This work explores the capability of both Type-1 and Type-2 Fuzzy Inference Systems as novel approaches for predicting carbonate lithofacies and permeability from Well Logs. As expected, these new computational intelligence approaches overcome the weaknesses of the standard neural networks limitations. In addition, we carried out a comparative study to compare their performances with those of the conventional artificial neural network models and other popular techniques. Empirical results show that the performance of T1

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