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Research On The Low-permeability Reservoir Log-interpretation In Wa6 Block Of Wazhuang Oil Field

Posted on:2012-04-28Degree:MasterType:Thesis
Country:ChinaCandidate:L QianFull Text:PDF
GTID:2120330338493492Subject:Mineral prospecting and exploration
Abstract/Summary:PDF Full Text Request
The Wa6 fault block in WaZhuang oil field located in the north slope of GaoYou depression is a low-permeability reservoir. The main oil bearing series are E1f1 and K2t1 formation. Because of the bad physical properties, the reservoir is serious heterogeneity. The normal log-interpretation can not describe the reservoir parameter accurately. Aiming at this situation, the date mining technology is applied to log-interpretation. Obviously, it is more suitable.Based on information of the structure, sedimentary and diagenesis in the study area, the log-interpretation is carried out. In order to improve the logging date's quality, it must be pretreated. The wavelet transform is used, not only to denoise, but also to improve the resolution of well log. The standardization of trend surface avoids the graduation error. It is impossible for the histogram and cross-plot to show multi-dimensional information, while the parallel plot and Scatter matrix can. The two graphs are used to analyze the reservoir four-properties relation. Combined with the cluster analysis and classification date mining, the variation of lithology is studied. The models of reservoir physical properties are built with the stepwise regression. Through model diagnose, with the methods of standard error and residual analysis, the models are credible. According to comprehensive analysis, the standard of effective thickness is determined.On the basis of log-interpretation, the reservoir heterogeneity is quantitative characterization. To overcome the defects of permeability variation coefficient, permeability mutation coefficient and permeability range, the Lorenz curve and Gini coefficient are introduced to quantitative characterize the reservoir heterogeneity.
Keywords/Search Tags:log-interpretation, date mining, visualization
PDF Full Text Request
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