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• W2316966472 abstract "PreviousNext No AccessBeijing 2014 International Geophysical Conference & Exposition, Beijing, China, 21-24 April 2014Application of Pinciple Component Spectral Analysis (PCSA) on channel detectionAuthors: Yan GaohanYang WuyangWei XinjianYang QingWang EnliYan GaohanResearch Institute of Petroleum Exploration & Development-Northwest (NWGI), PetroChina, Lanzhou 730020, ChinaSearch for more papers by this author, Yang WuyangResearch Institute of Petroleum Exploration & Development-Northwest (NWGI), PetroChina, Lanzhou 730020, ChinaSearch for more papers by this author, Wei XinjianResearch Institute of Petroleum Exploration & Development-Northwest (NWGI), PetroChina, Lanzhou 730020, ChinaSearch for more papers by this author, Yang QingResearch Institute of Petroleum Exploration & Development-Northwest (NWGI), PetroChina, Lanzhou 730020, ChinaSearch for more papers by this author, and Wang EnliResearch Institute of Petroleum Exploration & Development-Northwest (NWGI), PetroChina, Lanzhou 730020, ChinaSearch for more papers by this authorhttps://doi.org/10.1190/IGCBeijing2014-215 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Spectral decomposition is a method applied in geophysical interpretation widely, which can reveal the lateral variation in thin bed and is effective in channel detection. Generally, dozens of single frequency volume data would be generated to analyze for one seismic volume. However, lots of redundancy exist among these single frequency data, which leads to the result that interpreters are usually hard to choose those correct frequencies to characterize the seismic data. Principle component analysis(PCA) was applied to those single frequency data, which is able to obtain the most important elements and structures from overabundance data, and figure out the simple structure hidden in the complicated data. The real seismic data test demonstrates the effectiveness of this method, which is able to depict the channel characteristics more delicately. Keywords: spectral, decomposition, attributesPermalink: https://doi.org/10.1190/IGCBeijing2014-215FiguresReferencesRelatedDetails Beijing 2014 International Geophysical Conference & Exposition, Beijing, China, 21-24 April 2014ISSN (online):2159-6832Copyright: 2014 Pages: 1360 publication data© 2014 Published in electronic format with permission by the Society of Exploration Geophysicists and Chinese Petroleum SocietyPublisher:Society of Exploration Geophysicists HistoryPublished: 24 Apr 2014 CITATION INFORMATION Yan Gaohan, Yang Wuyang, Wei Xinjian, Yang Qing, and Wang Enli, (2014), Application of Pinciple Component Spectral Analysis (PCSA) on channel detection, SEG Global Meeting Abstracts : 849-852. https://doi.org/10.1190/IGCBeijing2014-215 Plain-Language Summary KeywordsspectraldecompositionattributesPDF DownloadLoading ..." @default.
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• W2316966472 title "Application of Pinciple Component Spectral Analysis (PCSA) on channel detection" @default.
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