{"title":"Machine learning for classification of seismic data","authors":"S.I. Litvinov, P. Bekeshko, O. Adamovich","doi":"10.3997/2214-4609.202156018","DOIUrl":null,"url":null,"abstract":"Summary This paper discusses the possibility of using neural networks to classify seismic data in order to increase the efficiency of data processing, reduce the time for a geophysicist to perform routine tasks and have a positive impact on the economic efficiency of the project. The result of using deep learning for the classification of seismograms in the presence of non-stationary man-made noise in space is presented. The approach made it possible to achieve high classification accuracy. As a result of the work, an important conclusion was made about the possibility of using this approach to search for man-made noise in seismic records.","PeriodicalId":266953,"journal":{"name":"Data Science in Oil and Gas 2021","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data Science in Oil and Gas 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3997/2214-4609.202156018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Summary This paper discusses the possibility of using neural networks to classify seismic data in order to increase the efficiency of data processing, reduce the time for a geophysicist to perform routine tasks and have a positive impact on the economic efficiency of the project. The result of using deep learning for the classification of seismograms in the presence of non-stationary man-made noise in space is presented. The approach made it possible to achieve high classification accuracy. As a result of the work, an important conclusion was made about the possibility of using this approach to search for man-made noise in seismic records.