煤矿微震监测台网监测能力分析与优化方法

陈法兵; 吴红军; 崔保阁; 王元杰; 李岩

doi:10.13272/j.issn.1671-251x.2022020048

煤矿微震监测台网监测能力分析与优化方法

doi: 10.13272/j.issn.1671-251x.2022020048

陈法兵^{1, 2,},
吴红军³,
崔保阁⁴,
王元杰^{1, 2},
李岩^{1, 2}

1.
煤炭科学研究总院开采研究分院, 北京　100013
2.
中煤科工开采研究院有限公司, 北京　100013
3.
辽宁九道岭煤业有限公司, 辽宁锦州　121100
4.
山东唐口煤业有限公司, 山东济宁　272055

基金项目: 天地科技股份有限公司科技创新创业资金专项项目（2019-TD-CXY004，2019-TD-CXY006）。

详细信息

作者简介:
陈法兵（1985—），男，山东泰安人，助理研究员，硕士，主要从事煤矿冲击地压机理与防治技术研究工作，E-mail：727479294@qq.com

中图分类号: TD326
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- 被引次数: 0
出版历程
- 收稿日期: 2022-02-24
- 修回日期: 2022-07-09
- 网络出版日期: 2022-04-14

Analysis and optimization method of monitoring capability of coal mine microseismic monitoring network

CHEN Fabing^{1, 2
,},
WU Hongjun³,
CUI Baoge⁴,
WANG Yuanjie^{1, 2},
LI Yan^{1, 2}

1.
Coal Mining Branch, China Coal Research Institute, Beijing 100013, China
2.
CCTEG Coal Mining Research Institute, Beijing 100013, China
3.
Liaoning Jiudaoling Coal Industry Co., Ltd., Jinzhou 121100, China
4.
Shandong Tangkou Coal Mine Co., Ltd., Jining 272055, China

摘要

摘要: 微震监测台网的监测能力取决于多种因素，如台网布置、速度模型、震相读取误差、走时区域异常、定位算法、设备运行状态和环境噪声等，其中台网布置现阶段可以人为优化。为了对微震监测台网的监测能力进行有效评价，并在此基础上对台网布置进行优化，提出了一种煤矿微震监测台网监测能力分析与优化方法。分析了台网布置因素中对微震监测台网监测能力影响最大、最直接的四因素：有效波形数、最大空隙角、近台震中距和台站高差，指出有效波形数、近台震中距和台站高差对震源深度求解误差起决定性作用，有效波形数和最大空隙角对震中定位精度起决定性作用。结合现有台网和工作面情况，得出四因素的分布云图，通过四因素分布云图逐项对微震监测台网监测能力进行评价，根据评价结果进行优化，得出新的台网布置方案；对新方案进行定位误差与灵敏度分析，得出全矿井的震中定位误差、震源定位误差及区域灵敏度，对新方案进行二次评价；若二次评价结果满足要求，则可将新方案作为最佳台网布置方案；若二次评价结果不满足要求，则重新进行四因素分项评价并对方案进行优化，直至满足要求为止。现场试验结果表明，利用提出的方法对唐口煤矿5307工作面的微震监测台网进行优化后，爆破震源定位误差均值由59.2 m降到37.2 m，定位误差最大值降到100 m以下，误差在50 m以下的爆破事件占总数的69.0%，说明提出的方法能够有效提高微震定位精度，优化台网监测能力。
- 煤矿微震监测 /
- 微震监测台网 /
- 台网布置 /
- 监测能力 /
- 分级评价 /
- 震源深度 /
- 震源定位 /
- 震中定位 /
- 灵敏度
Abstract: The monitoring capability of microseismic monitoring network depends on many factors, such as network layout, velocity model, seismic phase reading error, regional anomaly of travel time, positioning algorithm, equipment running state and environmental noise. Among these factors, the network layout can be artificially optimized at present stage. In order to effectively evaluate the monitoring capacity of microseismic monitoring network and optimize the network layout, the analysis and optimization method of monitoring capacity of coal mine microseismic monitoring network is proposed. This study analyzes four factors which have the greatest and most direct influence on the monitoring capability of the microseismic monitoring network. The four factors are the number of effective waveforms, the maximum gap angle, the near-station epicenter distance and the height difference between stations. It is pointed out that the number of effective waveforms, the near-station epicenter distance and the height difference between stations play a decisive role in the error of hypocenter depth solution. The number of effective waveforms and the maximum gap angle play a decisive role in the precision of epicenter positioning. According to the situation of the existing network and the working face, the distribution cloud pictures of the four factors are obtained. The monitoring capability of the microseismic network is evaluated item by item through the distribution cloud pictures of the four factors. The new network arrangement scheme is obtained through optimization of the evaluation result. The positioning error and sensitivity of the new scheme are analyzed. The epicenter positioning error, hypocenter positioning error and regional sensitivity of the whole mine are obtained. The second evaluation of the new scheme is carried out. If the secondary evaluation results meet the requirements, the new scheme can be regarded as the best network layout scheme. If the secondary evaluation results do not meet the requirements, the four factors sub item evaluation will be carried out again and the scheme will be optimized until the requirements are met. The field test results show that after the proposed method is used to optimize the microseismic monitoring network of 5307 working face in Tangkou Coal Mine, the average value of blasting hypocenter positioning error is reduced from 59.2 m to 37.2 m. The maximum value of positioning error is reduced to less than 100 m, and the blasting events with error less than 50 m account for 69.0% of the total. The results show that the proposed method can effectively improve the microseismic positioning precision and optimize the monitoring capability of the network.
- coal mine microseismic monitoring /
- microseismic monitoring network /
- network layout /
- monitoring capability /
- graded evaluation /
- hypocenter depth /
- hypocenter positioning /
- epicenter positioning /
- sensitivity

