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The Research Of Methods For Well Logging Evaluation Of Complex Reservoir In Biyang Depression

Posted on:2011-08-07Degree:MasterType:Thesis
Country:ChinaCandidate:T Z LiFull Text:PDF
GTID:2120360308490562Subject:Earth Exploration and Information Technology
Abstract/Summary:PDF Full Text Request
Exploratory development for complex reservoir is difficult, the main points of evaluation are low resistivity and complex water system, so the research of well logging evaluation for low resistivity oil layer is the core. Low resistivity oil layer is also significant problem for the scientists of home and abroad at present, that is why we should do the research for evaluation and interpretation of low resistivity oil layer.In this paper, I have classified the factors of low resistivity reservoir in electric conduction. Analyse the factors of low resistivity in Wangji Oil Field, and test the factors of low resistivity reservoir in the grey correlation analysis.Utilize different interpretation model of saturation for different kinds of the type of low resistivity reservoir.Identify the low resistivity oil reservoir by the comprehensive method of connecting the grey correlation analysis and correlation analysis in the article.In Wangji Oil Field ,the models of fluid were expressed in web graph,then compute the grey degree in the weighted grey correlation analysis considering correlation analysis, the fluid potential of unknown reservoirs was identified in the light of maxmum subject degree.Identify the oil bed in vertical direction,and forecast the layer system in cross range for the comprehensive evaluation of complex water and oil bed.On the basic of the result of single layer, using the method of geologic correlation to assure the better layer system.In study field, the analysis result by using the above approach shows that the rate of identifying fluid is higher than other methods and generating good impact of application.
Keywords/Search Tags:complicate reservoir, the factors of low resistivity reservoir, grey correlation analysis, clustering analysis, comprehensive evaluation
PDF Full Text Request
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