• DocumentCode
    3399423
  • Title

    A new method for detecting real-time geopressure from drilling-logging parameters

  • Author

    Li Gongquan ; Wang Zhizhan

  • Author_Institution
    Sch. of Geosci., Yangtze Univ., Jinzhou, China
  • fYear
    2011
  • fDate
    19-22 Aug. 2011
  • Firstpage
    2502
  • Lastpage
    2506
  • Abstract
    Real-Time detecting abnormal formation pressure can not only prevent the happening of drilling hazard, but also effective protect the pollution of reservoir. A detective model can be made from some drilling-logging parameters because these parameters collected by comprehensive logging instrument can indicate the abnormal pressure information existing in the formation. First, a PCA method is used to process six wells from Dongying Depression, China in order to reduce the cross-correlation among parameters and the count. Then a neural net model is trained by the result in the first step. Finally, thirty wells are detected by the model. The correspondence between real data and predicted results is about 84.6%.So this method can be used in the real case.
  • Keywords
    drilling (geotechnical); neural nets; principal component analysis; well logging; Dongying; PCA method; drilling hazard; drilling-logging parameters; neural net model; real-time geopressure detection; Artificial neural networks; Correlation; Hydrocarbons; Predictive models; Principal component analysis; Real time systems; Training; Abnormal formation pressure; Neural net; PCA; Real-Time detecting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on
  • Conference_Location
    Jilin
  • Print_ISBN
    978-1-61284-719-1
  • Type

    conf

  • DOI
    10.1109/MEC.2011.6026001
  • Filename
    6026001