• DocumentCode
    2313637
  • Title

    Application of artificial neural network to the research of formation damage

  • Author

    Sun, Yu-xue ; Long, An-Hou ; Peng, Jian-Wei

  • Author_Institution
    Daqing Pet. Inst., China
  • Volume
    6
  • fYear
    2004
  • fDate
    26-29 Aug. 2004
  • Firstpage
    3484
  • Abstract
    The application of artificial neural network to control formation damage is studied and corresponding models are constructed: backpropagation neural network and adaptive resonance theory neural network. The former is used to evaluate reservoir sensitivity and the latter to diagnose formation damage. During the application process of artificial neural network to control formation damage, the original data are converted to the data needed in decision-making and the experience of specialists is used in diagnosis and decision-making. This minimizes the influence of uncertain factors on the problem and enables the model to be advanced, predominant and adaptive. The corresponding software based on the research of application of artificial neural network is programmed and the verification of the models constructed shows satisfactory reliability.
  • Keywords
    ART neural nets; backpropagation; control engineering computing; decision making; process control; reservoirs; adaptive resonance theory; artificial neural network; backpropagation neural network; decision-making; formation damage control; formation damage diagnosis; reservoir sensitivity evaluation; Adaptive systems; Artificial neural networks; Decision making; Mathematical model; Neural networks; Neurons; Production systems; Reservoirs; Resonance; Sun;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
  • Print_ISBN
    0-7803-8403-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2004.1380391
  • Filename
    1380391