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图 1 震动波的传播

Figure 1. Propagation of shock waves

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图 2 最大空隙角

Figure 2. Maximum gap angle

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图 3 震源深度求解误差与近台震中距的关系

Figure 3. The relationship between the epicenter depth solution error and the near-station epicenter distance

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图 4 台站高差对震源深度求解精度的影响

Figure 4. Influence of height difference between stations on the accuracy of epicenter depth solution

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图 5 台网监测能力分级评价与优化流程

Figure 5. Grading evaluation and optimization process of network monitoring capability

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图 6 微震台网布置方案

Figure 6. Microseismic network layout plan

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图 7 有效波形数云图

Figure 7. Cloud map of effective waveform number

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图 8 最大空隙角云图

Figure 8. Cloud map of maximum gap angle

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图 9 近台震中距等值线

Figure 9. Contour line of near-station epicenter distance

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图 10 震源定位误差等值线

Figure 10. Contour line of hypocenter positioning error

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图 11 区域灵敏度等值线

Figure 11. Contour line of area sensitivity

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图 12 典型爆破波形

Figure 12. Typical blasting waveforms

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图 13 震源定位误差区间分布

Figure 13. The distribution of hypocenter positioning error interval

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表 1 2种情况下的台站坐标

Table 1. Station coordinates in 2 cases m

台站编号	台站无高差			台站高差合理
台站编号	x_i	y_i	z_i	x_i	y_i	z_i
1	470	450	−600	470	450	−500
2	770	450	−600	770	450	−550
3	1070	450	−600	1070	450	−600
4	1370	550	−600	1370	550	−650
5	1070	650	−600	1070	650	−700
6	770	650	−600	770	650	−560
7	470	650	−600	470	650	−620

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表 2 台网监测能力分级评价结论与改进措施

Table 2. Classification evaluation conclusions and improvement measures of network monitoring capability

研究项	评价结论	改进措施
有效波形数	台站数少	增加3个台站
最大空隙角	单侧布置	工作面后方增加S₇，S₈
近台震中距	低值区小	工作面前方增加S₆
台站高差	需要扩大	S₇，S₈位于630轨道大巷内

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表 3 优化前后台站坐标

Table 3. Station coordinates before and after optimization m

阶段	台站	x_i	y_i	z_i
优化前	T₁	39452767	3921063	−901
	T₂	39452911	3920964	−891
	T₃	39452743	3920849	−903
	S₄	39452750	3920312	−958
	S₅	39453116	3920053	−964
优化后	T₁	39452767	3921063	−901
	T₂	39453037	3920889	−888
	T₃	39452743	3920849	−903
	S₄	39452750	3920312	−958
	S₅	39453116	3920053	−964
	S₆	39453076	3920616	−889
	S₇	39452123	3920745	−958
	S₈	39451613	3921114	−949

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表 4 震源定位误差对比

Table 4. Comparison of hypocenter positioning error

对比项	误差均值/m	误差标准差/m	误差最大值/m	误差≤50 m 事件占比/%
优化前	59.2	38.7	175	45.5
优化后	37.2	23.2	96	69.0
改进度/%	37.2	40.1	45.1	51.6

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