Method of Identifying Total Sulfur Content in Coal: Geochemical and Geophysical Logging Data from the Upper Paleozoic in North China

Abstract

The research of sulfur content and logging parameters in coal seams is of great significance for accurate mining and efficient utilization of coal. Taking 81 coal samples collected from the Upper Paleozoic in North China as an example, coulometric titration and chemical reagent methods were used to determine the contents of total sulfur and morphological sulfur in coal seams, and correlation analysis and multivariate linear fitting methods were used to analyze the relationship between total sulfur in coal and the shape and peak value of logging curve. The results show that the content of total sulfur in the Upper Paleozoic coal seams ranges from 0.19% to 12.36%. The morphological sulfur in coal is mostly pyrite sulfur, followed by organic sulfur and sulfate sulfur. The logging curves of the deep lateral resistivity log (LLD), natural gamma ray (GR), short-distance gamma gamma (CGS), and spontaneous potential (SP) in coal seams from Shanxi Formation are funnel-shaped, tooth-shaped, box-shaped, and flat-shaped, respectively. The shapes of LLD corresponding to a few coal seams with a sulfur content of less than 3.0% are finger-shaped and bell-shaped, and GR is finger-shaped. The GR, CGS, acoustic (AC), and density (DEN) curves corresponding to Taiyuan Formation coal seams with a total sulfur content more than 3.0% (St,d≥ 3.0%) are mainly box-shaped, and the LLD curve corresponding to high-sulfur coal seams is mostly tooth-shaped. The LLD, GR, CGS, and AC curves are second only to funnel-shaped, and the DEN curve is tooth-shaped. The LLD, GR, AC, CGS, and DEN curves of coal seams with a total sulfur content less than 3.0% are mainly box-shaped. GR, AC, and DEN curves are next to tooth-shaped, LLD is bell-shaped, and CGS curve is finger-shaped. The total sulfur content in coal has a negative correlation with LLD and CGS values and a positive correlation with GR, AC, DEN,and SP values. The prediction model of total sulfur in coal is established by using a multivariate linear fitting method through geophysical logging parameter values, which can provide a method for comprehensively quantifying the change of total sulfur content in coal seams.