Article(id=1242129955002319335, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242129934576058746, articleNumber=null, orderNo=null, doi=10.3981/j.issn.1000-7857.2013.h1.016, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1354032000000, receivedDateStr=2012-11-28, revisedDate=1355328000000, revisedDateStr=2012-12-13, acceptedDate=null, acceptedDateStr=null, onlineDate=1361980800000, onlineDateStr=2013-02-28, pubDate=1361980800000, pubDateStr=2013-02-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1361980800000, onlineIssueDateStr=2013-02-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774076458928, creator=sys-migrate, updateTime=1774076458928, updator=sys-migrate, issue=Issue{id=1242129934576058746, tenantId=1146029695717560320, journalId=1146031591421210625, year='2013', volume='31', issue='5-6', pageStart='3', pageEnd='96', issueExtLink='null', onlineDate='null', pubDate='1361980800000', pubDateStr='2013-02-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774076454059, creator='sys-migrate', updateTime=1774076454059, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=81, endPage=86, ext={EN=ArticleExt(id=1242129958928187913, articleId=1242129955002319335, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Design of Point by Point to Obtain the Rock Element and Its Application, columnId=1242116080374710456, journalTitle=Science & Technology Review, columnName=Articles, runingTitle=null, highlight=null, articleAbstract=The rock components are very important for the logging interpretation of complex lithology reservoir. In order to obtain the ratio of rock matrix components point by point quickly and accurately, a fuzzy clustering method was discussed by taking the Biyang dolostone reservoir as an example. First, logging parameters were processed by principal component analysis and the purpose is to reduce the number of dimensions. Samples were processed by routine standardization, mean processing standardization, and logarithmic transformation standardization. The cumulative variance contribution rates of the first three principal factors are 86.07%, 96.97%, 96.71%, respectively. Then the samples are clustered and the classification number of k-means clustering is discussed. Finally, the lithologic component is point by point and quantitatively obtained by using the idea of fuzzy mathematics and calculating the degree of membership. The results show that the method is effective and suitable for the analysis of a large number of well logging data. It is worth to point out that this method is also effective when the new materials of logging technique are lack of., authors=WANG Jingci^1,2, GUO Haimin^1,2, WANG Huawei³, authorsList=WANG Jingci;GUO Haimin;WANG Huawei, authorCompany=1. Key Laboratory of Exploration Technologies for Oil and Gas Resources, Ministry of Education, Yangtze University, Wuhan;430100, China;2. School of Geophysics and Oil Resources, Yangtze University, Wuhan 430100, China;3. Research Institute of Exploration and Development, Tarim Oilfield Company, PetroChina, Korla 841000, Xinjiang Uyghur Autonomous Region, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=eQCuFo00m4CLqw3zruUXAQ==, pdfFileSize=2691245, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242129957854446075, articleId=1242129955002319335, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=岩石组分逐点求取方法设计与应用, columnId=1146540929516700224, journalTitle=科技导报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=在进行较复杂岩性储层的测井评价时,岩石组分的逐点求取非常重要.为快捷而准确地逐点获取岩石组分信息,以泌阳凹陷白云岩储层为例,探讨了一种岩石组分逐点模糊聚类求取方法.首先,利用主成分分析对多种测井参数进行降维处理,其中对分析样本进行常规标准化、均值处理标准化、对数变换标准化后,前3个主因子的累计方差贡献率分别为86.07%、96.97%、96.71%.进而对降维后的分析样本进行聚类处理,并对k-均值聚类算法中类别数目的确定进行了探讨.最终,构建隶属度表达 式,利用模糊数学的思想,实现了利用常规测井资料的岩石组分逐点自动化定量求取.将计算结果与实验结论对比,表明该运算方法针对性强、限制条件少、效果良好.值得一提的是,该方法可在测井新技术资料缺乏的情况下使用., authors=王婧慈^1,2, 郭海敏^1,2, 王华伟³, authorsList=王婧慈;郭海敏;王华伟, authorCompany=1. 长江大学油气资源与勘探技术教育部重点实验室,武汉 430100;2. 长江大学地球物理与石油资源学院,武汉 430100;3. 中国石油塔里木油田分公司勘探开发研究院,新疆库尔勒 841000, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=rf8asUAJuM8JRQ9f4kevWg==, pdfFileSize=2691245, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null)}, 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