A Fuzzy Inference Algorithm for Lithology Analysis in Formation Evaluation
This paper presents a novel application of fuzzy logic in the interpretation of well logs, specifically, in determining the formation rock types in Petroleum Engineering. To solve this practical problem, a new inference algorithm is proposed. The interpretation of well logs is a decision-making problem where the issue is to utilize (and compromise) knowledge from human experts, evidence from well logs, and information from other sources. This research was motivated by the fact that fuzzy logic has proven to be highly effective in many applications involving uncertainties. Comparing with neural networks, this fuzzylogic-based method avoids the problems of training data collection, network training, and unavailability of rules or knowledge used in the interpretation. This results in an algorithm that is effective and inexpensive.
KeywordsFuzzy Logic Rock Type Membership Grade Formation Evaluation Training Data Collection
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