eu-repo/semantics/conferenceObject 2022 ftgfzpotsdam https://doi.org/10.5194/egusphere-egu22-5953 2022-09-14T05:58:15Z In both seismic and electromagnetic imaging the diffracted wavefield has gained importance in recent years. While seismic data is often acquired for a large range of different source-receiver offsets, ground-penetrating radar (GPR) acquisitions are mostly (near-) zero-offset. This characteristic inhibits the use of reflected waves for the estimation of depth velocities, which in turn increases the importance of a reliable imaging and characterization of the diffracted wavefield. In this study, we adapt a coherence-based workflow originally designed for seismic wavefields to ground-penetrating radar (GPR) data, which often exhibit similar wave propagation phenomena. The first step of the proposed workflow is the coherence-based imaging of the often predominant reflected wavefield, which in the second step is adaptively subtracted from the original data, resulting in an approximation of the diffracted wavefield. In the third step, we characterize the previously revealed diffracted wavefield by means of wavefront attributes, namely slopes and curvatures. In the fourth and final step, these wavefront attributes can be used for the estimation of depth velocities by means of wavefront tomography, an inversion scheme that provides both the localization of scatterers and a smooth velocity model of the subsurface. We demonstrate the wide applicability of the suggested workflow on two GPR field data examples provided by the USGS – one recorded in the aftermath of Hurricane Sandy on the shores of Long Beach Island, New Jersey, the other capturing the internal structure of Wolverine Glacier, Alaska. Conference Object glacier Alaska GFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam) Long Beach Beach Island ENVELOPE(-79.050,-79.050,57.500,57.500)
institution Open Polar
collection GFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam)
op_collection_id ftgfzpotsdam
language English
description In both seismic and electromagnetic imaging the diffracted wavefield has gained importance in recent years. While seismic data is often acquired for a large range of different source-receiver offsets, ground-penetrating radar (GPR) acquisitions are mostly (near-) zero-offset. This characteristic inhibits the use of reflected waves for the estimation of depth velocities, which in turn increases the importance of a reliable imaging and characterization of the diffracted wavefield. In this study, we adapt a coherence-based workflow originally designed for seismic wavefields to ground-penetrating radar (GPR) data, which often exhibit similar wave propagation phenomena. The first step of the proposed workflow is the coherence-based imaging of the often predominant reflected wavefield, which in the second step is adaptively subtracted from the original data, resulting in an approximation of the diffracted wavefield. In the third step, we characterize the previously revealed diffracted wavefield by means of wavefront attributes, namely slopes and curvatures. In the fourth and final step, these wavefront attributes can be used for the estimation of depth velocities by means of wavefront tomography, an inversion scheme that provides both the localization of scatterers and a smooth velocity model of the subsurface. We demonstrate the wide applicability of the suggested workflow on two GPR field data examples provided by the USGS – one recorded in the aftermath of Hurricane Sandy on the shores of Long Beach Island, New Jersey, the other capturing the internal structure of Wolverine Glacier, Alaska.
format Conference Object
author Bauer, A.
Schwarz, B.
Gajewski, D.
spellingShingle Bauer, A.
Schwarz, B.
Gajewski, D.
Coherence-based GPR diffraction imaging and inversion
author_facet Bauer, A.
Schwarz, B.
Gajewski, D.
author_sort Bauer, A.
title Coherence-based GPR diffraction imaging and inversion
title_short Coherence-based GPR diffraction imaging and inversion
title_full Coherence-based GPR diffraction imaging and inversion
title_fullStr Coherence-based GPR diffraction imaging and inversion
title_full_unstemmed Coherence-based GPR diffraction imaging and inversion
title_sort coherence-based gpr diffraction imaging and inversion
publishDate 2022
url https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012205
long_lat ENVELOPE(-79.050,-79.050,57.500,57.500)
geographic Long Beach
Beach Island
geographic_facet Long Beach
Beach Island
genre glacier
Alaska
genre_facet glacier
Alaska
op_source Abstracts
op_relation info:eu-repo/semantics/altIdentifier/doi/10.5194/egusphere-egu22-5953
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012205
op_doi https://doi.org/10.5194/egusphere-egu22-5953
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