• DocumentCode
    3449033
  • Title

    Predicating reservoir sensitivity rapidly with single-correlation analysis and multiple regression

  • Author

    Yuxue Sun ; Chang Xiao ; Yinsheng Lang

  • Author_Institution
    Northeast Pet. Univ., Daqing, China
  • Volume
    2
  • fYear
    2011
  • fDate
    20-22 Aug. 2011
  • Firstpage
    100
  • Lastpage
    104
  • Abstract
    Sensitivity analysis is the premise of studying reservoir-damage mechanism, meanwhile it is also extremely significant to optimize each work link during exploratory boring and development process, and to formulate systemic reservoir-protection technology solutions. After discussing various reservoir-sensitivity prediction methods developed in recent years, we have found that it´s an ideal, fast, new method to use single-correlation analysis and multiple regression to predicate reservoir sensitivity. On the basis of conventional core analysis and sensitive mineral analysis, we extract information relevant to every sensitivity, and use the new method above mentioned to predict reservoir-sensitivity, the accuracy of forecasting results can reach 85%, basically meet the needs of reservoir sensitivity predicted. Compared with single methods, the method combined single-correlation analysis and multiple regression is obviously improved when predicate reservoir sensitivity, and it is simple, widely applicable and with explicit physical significance.
  • Keywords
    boring; condition monitoring; hydrocarbon reservoirs; regression analysis; sensitivity analysis; conventional core analysis; exploratory boring; multiple regression; reservoir sensitivity; reservoir-damage mechanism; sensitive mineral analysis; sensitivity analysis; single-correlation analysis; systemic reservoir-protection technology; Correlation; Permeability; Predictive models; Regression analysis; Reservoirs; Sensitivity; core analysis; multiple regression; sensitive mineral; sensitivity analysis; single-correlation analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Artificial Intelligence Conference (ITAIC), 2011 6th IEEE Joint International
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-8622-9
  • Type

    conf

  • DOI
    10.1109/ITAIC.2011.6030286
  • Filename
    6030286