Extrapolated supervirtual refraction interferometry
SUMMARY Accurate picking of head-wave arrival times is an important component of first-arrival traveltime tomography. Far-offset traces in particular have low signal-to-noise ratio (SNR), but picking on these traces is necessary in order to obtain velocity information at depth. Furthermore, there is...
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2021
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Online Access: | http://dx.doi.org/10.1093/gji/ggab283 http://academic.oup.com/gji/advance-article-pdf/doi/10.1093/gji/ggab283/39169621/ggab283.pdf http://academic.oup.com/gji/article-pdf/227/2/1439/39738886/ggab283.pdf |
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croxfordunivpr:10.1093/gji/ggab283 2024-05-12T08:08:57+00:00 Extrapolated supervirtual refraction interferometry Xu, Zhuo Zhang, Fengjiao Juhlin, Christopher Lund, Björn Ask, Maria Han, Liguo Swedish Research Council Kempe Foundations Svensk Kärnbränslehantering Uppsala Universitet National Natural Science Foundation of China 2021 http://dx.doi.org/10.1093/gji/ggab283 http://academic.oup.com/gji/advance-article-pdf/doi/10.1093/gji/ggab283/39169621/ggab283.pdf http://academic.oup.com/gji/article-pdf/227/2/1439/39738886/ggab283.pdf en eng Oxford University Press (OUP) https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model Geophysical Journal International volume 227, issue 2, page 1439-1463 ISSN 0956-540X 1365-246X Geochemistry and Petrology Geophysics journal-article 2021 croxfordunivpr https://doi.org/10.1093/gji/ggab283 2024-04-18T08:18:03Z SUMMARY Accurate picking of head-wave arrival times is an important component of first-arrival traveltime tomography. Far-offset traces in particular have low signal-to-noise ratio (SNR), but picking on these traces is necessary in order to obtain velocity information at depth. Furthermore, there is often an insufficient number of far-offset traces for obtaining reliable models at depth. We present here an extrapolation method for increasing the number of first arrivals beyond the maximum recorded offset, thereby extending the supervirtual refraction interferometry (SVI) method. We refer to the method as extrapolated SVI (ESVI). It is a novel attempt to extrapolate first arrivals using a fully data-driven method. We first test the methodology on synthetic data sets, and we then apply ESVI to two published real data sets over the Pärvie fault system in northern Sweden. These data sets were acquired along the same profile at different times with different acquisition parameters and noise levels. The results show that ESVI enhances the SNR of head waves when the noise level is high. That is the same as the conventional SVI. ESVI also increases the number of pickable first arrivals by extrapolating head waves past the original maximum offset of each shot. We also show that the significant increase in first-arrival traveltime picks is beneficial for improving resolution and penetration depth in the tomographic imaging and, consequently, better revealing the subsurface velocity distribution. The tomographic images show higher velocities in the hanging walls of the main Pärvie fault and another subsidiary fault, as interpreted relative to migrated images from previous seismic reflection processing. Article in Journal/Newspaper Northern Sweden Oxford University Press Geophysical Journal International 227 2 1439 1463 |
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Open Polar |
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Oxford University Press |
op_collection_id |
croxfordunivpr |
language |
English |
topic |
Geochemistry and Petrology Geophysics |
spellingShingle |
Geochemistry and Petrology Geophysics Xu, Zhuo Zhang, Fengjiao Juhlin, Christopher Lund, Björn Ask, Maria Han, Liguo Extrapolated supervirtual refraction interferometry |
topic_facet |
Geochemistry and Petrology Geophysics |
description |
SUMMARY Accurate picking of head-wave arrival times is an important component of first-arrival traveltime tomography. Far-offset traces in particular have low signal-to-noise ratio (SNR), but picking on these traces is necessary in order to obtain velocity information at depth. Furthermore, there is often an insufficient number of far-offset traces for obtaining reliable models at depth. We present here an extrapolation method for increasing the number of first arrivals beyond the maximum recorded offset, thereby extending the supervirtual refraction interferometry (SVI) method. We refer to the method as extrapolated SVI (ESVI). It is a novel attempt to extrapolate first arrivals using a fully data-driven method. We first test the methodology on synthetic data sets, and we then apply ESVI to two published real data sets over the Pärvie fault system in northern Sweden. These data sets were acquired along the same profile at different times with different acquisition parameters and noise levels. The results show that ESVI enhances the SNR of head waves when the noise level is high. That is the same as the conventional SVI. ESVI also increases the number of pickable first arrivals by extrapolating head waves past the original maximum offset of each shot. We also show that the significant increase in first-arrival traveltime picks is beneficial for improving resolution and penetration depth in the tomographic imaging and, consequently, better revealing the subsurface velocity distribution. The tomographic images show higher velocities in the hanging walls of the main Pärvie fault and another subsidiary fault, as interpreted relative to migrated images from previous seismic reflection processing. |
author2 |
Swedish Research Council Kempe Foundations Svensk Kärnbränslehantering Uppsala Universitet National Natural Science Foundation of China |
format |
Article in Journal/Newspaper |
author |
Xu, Zhuo Zhang, Fengjiao Juhlin, Christopher Lund, Björn Ask, Maria Han, Liguo |
author_facet |
Xu, Zhuo Zhang, Fengjiao Juhlin, Christopher Lund, Björn Ask, Maria Han, Liguo |
author_sort |
Xu, Zhuo |
title |
Extrapolated supervirtual refraction interferometry |
title_short |
Extrapolated supervirtual refraction interferometry |
title_full |
Extrapolated supervirtual refraction interferometry |
title_fullStr |
Extrapolated supervirtual refraction interferometry |
title_full_unstemmed |
Extrapolated supervirtual refraction interferometry |
title_sort |
extrapolated supervirtual refraction interferometry |
publisher |
Oxford University Press (OUP) |
publishDate |
2021 |
url |
http://dx.doi.org/10.1093/gji/ggab283 http://academic.oup.com/gji/advance-article-pdf/doi/10.1093/gji/ggab283/39169621/ggab283.pdf http://academic.oup.com/gji/article-pdf/227/2/1439/39738886/ggab283.pdf |
genre |
Northern Sweden |
genre_facet |
Northern Sweden |
op_source |
Geophysical Journal International volume 227, issue 2, page 1439-1463 ISSN 0956-540X 1365-246X |
op_rights |
https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model |
op_doi |
https://doi.org/10.1093/gji/ggab283 |
container_title |
Geophysical Journal International |
container_volume |
227 |
container_issue |
2 |
container_start_page |
1439 |
op_container_end_page |
1463 |
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1798852094470389760 |