{"title":"Detecting Specifi c Facies in Well-Log Data Sets Using Knowledge-Driven Hierarchical Clustering","authors":"I. Emelyanova, J. Peyaud, T. Dance, M. Pervukhina","doi":"10.30632/pjv61n4-2020a4","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":49703,"journal":{"name":"Petrophysics","volume":"61 1","pages":"383-400"},"PeriodicalIF":0.7000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Petrophysics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.30632/pjv61n4-2020a4","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, PETROLEUM","Score":null,"Total":0}
期刊介绍:
Petrophysics contains original contributions on theoretical and applied aspects of formation evaluation, including both open hole and cased hole well logging, core analysis and formation testing.