煤矿隐蔽致灾因素内涵及普查要点辨析

Analysis of the connotation of hidden disaster-causing factors in coal mines and the key points of their reconnaissance

  • 摘要:
    背景 为系统规范煤矿隐蔽致灾因素普查工作,国家矿山安全监察局于2024年颁布了《矿山隐蔽致灾因素普查规范》。当前煤矿企业在实施过程中仍面临隐蔽致灾因素内涵界定模糊、普查范围宽泛、实施阶段不明确、勘查与普查脱节、结论表述不当等突出问题,严重制约了隐蔽致灾因素普查工作的科学性和可操作性。
    方法 回顾了隐蔽致灾因素普查的研究历程,梳理总结了各发展阶段的主要技术成果,剖析存在问题,凝练关键技术和科学问题,展望业界未来所面临的挑战,指出迎接挑战的关键技术及理论方向。
    进展 在此基础上,界定隐蔽致灾因素内涵仅包括地质类因素和采矿类因素,进一步划分为5大类,煤层储存条件、地质体、地质构造、采矿及其他因素;普查实施阶段应摒弃传统的“3年周期普查”模式,采用建井前区域探查、生产前补充勘探、采区设计前精细勘查、采掘前综合探治、采掘过程中动态补充的递进式普查治理方法,突出隐蔽致灾因素普查与治理的动态演化特征,实现灾害防控与采掘工程的动态协同;建立隐蔽致灾因素资料评估机制,即已经查明直接引用、部分存疑局部验证、尚未查明全面探查,实现勘查与普查的高效协同,避免重复探查;提出“一般规定−资料分析−现场探查−危险性评价−结论建议”的标准化普查流程。
    展望  我国复杂的地质构造决定了隐蔽致灾因素在采掘过程中的重要地位,在未来隐蔽致灾领域将跟随科学脚步,面向智能、透明化矿山需求,构建“区域−矿井−煤层”的隐蔽致灾评估体系,推动灾害防控和采掘活动的动态协同,为煤矿安全开采提供地质保障,为煤矿隐蔽致灾因素普查提供科学指导,对提升矿山灾害防控能力具有重要意义。

     

    Abstract:
    Background To systematically normalize the reconnaissance of hidden disaster-causing factors in coal mines, the National Mine Safety Administration issued the Specification for General Survey of Hidden Disaster-causing Factors in Mine in 2024. Nevertheless, coal mining enterprises still face a range of notable issues in reconnaissance of hidden disaster-causing factors, including ambiguous connotations of the factors, broad scopes of reconnaissance, unclear implementation stages, a disjunction between explorations and reconnaissance, and improper conclusion descriptions. These problems severely restrict scientific and operational reconnaissance.
    Methods This study reviews the history of research on the reconnaissance of hidden disaster-causing factors, presents a summary of significant technical achievements across various development stages, and analyzes existing issues, especially critical technical and scientific issues. Furthermore, this study proposes future c in the industry, as well as primary technical and theoretical orientations to address the challenges.
    Advances This study holds that hidden disaster-causing factors consist merely of geologic and mining factors, which can be further categorized into five major types: coal seam storage conditions, geobodies, geological structures, mining, and others. Regarding general-survey implementation stages, this study proposes that the traditional survey mode with three years as a cycle should be replaced by a progressive approach, which comprises regional exploration before shaft construction, supplementary exploration before coal mining, detailed survey prior to panel design, integrated exploration and treatment before mining, and dynamic supplementary survey during mining. This approach emphasizes the dynamic evolution of the reconnaissance and treatment of hidden disaster-causing factors, enabling the dynamic coordination between mining engineering and disaster prevention and control. This study recommends that it is necessary to establish a data assessment mechanism for hidden disaster-causing factors, i.e., directly citing verified factors, partially verifying questionable factors, and comprehensively exploring unknown factors. This helps achieve efficient coordination between explorations and reconnaissance while avoiding redundant efforts. Moreover, this study proposes a standardized reconnaissance process comprising general provisions, data analysis, field exploration, risk assessment, and conclusions and suggestions.
    Prospects In China, complex geological structures underscore the critical role of exploring hidden disaster-causing factors in coal mining. With scientific advancements and the demand for transparency and intelligent mining of coal mines, it is necessary to develop a region-mine-coal seam assessment system for hidden disaster-causing factors and to promote the dynamic coordination between mining operations and disaster prevention and control. This helps provide a geological guarantee for safe coal mining and a scientific guide for reconnaissance of hidden disaster-causing factors in coal mines, holding great significance for enhancing the disaster prevention and control capability of coal mines.

     

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