Estimating picking errors in near-surface seismic data to enable their time-lapse interpretation on hydrosystems
International audience Time‐lapse applications of seismic methods have been recently suggested at the near‐surface scale to track hydrological properties variations due to climate, water level changes or permafrost thaw for instance. But when it comes to traveltime tomography or surface‐wave dispers...
Published in: | Near Surface Geophysics |
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Main Authors: | , , , , , , |
Other Authors: | , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
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HAL CCSD
2018
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Online Access: | https://insu.hal.science/insu-01914586 https://doi.org/10.1002/nsg.12019 |
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ftinsu:oai:HAL:insu-01914586v1 |
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Open Polar |
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Institut national des sciences de l'Univers: HAL-INSU |
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ftinsu |
language |
English |
topic |
[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology |
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[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology Dangeard, Marine Bodet, L. Pasquet, S. Thiesson, J. Guerin, R. Jougnot, D. Longuevergne, Laurent Estimating picking errors in near-surface seismic data to enable their time-lapse interpretation on hydrosystems |
topic_facet |
[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology |
description |
International audience Time‐lapse applications of seismic methods have been recently suggested at the near‐surface scale to track hydrological properties variations due to climate, water level changes or permafrost thaw for instance. But when it comes to traveltime tomography or surface‐wave dispersion inversion, a careful estimation of the data variability associated to the picking process must be considered prior to any time‐lapse interpretation. In this study, we propose to estimate picking errors that are due to the inherent subjectivity of human operators using statistical analysis based on picking repeatability. Two seismic datasets were collected along the same profile under distinct hydrological conditions, across a granite‐micaschist contact at the Ploemeur hydrological observatory (France). Both datasets were recorded using identical equipment and acquisition parameters. A thorough statistical analysis is conducted to estimate picking uncertainties, at the 99 % confidence level, for both Pressure (P) wave first arrival time and surface‐wave phase velocity. With the suggested workflow, we are able to identify 33 % of the P‐wave traveltimes and 16 % of the surface‐wave dispersion data that can be considered significant enough for time‐lapse interpretations. In this selected portion of the data, point‐by‐point differences are highlighting important variations linked to different hydrogeological properties of the subsurface. These variations show strong contrasts with a non‐monotonous behaviour along the line, offering new insights to better constrain the dynamics of this hydrosystem. |
author2 |
Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS) École Pratique des Hautes Études (EPHE) Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) Institut de Physique du Globe de Paris (IPGP) Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université de La Réunion (UR)-Institut de Physique du Globe de Paris (IPG Paris)-Centre National de la Recherche Scientifique (CNRS) Géosciences Rennes (GR) Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS) ANR‐11‐EQPX‐0011, Agence Nationale de la Recherche ANR-11-EQPX-0011,CRITEX,Parc national d'équipements innovants pour l'étude spatiale et temporelle de la Zone Critique des Bassins Versants(2011) |
format |
Article in Journal/Newspaper |
author |
Dangeard, Marine Bodet, L. Pasquet, S. Thiesson, J. Guerin, R. Jougnot, D. Longuevergne, Laurent |
author_facet |
Dangeard, Marine Bodet, L. Pasquet, S. Thiesson, J. Guerin, R. Jougnot, D. Longuevergne, Laurent |
author_sort |
Dangeard, Marine |
title |
Estimating picking errors in near-surface seismic data to enable their time-lapse interpretation on hydrosystems |
title_short |
Estimating picking errors in near-surface seismic data to enable their time-lapse interpretation on hydrosystems |
title_full |
