• Title of article

    Estimating the initial pressure, permeability and skin factor of oil reservoirs using artificial neural networks

  • Author/Authors

    Farzin Jeirani، نويسنده , , Z. and Mohebbi، نويسنده , , A.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2006
  • Pages
    10
  • From page
    11
  • To page
    20
  • Abstract
    Artificial neural network, a biologically inspired computing method which has an ability to learn, self-adjust, and be trained, provides a powerful tool in solving pattern recognition problems. In this study, a new approach based on artificial neural networks (ANNs) has been designed to estimate the initial pressure, permeability and skin factor of oil reservoir using the pressure build up test data. Five sets of actual field data in conventional and dual porosity reservoirs have been used to test the results of the neural network. The results from the network are in good agreement with the results from Horner plot. Finally, it is shown that the application of artificial neural networks in a pressure build up test reduces the cost of the test and it is also a valuable tool for well testing.
  • Keywords
    Well test , Initial pressure , Permeability , Pressure build up test , Skin factor , Artificial neural networks
  • Journal title
    Journal of Petroleum Science and Engineering
  • Serial Year
    2006
  • Journal title
    Journal of Petroleum Science and Engineering
  • Record number

    2215381