The Use of Soft Computing Techniques as Data Preprocessing and Postprocessing in Permeability Determination from Well Log Data

  • K. W. Wong
  • T. D. Gedeon
  • C. C. Fung
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 80)


The uses of soft computing techniques comprising artificial neural networks, fuzzy logic and genetic algorithms are emerging for the building of permeability interpretation models in well log data analysis. Regardless of which soft computing techniques are used, they rely on a set of core permeability data to give a better understanding of the formation. However, uncertainties and errors with the core permeability data may undetermined the accuracy of permeability determination. This paper examines the problems that could possibly appear in the core permeability data. In most cases, data preprocessing and postprocessing are required to ensure that the permeability determination is successful. In this paper, soft computing techniques that are mainly based on fuzzy and neural networks approaches are used to assist the preprocessing and postprocessing stages thereby improving the overall accuracy.


Artificial Neural Network Fuzzy Rule Hide Node Fuzzy Membership Core Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • K. W. Wong
    • 1
  • T. D. Gedeon
    • 1
  • C. C. Fung
    • 2
  1. 1.School of Information TechnologyMurdoch UniversityMurdochWestern Australia
  2. 2.School of Electrical and Computer EngineeringCurtin UniversityBentleyWestern Australia

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