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Prestack data enhancement with phase corrections in time‐frequency domain guided by local multidimensional stacking
ABSTRACT We present a new approach to enhancing weak prestack reflection signals without sacrificing higher frequencies. As a first step, we employ known multidimensional local stacking to obtain an approximate ‘model of the signal’. Guided by phase spectra from this model, we can detect very weak s...
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Published in: | Geophysical Prospecting 2020-07, Vol.68 (6), p.1811-1818 |
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container_title | Geophysical Prospecting |
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creator | Bakulin, Andrey Neklyudov, Dmitri Silvestrov, Ilya |
description | ABSTRACT
We present a new approach to enhancing weak prestack reflection signals without sacrificing higher frequencies. As a first step, we employ known multidimensional local stacking to obtain an approximate ‘model of the signal’. Guided by phase spectra from this model, we can detect very weak signals and make them visible and coherent by ‘repairing’ corrupted phase of original data. Both presented approaches – phase substitution and phase sign corrections – show good performance on complex synthetic and field data suffering from severe near‐surface scattering where conventional processing methods are rendered ineffective. The methods are mathematically formulated as a special case of time‐frequency masking (common in speech processing) combined with the signal model from local stacking. This powerful combination opens the avenue for a completely new family of approaches for multi‐channel seismic processing that can address seismic processing of land data with nodes and single sensors in the desert environment. |
doi_str_mv | 10.1111/1365-2478.12956 |
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We present a new approach to enhancing weak prestack reflection signals without sacrificing higher frequencies. As a first step, we employ known multidimensional local stacking to obtain an approximate ‘model of the signal’. Guided by phase spectra from this model, we can detect very weak signals and make them visible and coherent by ‘repairing’ corrupted phase of original data. Both presented approaches – phase substitution and phase sign corrections – show good performance on complex synthetic and field data suffering from severe near‐surface scattering where conventional processing methods are rendered ineffective. The methods are mathematically formulated as a special case of time‐frequency masking (common in speech processing) combined with the signal model from local stacking. This powerful combination opens the avenue for a completely new family of approaches for multi‐channel seismic processing that can address seismic processing of land data with nodes and single sensors in the desert environment.</description><identifier>ISSN: 0016-8025</identifier><identifier>EISSN: 1365-2478</identifier><identifier>DOI: 10.1111/1365-2478.12956</identifier><language>eng</language><publisher>Houten: Wiley Subscription Services, Inc</publisher><subject>Corrections ; Data ; Data processing ; Desert environments ; Masking ; Methods ; New family ; Noise ; Signal processing ; Signal reflection ; Speech processing ; Stacking</subject><ispartof>Geophysical Prospecting, 2020-07, Vol.68 (6), p.1811-1818</ispartof><rights>2020 European Association of Geoscientists & Engineers</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a3386-a829e6b37924da6aa9ff19307106632527da51d7c55a43e67f2820ab46a90b223</citedby><cites>FETCH-LOGICAL-a3386-a829e6b37924da6aa9ff19307106632527da51d7c55a43e67f2820ab46a90b223</cites><orcidid>0000-0002-0495-0156</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Bakulin, Andrey</creatorcontrib><creatorcontrib>Neklyudov, Dmitri</creatorcontrib><creatorcontrib>Silvestrov, Ilya</creatorcontrib><title>Prestack data enhancement with phase corrections in time‐frequency domain guided by local multidimensional stacking</title><title>Geophysical Prospecting</title><description>ABSTRACT
