Diving Wave Tomography: Velocity Modelling Using First Arrival Traveltime
In hydrocarbon exploration, information carried by diving waves and post-critical reflections that are used to reconstruct the long-to-intermediate wavelength of the subsurface is an integral part of successful velocity model building. Diving wave tomography (DWT) is one of the tools for shallow vel...
Gespeichert in:
Veröffentlicht in: | Buletin Persatuan Geologi Malaysia 2022-05, Vol.73 (1), p.13-22 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 22 |
---|---|
container_issue | 1 |
container_start_page | 13 |
container_title | Buletin Persatuan Geologi Malaysia |
container_volume | 73 |
creator | Abdul Basit, Amatul Syafi Md Arshad, Abdul Rahim Permalu, Arulini |
description | In hydrocarbon exploration, information carried by diving waves and post-critical reflections that are used to reconstruct the long-to-intermediate wavelength of the subsurface is an integral part of successful velocity model building. Diving wave tomography (DWT) is one of the tools for shallow velocity assessment particularly when seismic data has poor signal-to-noise ratio (SNR) with complex geologic settings where no clear reflector is present. Considering the relationship between velocity with time and space, the output from tomography plays a crucial role to align data between time and depth domain and produce a reliable image of the deeper structure where hydrocarbon reservoir is typically located. In geophysics, tomography is primarily used to correct seismic trace alignment to produce a reliable stack section. In advanced imaging it is used as an initial model for waveform inversion in an integrated workflow. In the post-processing stage, it is used to correct the misfit between well logs and seismic data and is crucial for the quantitative analysis of rock physics. In this paper, we focus on tomography and its working principle on near-surface velocity modelling. We restricted our workflow to 2D synthetic data simulating the shallow gas occurrence that is prominent in the offshore Malay Basin to demonstrate how tomography works in velocity reconstruction. Results from synthetic and real data example shows that DWT can recover local large-scale structure and improved stacked data, considering no other seismic data and constraint from well data is included in the iterative process. |
doi_str_mv | 10.7186/bgsm73202202 |
format | Article |
fullrecord | <record><control><sourceid>crossref</sourceid><recordid>TN_cdi_crossref_primary_10_7186_bgsm73202202</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>10_7186_bgsm73202202</sourcerecordid><originalsourceid>FETCH-LOGICAL-c1452-b2127f9d39af810a9c594146e2e86367c4f1c48ef55ea84d240a96bf7f6725433</originalsourceid><addsrcrecordid>eNpNkMFKxDAYhIMoWNa9-QB5AKvJnzRJvS2rqwsrXrrqraRpUiOtXZJS6NvbogdhmLl8M4dB6JqSW0mVuKua2EkGBGadoQQEkykl-cc5SggFkQqq5CVax_hFCAEpBXCaoP2DH_13g9_1aHHRd30T9Olzusdvtu2NHyb80te2bRfmGBff-RAHvAnBj7rFRZiL7eA7e4UunG6jXf_lCh13j8X2OT28Pu23m0NqKM8grYCCdHnNcu0UJTo3Wc4pFxasEkxIwx01XFmXZVYrXgOfGVE56YSEjDO2Qje_uyb0MQbrylPwnQ5TSUm5PFH-f4L9AEGRUPs</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Diving Wave Tomography: Velocity Modelling Using First Arrival Traveltime</title><source>DOAJ Directory of Open Access Journals</source><creator>Abdul Basit, Amatul Syafi ; Md Arshad, Abdul Rahim ; Permalu, Arulini</creator><creatorcontrib>Abdul Basit, Amatul Syafi ; Md Arshad, Abdul Rahim ; Permalu, Arulini ; Centre of Excellence in Seismic Imaging & Hydrocarbon Prediction (CSI), Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia ; Department of Geoscience, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia</creatorcontrib><description>In hydrocarbon exploration, information carried by diving waves and post-critical reflections that are used to reconstruct the long-to-intermediate wavelength of the subsurface is an integral part of successful velocity model building. Diving wave tomography (DWT) is one of the tools for shallow velocity assessment particularly when seismic data has poor signal-to-noise ratio (SNR) with complex geologic settings where no clear reflector is present. Considering the relationship between velocity with time and space, the output from tomography plays a crucial role to align data