智能时代的矿井地质工作展望——矿井开采智能地质保障技术体系架构

夏玉成, 孙学阳, 苗霖田, 郭晨, 杜荣军

夏玉成, 孙学阳, 苗霖田, 郭晨, 杜荣军. 智能时代的矿井地质工作展望——矿井开采智能地质保障技术体系架构[J]. 煤田地质与勘探.
引用本文: 夏玉成, 孙学阳, 苗霖田, 郭晨, 杜荣军. 智能时代的矿井地质工作展望——矿井开采智能地质保障技术体系架构[J]. 煤田地质与勘探.
XIA Yucheng, SUN Xueyang, MIAO Lintian, GUO Cheng, DU Rong. Prospects for Mine Geological Work in the Age of Intelligence: The architecture of intelligent geological support technology system for coal mining[J]. COAL GEOLOGY & EXPLORATION.
Citation: XIA Yucheng, SUN Xueyang, MIAO Lintian, GUO Cheng, DU Rong. Prospects for Mine Geological Work in the Age of Intelligence: The architecture of intelligent geological support technology system for coal mining[J]. COAL GEOLOGY & EXPLORATION.

 

智能时代的矿井地质工作展望——矿井开采智能地质保障技术体系架构

基金项目: 

陕西省自然科学基础研究计划项目(2023-JC-YB-272)

国家重点研发计划项目(2022YFF1303304)

详细信息
    作者简介:

    夏玉成,1957年生,男,甘肃武威人,博士,教授,博士生导师。E-mail:xiayc823@163.com

    通讯作者:

    孙学阳,1976年生,男,安徽涡阳人,博士,教授,博士生导师。E-mai:sxy163@163.com

  • 中图分类号: TD163;TD82

Prospects for Mine Geological Work in the Age of Intelligence: The architecture of intelligent geological support technology system for coal mining

  • 摘要: 面临碳达峰碳中和(“双碳”)目标的严峻挑战,煤矿智能化是新时期煤炭产业高质量可持续发展的必由之路和重要标志。矿井地质工作为地下煤矿开采提供地质基础和保障,在煤炭产业转型升级高质量发展中的重要性将日益增强。通过“矿井地质+人工智能”,构建“矿井开采智能地质保障技术体系”,为矿井安全高效绿色智能开采提供全方位和全过程地质保障,是新时期矿井地质工作契合煤矿智能化建设目标的发展方向与必然趋势,必将成为助推矿井地质工作提质增效的新质生产力。在探讨矿井开采智能地质保障技术体系科学内涵的基础上,初步搭建了矿井开采智能地质保障技术体系架构,并对构成该技术体系的5个子体系:基础地测信息智能化管理、矿井地质灾害的智能化预测预警、矿区生态环境的智能化监测预测预警、开采有利区块的智能化辨识、透明工作面子体系,及其核心工作模块进行系统梳理。同时特别强调,在地质探测、检测技术手段不断进步的前提下,矿井开采智能地质保障技术体系的有效性取决于原始数据的准确性和可靠性,归根结底取决于地测人员的数量和专业素养,呼吁进一步加强矿井地质专业人才的引进与培养。
    Abstract: Facing the severe challenges of the “dual carbon” goal, the intelligentization of coal mines is the only way and important symbol for the high-quality and sustainable development of the coal industry in the new era. Mine geological work provides geological foundation and guarantee for underground coal mining, and its importance in the transformation and upgrading of the coal industry for high-quality development will increase. Through the combination of “mine geology + artificial intelligence”, the construction of a “intelligent geological support technology system for mine mining” provides comprehensive and full-process geological support for safe, green, efficient and intelligent mining in mines. It is the development direction and inevitable trend of mine geological work in the new era that fits the goal of intelligent construction of coal mines, and will become a new productivity that will boost the quality and efficiency of mine geological work. Based on the discussion of the scientific connotation of the intelligent geological support technology system for mining in mines, a preliminary framework for the intelligent geological support technology system for mining in mines has been established, and the five subsystems that constitute the technology system have been systematically sorted out:the intelligent management subsystem of basic geological survey information, the intelligent prediction and early warning subsystem of geological disasters in mines, the intelligent monitoring and prediction subsystem of ecological environment in mining areas, the intelligent identification subsystem of favorable mining blocks, and transparent work face subsystem, as well as their core work modules. Meanwhile, it is especially emphasized that under the premise of continuous progress of geological exploration and detection technical means, the effectiveness of the intelligent geological support technology system of mine mining depends on the accuracy and reliability of the original data, and ultimately depends on the number and professional quality of the geological personnel. It is called for to further strengthen the introduction and cultivation of geological professionals in mines.
  • [1] 谢克昌. 新型能源体系发展背景下煤炭清洁高效转化的挑战及途径[J]. 煤炭学报,2024,49(1):47-56.

