A new seismic attribute for ambiguity reduction in hydrocarbon prediction
ABSTRACT Hydrocarbon prediction from seismic amplitude and amplitude‐versus‐offset is a daunting task. Amplitude interpretation is ambiguous due to the effects of lithology and pore fluid. In this paper, we propose a new attribute “J” based on a Gassmann–Biot fluid substitution to reduce ambiguity....
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Veröffentlicht in: | Geophysical Prospecting 2017-01, Vol.65 (1), p.229-239 |
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description | ABSTRACT
Hydrocarbon prediction from seismic amplitude and amplitude‐versus‐offset is a daunting task. Amplitude interpretation is ambiguous due to the effects of lithology and pore fluid. In this paper, we propose a new attribute “J” based on a Gassmann–Biot fluid substitution to reduce ambiguity. Constrained by seismic and rock physics, the J attribute has good ability to detect hydrocarbons from seismic data. There are currently many attributes for hydrocarbon prediction. Among the existing attributes, far‐minus‐near times far and fluid factor are commonly used. In this paper, the effectiveness of these two existing attributes was compared with the new attribute. Numerical modelling was used to test the new attribute “J” and to compare “J” with the two existing attributes. The results showed that the J attribute can predict the existence of hydrocarbon in different porosity scenarios with less ambiguity than the other two attributes. Tests conducted with real seismic data demonstrated the effectiveness of the J attribute. The J attribute has performed well in scenarios in which the other two attributes gave inaccurate predictions. The proposed attribute “J” is fast and simple, and it could be used as a first step in hydrocarbon analysis for exploration. |
doi_str_mv | 10.1111/1365-2478.12367 |
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Hydrocarbon prediction from seismic amplitude and amplitude‐versus‐offset is a daunting task. Amplitude interpretation is ambiguous due to the effects of lithology and pore fluid. In this paper, we propose a new attribute “J” based on a Gassmann–Biot fluid substitution to reduce ambiguity. Constrained by seismic and rock physics, the J attribute has good ability to detect hydrocarbons from seismic data. There are currently many attributes for hydrocarbon prediction. Among the existing attributes, far‐minus‐near times far and fluid factor are commonly used. In this paper, the effectiveness of these two existing attributes was compared with the new attribute. Numerical modelling was used to test the new attribute “J” and to compare “J” with the two existing attributes. The results showed that the J attribute can predict the existence of hydrocarbon in different porosity scenarios with less ambiguity than the other two attributes. Tests conducted with real seismic data demonstrated the effectiveness of the J attribute. The J attribute has performed well in scenarios in which the other two attributes gave inaccurate predictions. The proposed attribute “J” is fast and simple, and it could be used as a first step in hydrocarbon analysis for exploration.</description><identifier>ISSN: 0016-8025</identifier><identifier>EISSN: 1365-2478</identifier><identifier>DOI: 10.1111/1365-2478.12367</identifier><identifier>CODEN: GPPRAR</identifier><language>eng</language><publisher>Houten: Wiley Subscription Services, Inc</publisher><subject>Ambiguity ; Amplitudes ; Attributes ; AVO ; Computational fluid dynamics ; Fluids ; Hydrocarbons ; Mathematical models ; Porosity ; Seismic studies</subject><ispartof>Geophysical Prospecting, 2017-01, Vol.65 (1), p.229-239</ispartof><rights>2016 European Association of Geoscientists & Engineers</rights><rights>2017 European Association of Geoscientists & Engineers</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a4047-46291ed7885705cd4659bda22bd04693ab82450ada2410b6fc4f076dda539a603</citedby><cites>FETCH-LOGICAL-a4047-46291ed7885705cd4659bda22bd04693ab82450ada2410b6fc4f076dda539a603</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2F1365-2478.12367$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2F1365-2478.12367$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1416,27923,27924,45573,45574</link.rule.ids></links><search><creatorcontrib>Liu, Changcheng</creatorcontrib><creatorcontrib>Ghosh, Deva</creatorcontrib><title>A new seismic attribute for ambiguity reduction in hydrocarbon prediction</title><title>Geophysical Prospecting</title><description>ABSTRACT
