Modeling the Porosity of the Carbonate Reservoir Using a Genetic Type-2 Fuzzy Logic System

This article proposes a genetic interval type-2 fuzzy logic system that uses the advantages of type-2 fuzzy sets to estimate the formation porosity of the reservoir using geophysical well logs. For structure identification, a fuzzy clustering algorithm is implemented to generate the rules and initial values automatically and for parameter adjustment the genetic algorithm is used. The proposed type-2 fuzzy logic system is then compared with another type-1 and type-2 fuzzy logic systems that use back-propagation optimization method. Simulation results show that better estimation can be obtained using proposed genetic type-2 fuzzy logic structure.