Volume 50 Issue 1
Jan.  2022
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LIU Wenming，GAO Yaoquan，JIANG Bici，et al.Application research on dynamic calibration and prediction technology of coal seam in coalmine working face[J].Coal Geology & Exploration，2022，50(1)：31−35. DOI: 10.12363/issn.1001-1986.21.11.0616
Citation: LIU Wenming，GAO Yaoquan，JIANG Bici，et al.Application research on dynamic calibration and prediction technology of coal seam in coalmine working face[J].Coal Geology & Exploration，2022，50(1)：31−35. DOI: 10.12363/issn.1001-1986.21.11.0616
shu

Application research on dynamic calibration and prediction technology of coal seam in coalmine working face

  • 1.

    Xi’an Research Institute Co. Ltd., China Coal Technology and Engineering Group Corp., Xi’an 710077, China

  • 2.

    China Coal Research Institute, Beijing 100013, China

  • 3.

    College of Geology and Environment, Xi’an University of Science and Technology, Xi’an 710054, China

  • 4.

    Ordos Huaxing Energy Co. Ltd., Ordos 017000, China

More Information
  • Received Date: November 01, 2021
  • Revised Date: December 26, 2021
  • Available Online: January 26, 2022
  • Published Date: January 31, 2022
    Graphical Abstract
    • Abstract
  • One of the prominent problems of intelligent mining is its inadaptability to geological conditions, especially for the absolute accuracy of coal seam floor and thickness. 3D seismic has a high horizontal resolution and it can control the ups and downs of the coal seam. However, due to the time domain data, the calculation of the coal seam floor elevation is negatively affected by the time-depth conversion point. On the basis of the 3D seismic data of the working face and the coal thickness data during the mining process, the absolute accuracy of the time-depth conversion of the coal seam floor is improved by continuously refreshing the velocity field. At the same time, the iterative interpolation algorithm is used to continuously update the coal seam thickness of the working face, then error statistics and analysis are conducted based on the calculated data. The experiment was carried out at TJH304 working face after using coal seam floor height and thickness of working face tunnel and mining face combined with the dynamic interpretation of the 3D seismic data. The absolute error of the coal seam floor elevation and thickness values in front of the working face is reduced. In particular, the four verification points within thirty meters from the current mining face and the coal seam floor elevation error is between 0.37-0.58 m; the coal seam thickness error is between 0.32-0.44 m. The results show that the 3D seismic dynamic interpretation technology can maximize the effective combination of 3D seismic and downhole production data, continuously improve the spatial accuracy of coal seam, and provide a prospective coal seam model for intelligent mining.
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    • References (13)
  • [1]
    王国法,刘峰,庞义辉,等. 煤矿智能化–煤炭工业高质量发展的核心技术支撑[J]. 煤炭学报,2019,44(2):349−357.

    WANG Guofa,LIU Feng,PANG Yihui,et al. Coal mine intellectualization:The core technology of high quality development[J]. Journal of China Coal Society,2019,44(2):349−357.
    [2]
    王国法,刘峰,孟祥军,等. 煤矿智能化(初级阶段)研究与实践[J]. 煤炭科学技术,2019,47(8):1−36.

    WANG Guofa,LIU Feng,MENG Xiangjun,et al. Research and practice on intelligent coal mine construction(primary stage)[J]. Coal Science and Technology,2019,47(8):1−36.
    [3]
    程建远,朱梦博,王云宏,等. 煤炭智能精准开采工作面地质模型梯级构建及其关键技术[J]. 煤炭学报,2019,44(8):2285−2295.

    CHENG Jianyuan,ZHU Mengbo,WANG Yunhong,et al. Cascade construction of geological model of longwall panel for intelligent precision coal mining and its key technology[J]. Journal of China Coal Society,2019,44(8):2285−2295.
    [4]
    徐志鹏．采煤机自适应截割关键技术研究[D]．徐州: 中国矿业大学, 2011．

    XU Zhipeng．Study on the key technologies of self–adaptive cutting for shearer[D]．Xuzhou: China University of Mining and Technology, 2011．
    [5]
    王铁军．基于动态精细建模的薄煤层采煤机广义记忆切割技术研究[D]．北京: 中国矿业大学(北京), 2013．

    WANG Tiejun．Research on the generalized memory cutting technology of thin seam shearers based on dynamic fine modeling[D]．Beijing: China University of Mining and Technology(Beijing), 2013．
    [6]
    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.
    [7]
    袁亮. 我国煤炭工业高质量发展面临的挑战与对策[J]. 中国煤炭,2020,46(1):6−12.

    YUAN Liang. Challenges and countermeasures for high quality development of China’s coal industry[J]. China Coal,2020,46(1):6−12.
    [8]
    程建远,聂爱兰,张鹏. 煤炭物探技术的主要进展及发展趋势[J]. 煤田地质与勘探,2016,44(6):136−141. DOI: 10.3969/j.issn.1001-1986.2016.06.025

    CHENG Jianyuan,NIE Ailan,ZHANG Peng. Outstanding progress and development trend of coal geophysics[J]. Coal Geology & Exploration,2016,44(6):136−141. DOI: 10.3969/j.issn.1001-1986.2016.06.025
    [9]
    程建远,王寿全,宋国龙. 地震勘探技术的新进展与前景展望[J]. 煤田地质与勘探,2009,37(2):55−58. DOI: 10.3969/j.issn.1001-1986.2009.02.015

    CHENG Jianyuan,WANG Shouquan,SONG Guolong. The new development and foreground expectation of seismic exploration[J]. Coal Geology & Exploration,2009,37(2):55−58. DOI: 10.3969/j.issn.1001-1986.2009.02.015
    [10]
    陆自清. 基于边界元方法的次级断裂信息挖掘试验研究[J]. 煤田地质与勘探,2020,48(5):211−217. DOI: 10.3969/j.issn.1001-1986.2020.05.026

    LU Ziqing. Experiment of secondary fault information mining based on boundary element method[J]. Coal Geology & Exploration,2020,48(5):211−217. DOI: 10.3969/j.issn.1001-1986.2020.05.026
    [11]
    刘再斌,刘程,刘文明,等. 透明工作面多属性动态建模技术研究[J]. 煤炭学报,2020,45(7):2628−2635.

    LIU Zaibin,LIU Cheng,LIU Wenming,et al. Study on multi−attribute dynamic modeling technique for transparent working face[J]. Journal of China Coal Society,2020,45(7):2628−2635.
    [12]
    程建远,朱梦博,崔伟雄,等. 回采工作面递进式煤厚动态预测试验研究[J]. 煤炭科学技术,2019,47(1):237−244.

    CHENG Jianyuan,ZHU Mengbo,CUI Weixiong,et al. Experimental study of coal thickness progressive prediction in working face[J]. Coal Science and Technology,2019,47(1):237−244.
    [13]
    LEVY B,MALLET J L. Discrete smooth interpolation: Constrained discrete fairing for arbitrary meshes[J]. Computer Aided Design,1992,24(4):263−270.
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