Evaluation of image comparison methods for complex textures

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2019Evaluation of image comparison methods for complex texturesAuthors: Rodrigo S. FerreiraJulia NoceMarco FerrazMatheus OliveiraEmilio Vita BrazilSérgio CersosimoRenato CerqueiraRodrigo S. FerreiraIBM ResearchSearch for more papers by this author, Julia NoceIBM ResearchSearch for more papers by this author, Marco FerrazGalpSearch for more papers by this author, Matheus OliveiraIBM ResearchSearch for more papers by this author, Emilio Vita BrazilIBM ResearchSearch for more papers by this author, Sérgio CersosimoGalpSearch for more papers by this author, and Renato CerqueiraIBM ResearchSearch for more papers by this authorhttps://doi.org/10.1190/segam2019-3216292.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail AbstractIn the O&G industry, interpreters may be assisted by image retrieval techniques when searching for relevant geological features in a seismic dataset, such as image patterns and structures. This can greatly accelerate the interpretation process by enabling the interpreter to relate the observed features with potential analogs from other interpretation projects. In this paper we evaluate the performance of different image comparison methods for seismic image retrieval. Most methodologies proposed in the literature assume that query and database images have comparable sizes. Our analysis includes methods that are able to compare images with arbitrarily different sizes which not only makes the retrieval application more general but also allows to answer queries not addressed by usual methods such as within, contains and resembles. The results in a public seismic dataset show a gain of up to 180% for [email protected] in comparison to traditional methods.Presentation Date: Wednesday, September 18, 2019Session Start Time: 1:50 PMPresentation Time: 3:55 PMLocation: Poster Station 3Presentation Type: PosterKeywords: machine learning, algorithm, interpretationPermalink: https://doi.org/10.1190/segam2019-3216292.1FiguresReferencesRelatedDetails SEG Technical Program Expanded Abstracts 2019ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2019 Pages: 5407 publication data© 2019 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 10 Aug 2019 CITATION INFORMATION Rodrigo S. Ferreira, Julia Noce, Marco Ferraz, Matheus Oliveira, Emilio Vita Brazil, Sérgio Cersosimo, and Renato Cerqueira, (2019), "Evaluation of image comparison methods for complex textures," SEG Technical Program Expanded Abstracts : 2639-2643. https://doi.org/10.1190/segam2019-3216292.1 Plain-Language Summary Keywordsmachine learningalgorithminterpretationPDF DownloadLoading ...