The application of Adaptive Neuro-Fuzzy Inference System in lithology identification

Abstract

Lithology identification is not only the key elements in reservoir evaluation and reservoir description, but also the very important foundation for obtaining reservoir parameters. Accurate results of lithology identification can provide reliable basis for the exploration of oil and gas, for more it has played an enormous role in searching oil and gas resources and evaluating the oil. Because of the heterogeneity of actual reservoir, the traditional lithology identification methods are difficult to express the true characteristics of the reservoir. Adaptive Neuro-Fuzzy Inference System has the characteristics of distributed processing, self-study, self-organization, highly nonlinear and fault tolerance capabilities, so it is a new effective lithology identification method that taking advantage of neural network to process logging information. Simulations show that it is a new effective lithology identification method that using neural networks to process logging data and identify lithology. This method has certain practical significance and good prospects in exploring and identifying the accuracy of oil and gas layers and the field of oil and gas resource development.