Fuzzy logic-driven and SVM-driven hybrid computational intelligence models applied to oil and gas reservoir characterization

► Demonstrates the capabilities of two hybrid models in the prediction of porosity and permeability of petroleum reservoirs. ► Hybrid modeling based on the combination of Functional Networks, Type-2 Fuzzy Logic System, and Support Vector Machines. ► No single technique is perfect in all situations, hence the need to combine the best traits of each technique in a hybrid. ► The hybrid models performed better than the individual techniques when used alone for the same sets of data. ► This work has demonstrated a successful application of hybridization in a real-life petroleum engineering problem.