Deep learning lunar penetrating radar inversion: An example from Chang’E-3

PreviousNext No AccessFirst International Meeting for Applied Geoscience & Energy Expanded AbstractsDeep learning lunar penetrating radar inversion: An example from Chang’E-3Authors: Zi Xian LeongTieyuan ZhuZi Xian LeongThe Pennsylvania State UniversitySearch for more papers by this author and Tieyuan ZhuThe Pennsylvania State UniversitySearch for more papers by this authorhttps://doi.org/10.1190/segam2021-3581586.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail AbstractThe Moon’s deeper subsurface layers beyond the regolith are not well-studied. Using data from Change’E-3 Yutu rover’s lunar penetrating radar (LPR), we invert for its subsurface dielectric permittivity (εr) model. We use convolutional neural network based deep learning architecture to train numerous εr profiles and their corresponding synthetic radargrams. The dielectric permittivity training dataset is designed to encapsulate all possible εr realizations that the lunar subsurface materials may have. We test our trained model on synthetic data, and on the Change’E-3 LPR data. We validate our predicted εr by comparing its forward data and the field data. Our interpretation suggests multiple layers in the upper 200 meters in the order of regolith, ejectas, Eratosthenian basaltic lava flows, paleoregolith, and lava flows from Imbrium period.Keywords: artificial intelligence, inversion, tomographyPermalink: https://doi.org/10.1190/segam2021-3581586.1FiguresReferencesRelatedDetails First International Meeting for Applied Geoscience & Energy Expanded AbstractsISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2021 Pages: 3561 publication data© 2021 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 01 Sep 2021 CITATION INFORMATION Zi Xian Leong and Tieyuan Zhu, (2021), "Deep learning lunar penetrating radar inversion: An example from Chang’E-3," SEG Technical Program Expanded Abstracts : 1379-1383. https://doi.org/10.1190/segam2021-3581586.1 Plain-Language Summary Keywordsartificial intelligenceinversiontomographyPDF DownloadLoading ...