Predicting Petrophysical Parameters in a Fuzzy Environment

  • Jose Finol
  • X. D. Jing
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 80)


This paper concerns with the use of fuzzy models to predict petrophysical rock properties. Fuzzy models can approximate any continuous function with any degree of accuracy by covering its graph with a finite number of fuzzy patches. Every patch is identified with a fuzzy If-Then rule which describes a local input-output relationship between the variables of the model. A methodology to construct the fuzzy rules from a set of input-output data using fuzzy clustering algorithms is presented. The structure and parameters of the fuzzy model are extracted from the detected fuzzy partition. In order to demonstrate the effectiveness of the proposed fuzzy modeling method an application is presented using well log and core data from the Lake Maracaibo Basin.


Membership Function Fuzzy Rule Fuzzy Cluster Fuzzy Partition Fuzzy Cluster Algorithm 
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

  • Jose Finol
    • 1
  • X. D. Jing
    • 1
  1. 1.Centre for Petroleum StudiesT.H. Huxley School of Environment, Earth Sciences and EngineeringLondonUK

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