回采工作面煤层动态标定预测技术应用研究

刘文明; 高耀全; 蒋必辞; 李鹏; 薛悟强

doi:10.12363/issn.1001-1986.21.11.0616

回采工作面煤层动态标定预测技术应用研究

doi: 10.12363/issn.1001-1986.21.11.0616

刘文明^1,,
高耀全¹,
蒋必辞^{1, 2},
李鹏^{1, 3},
薛悟强⁴

基金项目: 天地科技股份有限公司科技创新创业资金专项重点项目(2019-TD-ZD003)；国家重点研发计划项目(2017YFC0804100)；天地科技股份有限公司科技创新创业资金专项项目(2018-TD-MSD072)

详细信息

第一作者:
刘文明，1990年生，男，山东临沂人，硕士，助理研究员，从事矿井地质透明化研究工作. E-mail：liuwm0506@126.com

中图分类号: P631
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- 被引次数: 0
出版历程
- 收稿日期: 2021-11-02
- 修回日期: 2021-12-27
- 发布日期: 2022-02-01
- 网络出版日期: 2022-01-27

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

LIU Wenming^1
,,
GAO Yaoquan¹,
JIANG Bici^{1, 2},
LI Peng^{1, 3},
XUE Wuqiang⁴

摘要

摘要: 智能开采对于地质条件的不适应问题非常突出，特别是对煤层起伏和厚度的绝对精度提出了更高的要求。三维地震勘探横向分辨率高，能够对煤层起伏进行控制，但在地震解释时，煤层底板高程受时深转换计算影响，存在一定的误差。针对这一问题，以工作面三维地震数据和采掘过程中探煤厚数据为基础，通过不断更新速度场提高煤层底板时深转换绝对精度；同时利用迭代插值算法，不断更新工作面煤层厚度；通过对计算得到的数据进行误差统计和分析。在TJH304回采工作面进行试验，利用工作面巷道和切眼探煤厚数据并结合三维地震资料动态解释后，工作面推采前方煤层底板高程值和厚度值绝对误差变小；特别是距离当前采煤面30 m以内的4个验证点煤层底板高程值误差范围为0.37~0.58 m，煤层厚度值误差为0.32~0.44 m。结果表明，三维地震动态解释技术可最大化将三维地震和井下生产数据有效结合，不断提高煤层空间精度，为智能开采提供预想煤层模型。
- 智能开采 /
- 地震动态解释 /
- 速度场刷新 /
- 迭代插值
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.
- intelligent mining /
- seismic dynamic interpretation /
- velocity field updating /
- iterative interpolation

HTML全文

图 1 TJH304工作面分布

Fig. 1 Sketch map of TJH304 longwall panel

下载: 全尺寸图片幻灯片

图 2 TJH304工作面推进方向地震剖面(A—A’)

Fig. 2 Seismic section map of TJH304 working face along mining direction(A-A’)

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图 3 巷道及切眼煤层底板测量点高程与双程旅行时相关关系

Fig. 3 The correlation of coal bottom elevation value and two-way time value of measure points in tunnel and initial mining surface

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图 4 不同开采阶段煤层底板高程数据更新前后的平均速度场平面图

Fig. 4 The average velocity comparison map updated by coal bottom elevation value of mining working face in different mining stages

下载: 全尺寸图片幻灯片

图 5 不同开采阶段煤层厚度数据更新前后的煤层厚度平面图

Fig. 5 The coal seam thickness comparison map updated by coal seam thickness value of mining working face in different mining stages

下载: 全尺寸图片幻灯片

表 1 不同开采阶段煤层底板与煤层厚度预测绝对误差

Table 1 Absolute error of the prediction of coal seam floor elevation and thickness in different mining stages

开采阶段	预测目标	验证点数	绝对误差范围/m	平均误差/m	0~0.5 m误差验证点数及概率/%	0.5~1.0 m误差验证点数及概率/%	大于1.0 m误差验证点数及概率/%
回采前	煤层底板	44	0.42~3.63	2.34	8/18.2	13/29.5	23/52.3
回采前	煤层厚度	44	0.27~1.89	1.32	11/25.0	13/29.5	20/45.5
回采300 m	煤层底板	22	0.34~3.26	2.12	5/22.7	7/36.4	10/45.5
回采300 m	煤层厚度	22	0.11~1.76	1.13	6/27.3	7/31.8	9/40.9

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参考文献(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.