between time and depth domain and produce a reliable image of the deeper structure where hydrocarbon reservoir is typically located. In geophysics, tomography is primarily used to correct seismic trace alignment to produce a reliable stack section. In advanced imaging it is used as an initial model for waveform inversion in an integrated workflow. In the post-processing stage, it is used to correct the misfit between well logs and seismic data and is crucial for the quantitative analysis of rock physics. In this paper, we focus on tomography and its working principle on near-surface velocity modelling. We restricted our workflow to 2D synthetic data simulating the shallow gas occurrence that is prominent in the offshore Malay Basin to demonstrate how tomography works in velocity reconstruction. Results from synthetic and real data example shows that DWT can recover local large-scale structure and improved stacked data, considering no other seismic data and constraint from well data is included in the iterative process.</description><identifier>ISSN: 0126-6187</identifier><identifier>EISSN: 2637-109X</identifier><identifier>DOI: 10.7186/bgsm73202202</identifier><language>eng</language><ispartof>Buletin Persatuan Geologi Malaysia, 2022-05, Vol.73 (1), p.13-22</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,861,27905,27906</link.rule.ids></links><search><creatorcontrib>Abdul Basit, Amatul Syafi</creatorcontrib><creatorcontrib>Md Arshad, Abdul Rahim</creatorcontrib><creatorcontrib>Permalu, Arulini</creatorcontrib><creatorcontrib>Centre of Excellence in Seismic Imaging & Hydrocarbon Prediction (CSI), Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia</creatorcontrib><creatorcontrib>Department of Geoscience, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia</creatorcontrib><title>Diving Wave Tomography: Velocity Modelling Using First Arrival Traveltime</title><title>Buletin Persatuan Geologi Malaysia</title><description>In hydrocarbon exploration, information carried by diving waves and post-critical reflections that are used to reconstruct the long-to-intermediate wavelength of the subsurface is an integral part of successful velocity model building. Diving wave tomography (DWT) is one of the tools for shallow velocity assessment particularly when seismic data has poor signal-to-noise ratio (SNR) with complex geologic settings where no clear reflector is present. Considering the relationship between velocity with time and space, the output from tomography plays a crucial role to align data between time and depth domain and produce a reliable image of the deeper structure where hydrocarbon reservoir is typically located. In geophysics, tomography is primarily used to correct seismic trace alignment to produce a reliable stack section. In advanced imaging it is used as an initial model for waveform inversion in an integrated workflow. In the post-processing stage, it is used to correct the misfit between well logs and seismic data and is crucial for the quantitative analysis of rock physics. In this paper, we focus on tomography and its working principle on near-surface velocity modelling. We restricted our workflow to 2D synthetic data simulating the shallow gas occurrence that is prominent in the offshore Malay Basin to demonstrate how tomography works in velocity reconstruction. Results from synthetic and real data example shows that DWT can recover local large-scale structure and improved stacked data, considering no other seismic data and constraint from well data is included in the iterative process.</description><issn>0126-6187</issn><issn>2637-109X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNpNkMFKxDAYhIMoWNa9-QB5AKvJnzRJvS2rqwsrXrrqraRpUiOtXZJS6NvbogdhmLl8M4dB6JqSW0mVuKua2EkGBGadoQQEkykl-cc5SggFkQqq5CVax_hFCAEpBXCaoP2DH_13g9_1aHHRd30T9Olzusdvtu2NHyb80te2bRfmGBff-RAHvAnBj7rFRZiL7eA7e4UunG6jXf_lCh13j8X2OT28Pu23m0NqKM8grYCCdHnNcu0UJTo3Wc4pFxasEkxIwx01XFmXZVYrXgOfGVE56YSEjDO2Qje_uyb0MQbrylPwnQ5TSUm5PFH-f4L9AEGRUPs</recordid><startdate>20220531</startdate><enddate>20220531</enddate><creator>Abdul Basit, Amatul Syafi</creator><creator>Md Arshad, Abdul Rahim</creator><creator>Permalu, Arulini</creator><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20220531</creationdate><title>Diving Wave