Selecting favorable post-mining goaf blocks is an important step in planning surface gas drainage. In this study, a productivity-based relative optimization index was constructed for block-scale screening. The conventional CBM–well productivity relationship was used only as a conceptual reference for organizing the selected evaluation factors. Gas abundance, goaf permeability, and gas pressure were used as the principal screening variables, while water accumulation and seam dip were incorporated as goaf-specific correction factors. Methods for determining the evaluation parameters were established based on mining-induced strata movement, the O-ring theory, gas migration characteristics, and field hydrogeological data. The method was applied to 23 goaf blocks in the No. 10, No. 12, and No. 8 Mines in the eastern Pingdingshan mining area. Sensitivity analysis showed that the elasticities of the optimization index with respect to gas abundance, permeability, and gas pressure were all equal to 1, whereas the effects of water accumulation and seam dip depended on their block-specific values. When the two correction factors were removed, the recalculated and original indices remained strongly correlated (Spearman’s ρ = 0.989, p < 0.001, n = 23), indicating that the correction factors modified the index values and the relative positions of some blocks but did not substantially alter the overall ranking for the present dataset. Using the adopted natural break classification, the 23 blocks were divided into seven Class I favorable blocks, seven Class II potential blocks, and nine Class III relatively unfavorable blocks. Several Class I blocks were located in the central–northern part of the No. 10 Mine. The SKCK-02 surface gas drainage well, located in a Class I block of the No. 10 Mine, is presented as an illustrative field application. It produced 2.40 × 106 m3 of cumulative pure gas over 945 days. Its production record is consistent with the screening result for this block but does not validate the three-class classification. The proposed method provides a relative screening basis for prioritizing candidate blocks before surface-well deployment.
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Zhang et al. (2026) studied this question.
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