Abstract
Chapter 8 starts with a fuzzy logic overview and its applications in the oil and gas industry. In order to understand the concept of fuzzy set, classical set theory is explained by describing set, subset, set operations, and set properties. Then fuzzy sets are introduced by defining different membership functions and fuzzy set operations. Fuzzy interference system which includes fuzzification, fuzzy rules, fuzzy inference, and defuzzification is covered next with two different examples such as choke adjustment. In this example Python's skfuzzy toolbox is used to control choke size by considering different values of tubing head pressure, gas–oil ratio, and production rate. At the end of this chapter, fuzzy c-means clustering, an unsupervised learning method, is explained. Fuzzy c-means clustering is used for a porosity-permeability data set to determine different rock types.
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