Permeability Prediction in Petroleum Reservoir using a Hybrid System

  • Y. Huang
  • P. M. Wong
  • T. D. Gedeon
Conference paper


This paper introduces and demonstrates a hybrid soft computing system for predicting reservoir permeability of sedimentary rocks in drilled wells in the petroleum exploration and development industry. The method employs Takagi-Sugeno’s fuzzy reasoning, and its fuzzy rules and membership functions are automatically derived by neural networks and floating-point encoding genetic algorithms. The method is trained with known data and tested with unseen data. The results show that the hybrid system has a good generalisation capability and is effective for industrial applications.


Permeability Porosity Petroleum Hydrocarbon Sandstone 


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Copyright information

© Springer-Verlag London 2000

Authors and Affiliations

  • Y. Huang
    • 1
  • P. M. Wong
    • 2
  • T. D. Gedeon
    • 3
  1. 1.TechComm Simulation Pty LtdChippendaleAustralia
  2. 2.School of Petroleum EngineeringUniversity of New South WalesSydneyAustralia
  3. 3.School of Information TechnologyMurdoch UniversityMurdochAustralia

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