Estimating picking errors in near-surface seismic data to enable their time-lapse interpretation on hydrosystems |
title_fullStr |
Estimating picking errors in near-surface seismic data to enable their time-lapse interpretation on hydrosystems |
title_full_unstemmed |
Estimating picking errors in near-surface seismic data to enable their time-lapse interpretation on hydrosystems |
title_sort |
estimating picking errors in near-surface seismic data to enable their time-lapse interpretation on hydrosystems |
publisher |
HAL CCSD |
publishDate |
2018 |
url |
https://insu.hal.science/insu-01914586 https://doi.org/10.1002/nsg.12019 |
genre |
permafrost |
genre_facet |
permafrost |
op_source |
ISSN: 1569-4445 EISSN: 1873-0604 Near Surface Geophysics https://insu.hal.science/insu-01914586 Near Surface Geophysics, 2018, 16 (6), pp.613-625. ⟨10.1002/nsg.12019⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1002/nsg.12019 insu-01914586 https://insu.hal.science/insu-01914586 doi:10.1002/nsg.12019 |
op_doi |
https://doi.org/10.1002/nsg.12019 |
container_title |
Near Surface Geophysics |
container_volume |
16 |
container_issue |
6 |
container_start_page |
613 |
op_container_end_page |
625 |
_version_ |
1790606745824919552 |
spelling |
ftinsu:oai:HAL:insu-01914586v1 2024-02-11T10:07:54+01:00 Estimating picking errors in near-surface seismic data to enable their time-lapse interpretation on hydrosystems Dangeard, Marine Bodet, L. Pasquet, S. Thiesson, J. Guerin, R. Jougnot, D. Longuevergne, Laurent Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS) École Pratique des Hautes Études (EPHE) Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) Institut de Physique du Globe de Paris (IPGP) Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université de La Réunion (UR)-Institut de Physique du Globe de Paris (IPG Paris)-Centre National de la Recherche Scientifique (CNRS) Géosciences Rennes (GR) Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS) ANR‐11‐EQPX‐0011, Agence Nationale de la Recherche ANR-11-EQPX-0011,CRITEX,Parc national d'équipements innovants pour l'étude spatiale et temporelle de la Zone Critique des Bassins Versants(2011) 2018-11-13 https://insu.hal.science/insu-01914586 https://doi.org/10.1002/nsg.12019 en eng HAL CCSD European Association of Geoscientists and Engineers (EAGE) info:eu-repo/semantics/altIdentifier/doi/10.1002/nsg.12019 insu-01914586 https://insu.hal.science/insu-01914586 doi:10.1002/nsg.12019 ISSN: 1569-4445 EISSN: 1873-0604 Near Surface Geophysics https://insu.hal.science/insu-01914586 Near Surface Geophysics, 2018, 16 (6), pp.613-625. ⟨10.1002/nsg.12019⟩ [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology info:eu-repo/semantics/article Journal articles 2018 ftinsu https://doi.org/10.1002/nsg.12019 2024-01-24T17:36:49Z International audience Time‐lapse applications of seismic methods have been recently suggested at the near‐surface scale to track hydrological properties variations due to climate, water level changes or permafrost thaw for instance. But when it comes to traveltime tomography or surface‐wave dispersion inversion, a careful estimation of the data variability associated to the picking process must be considered prior to any time‐lapse interpretation. In this study, we propose to estimate picking errors that are due to the inherent subjectivity of human operators using statistical analysis based on picking repeatability. Two seismic datasets were collected along the same profile under distinct hydrological conditions, across a granite‐micaschist contact at the Ploemeur hydrological observatory (France). Both datasets were recorded using identical equipment and acquisition parameters. A thorough statistical analysis is conducted to estimate picking uncertainties, at the 99 % confidence level, for both Pressure (P) wave first arrival time and surface‐wave phase velocity. With the suggested workflow, we are able to identify 33 % of the P‐wave traveltimes and 16 % of the surface‐wave dispersion data that can be considered significant enough for time‐lapse interpretations. In this selected portion of the data, point‐by‐point differences are highlighting important variations linked to different hydrogeological properties of the subsurface. These variations show strong contrasts with a non‐monotonous behaviour along the line, offering new insights to better constrain the dynamics of this hydrosystem. Article in Journal/Newspaper permafrost Institut national des sciences de l'Univers: HAL-INSU Near Surface Geophysics 16 6 613 625 |