• DocumentCode
    495091
  • Title

    Data Mining of Oil Productive Index with Artificial Neural Network

  • Author

    He, X. ; Liu, J.J.

  • Author_Institution
    Civil Eng. Dept., Wuhan Polytech. Univ., Wuhan, China
  • Volume
    2
  • fYear
    2009
  • fDate
    21-22 May 2009
  • Firstpage
    265
  • Lastpage
    268
  • Abstract
    Levenberg-Marquardt (shorted as L-M) algorithm is improved and adopted to train the neural network. The improved training algorithm leads to better convergence, faster convergent speed and higher precision. The proposed L-M neural network is used for geological data mining of oil productive index basing on the geological database. The process of geological spatial data mining and the geological knowledge discovering with L-M neural network are discussed. As an engineering case, data mining and knowledge discovering of the oil productive index basing on the reservoir property stored in the geological database are presented to explain the method proposed.
  • Keywords
    data mining; geology; geophysics computing; hydrocarbon reservoirs; learning (artificial intelligence); neural nets; petroleum industry; L-M neural network; Levenberg-Marquardt algorithm; artificial neural network; geological data mining; geological database; geological knowledge discovering; geological spatial data mining; oil productive index; reservoir property; training algorithm; Artificial neural networks; Convergence; Data engineering; Data mining; Geology; Indexes; Knowledge engineering; Neural networks; Petroleum; Spatial databases; Levenberg-Marquardt algorithm; artificial neural network; data mining; knowledge discover; oil productive index;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Computing Science, 2009. ICIC '09. Second International Conference on
  • Conference_Location
    Manchester
  • Print_ISBN
    978-0-7695-3634-7
  • Type

    conf

  • DOI
    10.1109/ICIC.2009.178
  • Filename
    5169062