Coal Structure Prediction Based on Type-2 Fuzzy Inference System for Multi-Attribute Fusion: A Case Study in South Hengling Block, Qinshui Basin, China

The accurate prediction of coal structure is important to guide the exploration and development reservoirs. Most models are interpreted for a single sensitive seam, selection parameters correlated with structure, but they ignore interactions between different attributes. Part it introduces concept geological strength index (GSI) rocks in order achieve multi-element macroscopic description quantitative characterization structure; however, determination involves some uncertainties among properties coal, such as lithology, gas content tectonic fracture, due their complex nature. Fuzzy inference systems provide knowledge discovery process handle uncertainty. study shows that type-2 fuzzy system (T2-FIS) multi-attribute fusion used effectively fuse pre-stack post-stack seismic inversion reservoir azimuthal attribute produce more results Hengling block Shanxi area. set rules generated this paper can reliable GSI system. proposed has been tested on various datasets show capable providing high-quality predictions.