Ground-roll noise attenuation based on convolutional neural network

Abstract

PreviousNext No AccessSEG 2019 Workshop: Fractured Reservoir & Unconventional Resources Forum: Prospects and Challenges in the Era of Big Data, Lanzhou, China, 1–3 September 2019Ground-roll noise attenuation based on convolutional neural networkAuthors: Haishan Li*Dewu ChenDekuan ChangHaishan Li*RIPED–NWGI, PetroChinaSearch for more papers by this author, Dewu ChenRIPED–NWGI, PetroChinaSearch for more papers by this author, and Dekuan ChangRIPED–NWGI, PetroChinaSearch for more papers by this authorhttps://doi.org/10.1190/frur2019_18.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Convolutional neural networks, a kind of advance machine learning method, have gained a lot of interest in various fields in recent years. In this paper, convolutional neural network (CNN) is applied to suppress pre-stack seismic noise by learning the features of noise in seismic data automatically. First of all, a convolutional neural network (CNN) architecture for ground-roll noise attenuation is designed, then the network is trained by using the ground-roll noise as labels, and finally, the denoising network is applied to shot records. The feasibility and effectiveness of this method is demonstrated using synthetic and field experiments, and this approach is shown to be promising in suppressing ground-roll noise automatically with high computational efficiency. Keywords: attenuation, neural network, 2D, field experiments, noisePermalink: https://doi.org/10.1190/frur2019_18.1FiguresReferencesRelatedDetailsCited byMagnetotelluric data denoising method combining two deep-learning-based modelsJin Li, Yecheng Liu, Jingtian Tang, Yiqun Peng, Xian Zhang, and Yong Li4 January 2023 | GEOPHYSICS, Vol. 88, No. 1Magnetotelluric noise suppression via convolutional neural networkJin Li, Yecheng Liu, Jingtian Tang, and Fanhong Ma16 January 2023 | GEOPHYSICS, Vol. 88, No. 1 SEG 2019 Workshop: Fractured Reservoir & Unconventional Resources Forum: Prospects and Challenges in the Era of Big Data, Lanzhou, China, 1–3 September 2019ISSN (online):2159-6832Copyright: 2019 Pages: 120 publication data© 2019 Published in electronic format with permission by the Society of Exploration Geophysicists and the Research Institute of Petroleum & Development-Northwest (NWGI), PetroChinaPublisher:Society of Exploration Geophysicists HistoryPublished Online: 24 Dec 2019 CITATION INFORMATION Haishan Li*, Dewu Chen, and Dekuan Chang, (2019), "Ground-roll noise attenuation based on convolutional neural network," SEG Global Meeting Abstracts : 69-73. https://doi.org/10.1190/frur2019_18.1 Plain-Language Summary Keywordsattenuationneural network2Dfield experimentsnoisePDF DownloadLoading ...