    XIE Kechang. Develop new energy system and promote clean and efficient conversion of coal[J]. Journal of China Coal Society,2024,49(1):47-56.

    [2] 彭苏萍. 我国煤矿安全高效开采地质保障系统研究现状及展望[J]. 煤炭学报,2020,45(7):2331-2345.

    PENG Suping. Current status and prospects of research on geological assurance system for coal mine safe and high efficient mining[J]. Journal of China Coal Society,2020,45(7):2331-2345.

    [3] 王国法,巩师鑫,申凯.煤矿智能安控技术体系与高质量发展对策[J].矿业安全与环保,2023,50(5):1-8.

    WANG Guofa,GONG Shixin,SHEN Kai. Intelligent security control technology system and high-quality development countermeasures for coal mines[J]. Mining Safety & Environmental Protection,2023,50(5):1-8.

    [4] 董书宁,刘再斌,程建远,等.煤炭智能开采地质保障技术及展望[J].煤田地质与勘探,2021,49(1):21-31.

    DONG Shuning,LIU Zaibin,CHENG Jianyuan,et al. Technologies and prospect of geological guarantee for intelligent coal mining[J]. Coal Geology & Exploration,2021,49(1):21-31.

    [5] 彭苏萍.建立和发展我国煤矿高产高效矿井地质保障系统[C]//中国煤炭学会矿井地质专业委员会年会报告.上海:1992.
    [6] 夏玉成.论高产高效工作面地质保障系统[J].中国煤田地质,1997,(S1):33-36.

    XIA Yucheng. On the geological guarantee system of high-yield and high-efficiency working face[J]. Coal Geology of China,1997,(S1):33-36.

    [7] 王安民.浅析建设高产高效矿井的地质保障[J].煤田地质与勘探,1998,(2):34-37.

    WANG Anmin. Analysis of the geological guarantee for the construction of high-yield and high-efficiency mines[J]. Coal Geology & Exploration,1998,(2):34-37.

    [8] 彭苏萍.中国煤矿高产高效矿井地质保障系统[J].河北煤炭,1999,(S1):1-4.

    PENG Suping. China's coal mine geological guarantee system with high yield and high efficiency[J]. Hebei Coal,1999,(S1):1-4.

    [9] 柴学周,岳建华.高产高效矿井地质保障体系研究[J].能源技术与管理,2004,(4):8-10.

    CHAI Xuezhou,YUE Jianhua. Research on the geological guarantee system of high-yield and high-efficiency mines[J]. Energy Technology and Management,2004,(4):8-10.

    [10] 郝贵,柴杨.我国煤炭行业“黄金十年”的成因分析[J].中国矿业,2013,22(2):17-19.

    HAO Gui,CHAI Yang. Analysis of the causes of the “golden decade” of China's coal industry[J]. China Mining Magazine,2013,22(2):17-19.

    [11] 胡省三,成玉琪.21世纪前期我国煤炭科技重点发展领域探讨[J].煤炭学报,2005,(1):1-7.

    HU Shengsan,CHENG Yuqi. Discussion on the key development areas of coal science and technology in China in the early 21st century[J]. Journal of China Coal Society,2005,(1):1-7.

    [12] 董书宁,刘再斌,程建远,等. 煤炭智能开采地质保障技术及展望[J]. 煤田地质与勘探,2021,49(1):21–31.

    DONG Shuning,LIU Zaibin,CHENG Jianyuan,et al. Technologies and prospect of geological guarantee for intelligentcoal mining[J]. Coal Geology & Exploration,2021,49(1):21–31.

    [13] 刘业娇,袁亮,薛俊华,等.2007-2016年全国煤矿瓦斯灾害事故发生规律分析[J].矿业安全与环保,2018,45(3):124-128.

