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

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.