Tomography: Velocity Modelling Using First Arrival Traveltime</title><author>Abdul Basit, Amatul Syafi ; Md Arshad, Abdul Rahim ; Permalu, Arulini</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1452-b2127f9d39af810a9c594146e2e86367c4f1c48ef55ea84d240a96bf7f6725433</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Abdul Basit, Amatul Syafi</creatorcontrib><creatorcontrib>Md Arshad, Abdul Rahim</creatorcontrib><creatorcontrib>Permalu, Arulini</creatorcontrib><creatorcontrib>Centre of Excellence in Seismic Imaging & Hydrocarbon Prediction (CSI), Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia</creatorcontrib><creatorcontrib>Department of Geoscience, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia</creatorcontrib><collection>CrossRef</collection><jtitle>Buletin Persatuan Geologi Malaysia</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Abdul Basit, Amatul Syafi</au><au>Md Arshad, Abdul Rahim</au><au>Permalu, Arulini</au><aucorp>Centre of Excellence in Seismic Imaging & Hydrocarbon Prediction (CSI), Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia</aucorp><aucorp>Department of Geoscience, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Diving Wave Tomography: Velocity Modelling Using First Arrival Traveltime</atitle><jtitle>Buletin Persatuan Geologi Malaysia</jtitle><date>2022-05-31</date><risdate>2022</risdate><volume>73</volume><issue>1</issue><spage>13</spage><epage>22</epage><pages>13-22</pages><issn>0126-6187</issn><eissn>2637-109X</eissn><abstract>In hydrocarbon exploration, information carried by diving waves and post-critical reflections that are used to reconstruct the long-to-intermediate wavelength of the subsurface is an integral part of successful velocity model building. Diving wave tomography (DWT) is one of the tools for shallow velocity assessment particularly when seismic data has poor signal-to-noise ratio (SNR) with complex geologic settings where no clear reflector is present. Considering the relationship between velocity with time and space, the output from tomography plays a crucial role to align data between time and depth domain and produce a reliable image of the deeper structure where hydrocarbon reservoir is typically located. In geophysics, tomography is primarily used to correct seismic trace alignment to produce a reliable stack section. In advanced imaging it is used as an initial model for waveform inversion in an integrated workflow. In the post-processing stage, it is used to correct the misfit between well logs and seismic data and is crucial for the quantitative analysis of rock physics. In this paper, we focus on tomography and its working principle on near-surface velocity modelling. We restricted our workflow to 2D synthetic data simulating the shallow gas occurrence that is prominent in the offshore Malay Basin to demonstrate how tomography works in velocity reconstruction. Results from synthetic and real data example shows that DWT can recover local large-scale structure and improved stacked data, considering no other seismic data and constraint from well data is included in the iterative process.</abstract><doi>10.7186/bgsm73202202</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0126-6187 |
ispartof | Buletin Persatuan Geologi Malaysia, 2022-05, Vol.73 (1), p.13-22 |
issn | 0126-6187 2637-109X |
language | eng |
recordid | cdi_crossref_primary_10_7186_bgsm73202202 |
source | DOAJ Directory of Open Access Journals |
title | Diving Wave Tomography: Velocity Modelling Using First Arrival Traveltime |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T03%3A20%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Diving%20Wave%20Tomography:%20Velocity%20Modelling%20Using%20First%20Arrival%20Traveltime&rft.jtitle=Buletin%20Persatuan%20Geologi%20Malaysia&rft.au=Abdul%20Basit,%20Amatul%20Syafi&rft.aucorp=Centre%20of%20Excellence%20in%20Seismic%20Imaging%20&%20Hydrocarbon%20Prediction%20(CSI),%20Universiti%20Teknologi%20PETRONAS,%2032610%20Bandar%20Seri%20Iskandar,%20Perak,%20Malaysia&rft.date=2022-05-31&rft.volume=73&rft.issue=1&rft.spage=13&rft.epage=22&rft.pages=13-22&rft.issn=0126-6187&rft.eissn=2637-109X&rft_id=info:doi/10.7186/bgsm73202202&rft_dat=%3Ccrossref%3E10_7186_bgsm73202202%3C/crossref%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |