• DocumentCode
    249101
  • Title

    Estimation of petro-physical parameters based on interpolation between cross-sectional well logs

  • Author

    Hassan, Thomas ; Hassan, Bassem

  • Author_Institution
    GeoGraphix R&D, LMKR (Pvt.) Ltd., Islamabad, Pakistan
  • fYear
    2014
  • fDate
    19-20 Aug. 2014
  • Firstpage
    437
  • Lastpage
    441
  • Abstract
    This paper presents a quick, resource efficient and computer simulation based implementation for the estimation of petro-physical parameters between two nearby wells by using four interpolation algorithms i.e. Ordinary Kriging, Nearest Neighbor, Moving Average and Weighted Average on cross sectional well logs. Many researchers have presented their work on estimating formation parameters based on existing well logs using multilayer perceptron and radial basis function etc. But those estimated parameters are calculated from the existing logs of drilled formation. However we used interpolation algorithms between two well logs (in cross sectional view) to estimate new well log data in between wells and then formation parameters are determined using the estimated well log data. The results of all four algorithms are computed and compared with each other to find average estimation error for estimated formation parameters. This paper discusses an effective, less time consuming and resource efficient estimation of a formation logs to indicate a producible formation by calculating petro-physical parameters. This implementation was developed on Microsoft Visual Studio 2012 using C#.
  • Keywords
    radial basis function networks; well logging; C#; Microsoft Visual Studio 2012; average estimation error; computer simulation; cross-sectional well logs; drilled formation; formation logs; interpolation algorithms; moving average; multilayer perceptron; nearest neighbor; ordinary kriging; petrophysical parameters; radial basis function; resource efficient estimation; weighted average; well log data; Algorithm design and analysis; Artificial neural networks; Conductivity; Estimation error; Interpolation; Permeability; Microsoft Visual Studio 2012 and C#; Moving Average; Nearest Neighbor; Ordinary Kriging; Weighted Average Interpolation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networks & Soft Computing (ICNSC), 2014 First International Conference on
  • Conference_Location
    Guntur
  • Print_ISBN
    978-1-4799-3485-0
  • Type

    conf

  • DOI
    10.1109/CNSC.2014.6906651
  • Filename
    6906651