Hydrocarbon prediction from seismic amplitude and amplitude‐versus‐offset is a daunting task. Amplitude interpretation is ambiguous due to the effects of lithology and pore fluid. In this paper, we propose a new attribute “J” based on a Gassmann–Biot fluid substitution to reduce ambiguity. Constrained by seismic and rock physics, the J attribute has good ability to detect hydrocarbons from seismic data. There are currently many attributes for hydrocarbon prediction. Among the existing attributes, far‐minus‐near times far and fluid factor are commonly used. In this paper, the effectiveness of these two existing attributes was compared with the new attribute. Numerical modelling was used to test the new attribute “J” and to compare “J” with the two existing attributes. The results showed that the J attribute can predict the existence of hydrocarbon in different porosity scenarios with less ambiguity than the other two attributes. Tests conducted with real seismic data demonstrated the effectiveness of the J attribute. The J attribute has performed well in scenarios in which the other two attributes gave inaccurate predictions. The proposed attribute “J” is fast and simple, and it could be used as a first step in hydrocarbon analysis for exploration.</description><subject>Ambiguity</subject><subject>Amplitudes</subject><subject>Attributes</subject><subject>AVO</subject><subject>Computational fluid dynamics</subject><subject>Fluids</subject><subject>Hydrocarbons</subject><subject>Mathematical models</subject><subject>Porosity</subject><subject>Seismic studies</subject><issn>0016-8025</issn><issn>1365-2478</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNqNkU1LxDAQhoMouK6evQa8eOluvtMel0XXhQVF9BzSJtUs_ViTFum_N92KBy86l2Heed6BmQHgGqMFjrHEVPCEMJkuMKFCnoDZj3IKZghhkaSI8HNwEcIeIYo4ZzOwXcHGfsJgXahdAXXXeZf3nYVl66Guc_fWu26A3pq-6FzbQNfA98H4ttA-j-UhdtyxcwnOSl0Fe_Wd5-D1_u5l_ZDsHjfb9WqXaIaYTJggGbZGpimXiBeGCZ7lRhOSG8RERnWeEsaRjhLDKBdlwUokhTGa00wLROfgdpp78O1Hb0OnahcKW1W6sW0fFE7TuB3liP0D5RmTVJIRvfmF7tveN3GRkaIUU0qzSC0nqvBtCN6W6uBdrf2gMFLjF9R4czXeXB2_EB18cny6yg5_4Wrz9Dz5vgD0wYdu</recordid><startdate>201701</startdate><enddate>201701</enddate><creator>Liu, Changcheng</creator><creator>Ghosh, Deva</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></search><sort><creationdate>201701</creationdate><title>A new seismic attribute for ambiguity reduction in hydrocarbon prediction</title><author>Liu, Changcheng ; Ghosh, Deva</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a4047-46291ed7885705cd4659bda22bd04693ab82450ada2410b6fc4f076dda539a603</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Ambiguity</topic><topic>Amplitudes</topic><topic>Attributes</topic><topic>AVO</topic><topic>Computational fluid dynamics</topic><topic>Fluids</topic><topic>Hydrocarbons</topic><topic>Mathematical models</topic><topic>Porosity</topic><topic>Seismic studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Changcheng</creatorcontrib><creatorcontrib>Ghosh, Deva</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>Liu, Changcheng</au><au>Ghosh, Deva</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A new seismic attribute for ambiguity reduction in hydrocarbon prediction</atitle><jtitle>Geophysical Prospecting</jtitle><date>2017-01</date><risdate>2017</risdate><volume>65</volume><issue>1</issue><spage>229</spage><epage>239</epage><pages>229-239</pages><issn>0016-8025</issn><eissn>1365-2478</eissn><coden>GPPRAR</coden><abstract>ABSTRACT
Hydrocarbon prediction from seismic amplitude and amplitude‐versus‐offset is a daunting task. Amplitude interpretation is ambiguous due to the effects of lithology and pore fluid. In this paper, we propose a new attribute “J” based on a Gassmann–Biot fluid substitution to reduce ambiguity. Constrained by seismic and rock physics, the J attribute has good ability to detect hydrocarbons from seismic data. There are currently many attributes for hydrocarbon prediction. Among the existing attributes, far‐minus‐near times far and fluid factor are commonly used. In this paper, the effectiveness of these two existing attributes was compared with the new attribute. Numerical modelling was used to test the new attribute “J” and to compare “J” with the two existing attributes. The results showed that the J attribute can predict the existence of hydrocarbon in different porosity scenarios with less ambiguity than the other two attributes. Tests conducted with real seismic data demonstrated the effectiveness of the J attribute. The J attribute has performed well in scenarios in which the other two attributes gave inaccurate predictions. The proposed attribute “J” is fast and simple, and it could be used as a first step in hydrocarbon analysis for exploration.</abstract><cop>Houten</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1111/1365-2478.12367</doi><tpages>11</tpages></addata></record> |
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subjects | Ambiguity Amplitudes Attributes AVO Computational fluid dynamics Fluids Hydrocarbons Mathematical models Porosity Seismic studies |
title | A new seismic attribute for ambiguity reduction in hydrocarbon prediction |
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