Takagi-Sugeno Integrated Fuzzy System in Subsurface Identification

This study investigates the possibility of using the rule-based fuzzy (FZ) inference method to analyse petrophysical data (DT). Some well logs (WL) DT provided by Shell Producing Development Company (SPDC), Nigeria, were utilised for this study. The exploration WL DT were clustered using an unsupervised neural network. The rule-based lithology (LTG) procedures were established from the training DT sets, and the procedure strength is weighted. The Takagi-Sugeno inference arrangement and the centroid of extent defuzzification technique were employed for the FZ inference. It was observed that FZ inference systems provide fast and comprehensive details of the LTG and fluid content of the subsurface structure of the petrophysical DT that was interpreted