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A self-generating fuzzy rules inference system for petrophysical properties prediction
Conference paper   Open access

A self-generating fuzzy rules inference system for petrophysical properties prediction

C.C. Fung, K.W. Wong and P.M. Wong
1997 IEEE International Conference on Intelligent Processing Systems (Cat. No.97TH8335), Vol.1, pp.205-208
IEEE
Proceedings of the 1997 IEEE International Conference on Intelligent Processing Systems, ICIPS'97 (Beijing, China, 28/10/1997–31/10/1997)
1998
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Abstract

This paper discusses the application of a self-generating fuzzy rule extraction and inference system for the prediction of petrophysical properties from well log data. A set of core data with known characteristics is first selected as the training samples. Fuzzy rules are then extracted and undergo a process of rule elimination. The reduced rule set forms the rule-base of the fuzzy prediction model. This will be used to predict properties of other depths within or around the well. Results based on a test case for the prediction of porosity is reported and the performance of the system is discussed.

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