Conventional coal mine reserve estimation methods are misaligned with modern production. This study develops a lifecycle, production-oriented framework for dynamic reserve accounting, including a strip inversion algorithm for mined faces and an improved GIS grid method for unmined faces, and a classification-coding system for coal pillar resources in remaining spaces. A case study on the Huainan Zhujidong Mine verifies the framework: the inverse calculations for the mined-faces yield of extracted coal were 9.20–14.30% lower than those of traditional methods, aligning better with reality; unmined-face predictions achieved relative errors of 1.91% (reserves) and 2.99% (extraction); remaining-space pillar resources were inventoried into five categories and 13 blocks (8.873 Mt). The framework supports accurate reserve accounting and refined decision-making and can be applied to similar coal mines.
Lin et al. (Sat,) studied this question.
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