• DocumentCode
    2585735
  • Title

    Application of BP Neural Network in Oil Field Production Prediction

  • Author

    Sun, Lei ; Bi, Yange ; Lu, Guorong

  • Author_Institution
    Coll. of Geophys. & Inf. Eng., Univ. of Pet., Beijing, China
  • Volume
    1
  • fYear
    2010
  • fDate
    19-20 Dec. 2010
  • Firstpage
    201
  • Lastpage
    203
  • Abstract
    This paper introduces a new Neural Network model which is suitable for oil production prediction with training parameter set. From the comparison between prediction of oil production and real production, the precision of prediction meets the requirements quite well. In addition, this new model offers better self-adaptive ability and can be used in multi-cycle and multi-descending production forecast. In general, BP Neural Network is an ideal mean for oil production prediction.
  • Keywords
    backpropagation; neural nets; petroleum industry; production engineering computing; BP neural network; oil field production prediction; real production; self-adaptive ability; training parameter set; Artificial neural networks; Petroleum; Prediction algorithms; Predictive models; Production; Training; Transfer functions; Artificial Neural Network; BP Model; Oil Production Prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering (WCSE), 2010 Second World Congress on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9287-9
  • Type

    conf

  • DOI
    10.1109/WCSE.2010.101
  • Filename
    5718294
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2585735