We present a new approach to enhancing weak prestack reflection signals without sacrificing higher frequencies. As a first step, we employ known multidimensional local stacking to obtain an approximate ‘model of the signal’. Guided by phase spectra from this model, we can detect very weak signals and make them visible and coherent by ‘repairing’ corrupted phase of original data. Both presented approaches – phase substitution and phase sign corrections – show good performance on complex synthetic and field data suffering from severe near‐surface scattering where conventional processing methods are rendered ineffective. The methods are mathematically formulated as a special case of time‐frequency masking (common in speech processing) combined with the signal model from local stacking. This powerful combination opens the avenue for a completely new family of approaches for multi‐channel seismic processing that can address seismic processing of land data with nodes and single sensors in the desert environment.</description><subject>Corrections</subject><subject>Data</subject><subject>Data processing</subject><subject>Desert environments</subject><subject>Masking</subject><subject>Methods</subject><subject>New family</subject><subject>Noise</subject><subject>Signal processing</subject><subject>Signal reflection</subject><subject>Speech processing</subject><subject>Stacking</subject><issn>0016-8025</issn><issn>1365-2478</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNqFkM1Kw0AUhQdRsFbXbgdcp52fzCRZStEqFBTR9XCTmbRT81NnJpTsfASf0ScxacWtd3Ph8J17Dweha0pmdJg55VJELE7SGWWZkCdo8qecogkhVEYpYeIcXXi_JYQTIeIJ6p6d8QGKd6whADbNBprC1KYJeG_DBu824A0uWudMEWzbeGwbHGxtvj-_Smc-OtMUPdZtDYO-7qw2Guc9rtoCKlx3VbB6gBs_WAfh8Mk260t0VkLlzdXvnqK3-7vXxUO0elo-Lm5XEXCeyghSlhmZ8yRjsQYJkJUlzThJKJGSM8ESDYLqpBACYm5kUrKUEchjCRnJGeNTdHO8u3PtENUHtW07NyTxisU0pkkqxEjNj1ThWu-dKdXO2RpcryhRY7dqbFKNTapDt4NDHB17W5n-P1wtn1-Ovh88-X2P</recordid><startdate>202007</startdate><enddate>202007</enddate><creator>Bakulin, Andrey</creator><creator>Neklyudov, Dmitri</creator><creator>Silvestrov, Ilya</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>F1W</scope><scope>FR3</scope><scope>H96</scope><scope>KR7</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0002-0495-0156</orcidid></search><sort><creationdate>202007</creationdate><title>Prestack data enhancement with phase corrections in time‐frequency domain guided by local multidimensional stacking</title><author>Bakulin, Andrey ; Neklyudov, Dmitri ; Silvestrov, Ilya</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a3386-a829e6b37924da6aa9ff19307106632527da51d7c55a43e67f2820ab46a90b223</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Corrections</topic><topic>Data</topic><topic>Data processing</topic><topic>Desert environments</topic><topic>Masking</topic><topic>Methods</topic><topic>New family</topic><topic>Noise</topic><topic>Signal processing</topic><topic>Signal reflection</topic><topic>Speech processing</topic><topic>Stacking</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bakulin, Andrey</creatorcontrib><creatorcontrib>Neklyudov, Dmitri</creatorcontrib><creatorcontrib>Silvestrov, Ilya</creatorcontrib><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Geophysical Prospecting</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bakulin, Andrey</au><au>Neklyudov, Dmitri</au><au>Silvestrov, Ilya</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prestack data enhancement with phase corrections in time‐frequency domain guided by local multidimensional stacking</atitle><jtitle>Geophysical Prospecting</jtitle><date>2020-07</date><risdate>2020</risdate><volume>68</volume><issue>6</issue><spage>1811</spage><epage>1818</epage><pages>1811-1818</pages><issn>0016-8025</issn><eissn>1365-2478</eissn><abstract>ABSTRACT
We present a new approach to enhancing weak prestack reflection signals without sacrificing higher frequencies. As a first step, we employ known multidimensional local stacking to obtain an approximate ‘model of the signal’. Guided by phase spectra from this model, we can detect very weak signals and make them visible and coherent by ‘repairing’ corrupted phase of original data. Both presented approaches – phase substitution and phase sign corrections – show good performance on complex synthetic and field data suffering from severe near‐surface scattering where conventional processing methods are rendered ineffective. The methods are mathematically formulated as a special case of time‐frequency masking (common in speech processing) combined with the signal model from local stacking. This powerful combination opens the avenue for a completely new family of approaches for multi‐channel seismic processing that can address seismic processing of land data with nodes and single sensors in the desert environment.</abstract><cop>Houten</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1111/1365-2478.12956</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-0495-0156</orcidid></addata></record> |
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subjects | Corrections Data Data processing Desert environments Masking Methods New family Noise Signal processing Signal reflection Speech processing Stacking |
title | Prestack data enhancement with phase corrections in time‐frequency domain guided by local multidimensional stacking |
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