Deep Learning SEM Image Segmentation of Shale Pyrite and Environmental Indications:A Study of Luzhou Block,Sichuan Basin
Pyrite,a significant heavy mineral in shale,aids in the comprehension of shale depositional environments.Referencing the Wufeng-Long,subsection Formation of the Luzhou Block in Sichuan Basin,a network model for pyrite SEM image segmentation was established via core mineral experiments,SEM observations,network model refinement,and feature parameter analysis.The model assesses the sedimentary environment of the study block using pyrite framboid parameters.① Our findings indicated that enhancement of the UNet-Im model for pyrite framboid SEM images resulted in a segmentation precision of 0.863,demonstrating the effectiveness of the enhancement measures.② Pyrite content varied from 2.95％in the Long11～3 minor layer to 0.83％in the Wufeng Formation,with the Long41 minor layer at 2.03％.③ Pyrite depositional environments are deduced as deep-water sulfide environments,strong reducing environments,strong-weak reduction environments,and reductive-suboxidative environments based on pyrite framboid characteristics.This study accurately segmented pyrite SEM images to enhance the exploration and development of intelligence in this industry.
万方数据
维普