    LIU Yejiao,YUAN Liang,XUE Junhua,et al. Analysis of the occurrence law of coal mine gas disasters in China from 2007 to 2016[J]. Mining Safety & Environmental Protection,2018,45(3):124-128.

    [14] 夏玉成.煤矿区地质环境承载能力及其评价指标体系研究[J].煤田地质与勘探,2003,(1):5-8.

    XIA Yucheng. Bearing capacity of geological environment in coal-mining area and its assessment index system[J]. Coal Geology & Exploration,2003,(1):5-8.

    [15] 薛永安,邹友峰,张文志,等.基于SVM的地下采煤区沉陷灾害发育敏感性分区研究[J].煤田地质与勘探,2022,50(10):108-118.

    XUE Yong’an,ZOU Youfeng,ZHANG Wenzhi,et al. SVM-based sensitivity zoning of subsidence disaster development in the underground coal mining areas[J]. Coal Geology & Exploration,2022,50(10):108-118.

    [16] 夏玉成,杜荣军,孙学阳,等.陕北煤田生态潜水保护与矿井水害预防对策[J].煤炭科学技术,2016,44(8):39-45.

    Xia Yucheng,Du Rongjun,Sun Xueyang,et al. Countermeasures of ecologic phreatic water protection and mine water disaster prevention in northern Shaanxi Coalfield[J]. Coal Science and Technology,2016,44(8):39-45.

    [17] 袁亮,张平松.煤炭精准开采地质保障技术的发展现状及展望[J].煤炭学报,2019,44(8) :2277-2284.

    YUAN Liang,ZHANG Pingsong. Development status and prospect of geological guarantee technology for precise coal mining[J]. Journal of China Coal Society,2019,44(8):2277-2284.

    [18] 许献磊,马正,陈令洲.煤矿地质灾害隐患透明化探测技术进展与思考[J].绿色矿山,2023,1(1):56-69.

    XU Xianlei,MA Zheng,CHEN Lingzhou. Progress and thinking of transparent detection technology for hidden geological hazards in coal mines[J]. Journal of Green Mine,2023,1(1):56-69.

    [19] 许家林,鞠金峰,轩大洋,等.煤矿全生命周期绿色开采研究展望[J].绿色矿山,2023,1(1):79-90.

    XU Jialin,JU Jinfeng,XUAN Dayang,et al. Prospects for green mining research of coal mine life cycle[J]. Journal of Green Mine,2023,1(1):79-90.

    [20] 刘峰,郭林峰,张建明,等.煤炭工业数字智能绿色三化协同模式与新质生产力建设路径[J].煤炭学报,2024,49(1):1-15.

    LIU Feng,GUO Linfeng,ZHANG Jianming,et al. Synergistic mode of digitalization- intelligentization- greeniation of the coal industry and it’s path of building new coal productivity[J]. Journal of China Coal Society,2024,49(1):1-15.

    [21] 贾建称,贾茜,桑向阳,等.我国煤矿地质保障系统建设30年:回顾与展望[J].煤田地质与勘探,2023,51(1):86-106.

    JIA Jiancheng,JIA Qian,SANG Xiangyang,et al. Review and prospect of coal mine geological guarantee system in China during 30 years of construction[J]. Coal Geology & Exploration,2023,51(1):86-106.

    [22] 段中会,苗霖田,张建军,等. 煤炭地质云及数字煤矿地质保障系统研发与应用[R]. 西安:陕西省煤田地质集团有限公司,2018-12-25.
    [23] 刘再斌,刘程,刘文明,等.透明工作面多属性动态建模技术[J].煤炭学报,2020,45(7):2628-2635.LIU Zaibin,LIU Cheng,LIU Wenming,et al. Multi-attribute dynamic modeling technique for transparent working face [J]. Journal of China Coal Society,2020,45(7):2628-2635.
    [24] 国家能源局,息烽县工业和信息化局.煤矿智能化标准体系建设指南[M].国能发科技〔2024〕18号,2024,000014349/2024-499088.
    [25] 赵兵朝,冯杰,赵阳,等. 覆岩导水裂隙带发育高度动态演化规律研究[J]. 煤矿安全,2024,55(2):176−183.ZHAO Bingchao,FENG Jie,ZHAO Yang,et al. Study on dynamic evolution law of development height of overburden water-flowing fractured zone[J]. Safety in Coal Mines,2024,55(2):176−183.
    [26] 高家明,夏永学,杨光宇,等.复合构造区域煤岩体应力分布及冲击地压危险性评价[J].工矿自动化,2021,47(3):14-19+26.GAO Jiaming,XlA Yongxue,YANG Guangyu,et al . The stress distribution of coal and rock mass and the risk evaluation of rock burst in the composite structure area[J]. Industry and Mine Automation,202l.47(3):14-19.
    [27]

    Fenner M,Crosas M,Grethe J S,et al. A data citation roadmap for scholarly data repositories[J]. Scientific Data,2019,6(1):28.

