Seismic image denoising with convolutional neural network

Abstract

PreviousNext No AccessFirst International Meeting for Applied Geoscience & Energy Expanded AbstractsSeismic image denoising with convolutional neural networkAuthors: Elena KlochikhinaSean CrawleyNizar CheminguiElena KlochikhinaPGS, Sean CrawleyPGS, and Nizar CheminguiPGShttps://doi.org/10.1190/segam2021-3594920.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail AbstractSeismic images are often contaminated by migration noise. The noise attenuation process can take a lot of effort from the domain expert and, in many cases, it can be challenging to get the optimal result. In recent years it has been demonstrated that data-driven approaches can produce quality results with minimum effort. In digital image processing, convolutional neural networks (CNN) have gained a lot of popularity. When trained properly on carefully selected data, CNNs can potentially outperform traditional methods through task automation leading to reduced turnaround time of processing projects. In this work we propose to train a neural network, specifically a U-net architecture, to eliminate migration artifacts from seismic images. We explain the data preparation step and describe the model parameters and training process. Finally, we demonstrate the model performance on field data examples from three different geographical regions.Keywords: machine learning, imaging, noise, migration, filteringPermalink: https://doi.org/10.1190/segam2021-3594920.1FiguresReferencesRelatedDetails 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 Elena Klochikhina, Sean Crawley, and Nizar Chemingui, (2021), "Seismic image denoising with convolutional neural network," SEG Technical Program Expanded Abstracts : 2864-2868. https://doi.org/10.1190/segam2021-3594920.1 Plain-Language Summary Keywordsmachine learningimagingnoisemigrationfilteringPDF DownloadLoading ...