• DocumentCode
    2282866
  • Title

    Data Mining for Seismic Exploration

  • Author

    Ouyang, Zhongbin ; He, Jing ; Zhang, Keliang

  • Author_Institution
    Res. Center on Fictitious Econ. & Data Sci., Chinese Acad. of Sci., Beijing
  • Volume
    3
  • fYear
    2008
  • fDate
    9-12 Dec. 2008
  • Firstpage
    424
  • Lastpage
    427
  • Abstract
    Seismic exploration plays an important role in petroleum industry. It is widely admitted that there are a lot of limitations of conventional data analysis ways in oil and gas industry. Traditional methods in petroleum engineering are knowledge-driven and often neglect some underlying factors. On the contrary, data mining is to deal with mass of data and never overlook any important phenomena. Due to large volumes of seismic data, we apply data mining to seismic exploration in this paper. K-means based Cluster analysis is applied for the 3-D seismic and well log data. Comparing the clustering results with the well log data, it is easy to display the distribution of lithology in geo-space.
  • Keywords
    data mining; petroleum industry; K-means; cluster analysis; data mining; petroleum engineering; petroleum industry; seismic exploration; Data analysis; Data mining; Data warehouses; Design optimization; Displays; Gas industry; Impedance; Intelligent agent; Knowledge engineering; Petroleum industry; cluster analysis; data mining; seismic exploration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    978-0-7695-3496-1
  • Type

    conf

  • DOI
    10.1109/WIIAT.2008.161
  • Filename
    4740813