Automated reflection strength tracking for improved stratigraphic interpretation of GPR data sets

Abstract

PreviousNext No Access19th International Conference on Ground Penetrating RadarAutomated reflection strength tracking for improved stratigraphic interpretation of GPR data setsAuthors: Matteo DossiEmanuele ForteBarbara CosciottiSebastian Emanuel LauroElisabetta MatteiElena PettinelliMichele PipanMatteo DossiRoma Tre UniversitySearch for more papers by this author, Emanuele ForteUniversity of TriesteSearch for more papers by this author, Barbara CosciottiRoma Tre UniversitySearch for more papers by this author, Sebastian Emanuel LauroRoma Tre UniversitySearch for more papers by this author, Elisabetta MatteiRoma Tre UniversitySearch for more papers by this author, Elena PettinelliRoma Tre UniversitySearch for more papers by this author, and Michele PipanUniversity of TriesteSearch for more papers by this authorhttps://doi.org/10.1190/gpr2022-016.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract We developed an algorithm to automatically detect and track reflections within GPR data sets, based on their reflection strength. The procedure divides each GPR trace into a series of energy packets, each containing reflected, diffracted, interfering, or noise-related signals. Close packets in nearby traces are then connected, using the local reflection dips, to create a web covering the entire GPR profile. Through this web, the algorithm tracks, and marks as horizons, the main reflections, while redundant horizons and possible false positives are automatically removed. The procedure can be applied with just minimal signal processing, and requires only limited input from the interpreter. The algorithm was able to accurately track all the recorded reflections within GPR data sets acquired on coastal sand dunes, and to filter out deeper false positives. Keywords: reflection, GPR, amplitude, algorithm, filteringPermalink: https://doi.org/10.1190/gpr2022-016.1FiguresReferencesRelatedDetails 19th International Conference on Ground Penetrating RadarISSN (online):2159-6832Copyright: 2022 Pages: 166 publication data© 2022 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 13 Oct 2022 CITATION INFORMATION Matteo Dossi, Emanuele Forte, Barbara Cosciotti, Sebastian Emanuel Lauro, Elisabetta Mattei, Elena Pettinelli, and Michele Pipan, (2022), "Automated reflection strength tracking for improved stratigraphic interpretation of GPR data sets," SEG Global Meeting Abstracts : 123-126. https://doi.org/10.1190/gpr2022-016.1 Plain-Language Summary KeywordsreflectionGPRamplitudealgorithmfilteringPDF DownloadLoading ...