    [28] 常立新,廉永彪,廉永海.论人工智能背景下地质资料服务模式转型[J].自然资源信息化,2024(2):23-28.

    CHANG Lixin,LIAN Yongbiao,LIAN Yonghai. Study on the transformation of geological data service models under the background of artificial intelligence[J]. Natural Resources Informatization,2024(2):23-28.

    [29]

    Yang Z.,Qi W.-w.,Xu C.,et al. Exploring deep learning for landslide mapping:A comprehensive review[J]. China Geology,2024,7(2):330-350.

    [30] 何文娜,朱长青,李仰春,等.基于ArcGIS的智能地质图综合[J].地球物理学进展,2020,35(2):0728-0734.

    HE Wenna,ZHU Changqing,LI Yangchun,et al. Intelligent geological map generalization based on Arc GIS[J]. Progress in Geophysics,2020,35(2):0728-0734.

    [31] 李仰春,王永志,陈圆圆,等.智绘地质:新一代智能化地质编图模式及应用[J].地质通报,2020,39(6):861-870.

    LI Yangchun,WANG Yongzhi,CHEN Yuanyuan,et al. Intelligent geological mapping:A novel pattern for smart geological compilation[J]. Geological Bulletin of China,2020,39(6):861-870.

    [32] 李杏龙,文广超,谢洪波.矿井瓦斯地质图辅助编图方法研究[J].煤炭技术,2022,41(2):117-120.

    LI Xinglong,WEN Guangchao,XIE Hongbo. Research on Auxiliary Mapping Method of Mine Gas-geological Map[J]. Coal Technology,2022,41(2):117-120.

    [33] 夏玉成,王悦,马丽.矿井地质灾害要素与地质灾源体辨识评价[J].中国煤炭地质,2019,31(2):51-56.

    XIA Yucheng,WANG Rui,MA Li. Coalmine Geological Hazard Elements and Geological Disaster Source Bodies Identification Assessment[J]. Coal Geology of China,2019,31(2):51-56.

    [34] 蒋必辞,程建远,李萍,等.基于钻孔雷达的透明工作面构建方法[J].煤田地质与勘探,2022,50(1):128−135.

    JIANG Bici,CHENG Jianyuan,LI Ping,et al.Construction method of transparent working face based on borehole radar[J].Coal Geology & Exploration,2022,50(1):128−135.

    [35] 李忠辉,王恩元,刘晓斐,等. 煤矿突出动力灾害声电瓦斯智能监测预警技术与装备[R]. 西安:中国矿业大学,2019-12-01.
    [36] 刘程,孙东玲,邓飞,等.煤矿多灾害智能防治与智能监控技术[J].智能矿山,2022,7:105-114.

    LIU Cheng,SUN Dongling,DENG Fei,et al.Intelligent control and monitoring technology of multi-disaster in coal mine [J]. Journal of Intelligent Mine,2022,7:105-114.

    [37] 储栋. 基于无人机的矿区地表特征点云提取方法及变形监测研究[D]. 淮南:安徽理工大学,2024.
    [38] 苏宇,汤伏全,李景祥,等. 矿山采动地表裂缝智能识别的YOLOv7模型改进研究[J]. 煤矿安全,2024,55(4):169−176.SU Yu,TANG Fuquan,LI Jingxiang,et al. Improvement of YOLOv7 model for intelligent recognition of mining surface cracks[J]. Safety in Coal Mines,2024,55(4):169−176.TANG Fuquan,LI Linkuan,LI Xiaotao,et al. Research on characteristics of mining-induced surface cracks based on UAV images[J]. Coal Science and Technology,2020,48(10):130-136.
    [39] 蔡秋欢.基于GPS与InSAR数据的矿区地表形变分析与研究[D].内蒙古工业大学,2023.CAI Qiuhuan. Analysis and Research on Surface Deformation in Mining Areas Based on GPS and InSAR Data[D]. Inter Mongolia University of Techology,2023.
    [40] 孙学阳,夏玉成.煤矿区构造环境内涵及类型划分[J].煤田地质与勘探,2015,43(4):79-84.

    SUN Xueyang,XIA Yucheng. Connotation of tectonic setting in coal area and its type division[J]. Coal Geology & Exploration,2015,43(4):79-84.

    [41] 吴群英,彭捷,迟宝锁,等.神南矿区煤炭绿色开采的水资源监测研究[J].煤炭科学技术,2021,49(1):304-311.

    WU Qunying,PENG Jie,CHI Baosuo,et al. Researoh on water resources monitoring of green coal mining in Shenan Ming Anea[J]. Coal Science and Technology,2021,49(1):304-311.

    [42] 范立民,孙魁,李成,等.西北大型煤炭基地地下水监测背景、思路及方法[J].煤炭学报,2020,45(1):317-329.FAN Limin,SUN Kui,LI Cheng,et al. Background,thought and method of groundwater monitoring in large coal base of northwest China[J]. Journal of China Coal Society,2020,45(1):317-329.
    [43] 宋子岭,祁文辉,范军富,等. 大型露天煤矿绿色开采评价体系研究[J]. 安全与环境学报,2017,17(3):1177-1182.

    SONG Ziling,QI Wenhui,FAN Junfu,et al. On the establishment of the evaluation system for green mining in large openpit coal mines[J]. Journal of Safety and Environment,2017,17(3):1177-1182.

    [44] 虎维岳,赵春虎.基于充水要素的矿井水害类型三线图划分方法[J].煤田地质与勘探,2019,47(5):1-8.HU Weiyue,ZHAO Chunhu. Trilinear chart classification method of mine water hazard type based on factors of water recharge[J]. Coal Geology & Exploration,2019,47(5):1-8.
    [45] 苗霖田,夏玉成,段中会,等.黄河中游榆神府矿区煤-岩-水-环特征及智能一体化技术[J].煤炭学报,2021,46(5):1521-1531.MIAO Lintian,XIA Yucheng,DUAN Zhonghui,et al.Coupling characteristics and intelligent integration technology of coal-overlying rock-groundwater-ecological environment in Yu-Shen-Fu mining area in the middle reaches of the Yellow River[J]. Journal of China Coal Society,2021,46(5):1521-1531.
    [46] 夏玉成,王佟,等.煤炭开采地质条件量化预测技术及程序设计[M].西安:陕西科学技术出版社,2001.
    [47] 李宏泽,丁海,詹润,等.煤矿开采区块综合评价与判识研究——以口孜东矿13-1煤层为例[J].煤炭科技,2023,44(1):1-6.

    LI Hongze,DING Hai,ZHAN Run,et al. Study on comprehensive evaluation and identification of coal mining blocks:taking 13-1 coal seam of Kouzidong Mine as an example[J]. Coal Science & Technology Magazine,2023,44(1):1-6.

    [48] 孙学阳,张齐,夏玉成,等.韩城矿区煤炭资源有利开采区块辨识的原理与方法[J].煤炭科学技术,2020,48(11):232-240.

    SUN Xueyang,ZHANG Qi,XIA Yucheng,et al. Principle and method of identifying favorable coal mining area in Hancheng[J]. Coal Science and Technology,2020,48(11):234-240.

    [49] 王国法,张建中,薛国华,等.煤矿回采工作面智能地质保障技术进展与思考[J].煤田地质与勘探,2023,51(2):12-26.

    WANG Guofa,ZHANG Jianzhong,XUE Guohua,et al. Progress and reflection of intelligent geological guarantee technology in coal mining face[J]. Coal Geology & Exploration,2023,51(2):12-26.

    [50] 毛善君.灰色地理信息系统—动态修正地质空间数据的理论和技术[J].北京大学学报(自然科学版),2002,38(4):556-562.

    MAO Shanjun. Gray geographical information system-the theory and technology of correct geological spatial data dynamically[J]. Acta Scientiarum Naturalium Universitatis Pekinensis,2002,38(4):556-562.

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  • 收稿日期:  2024-07-27
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