Microseismic Monitoring and Disaster Warning via Mining and Filling Processes of Residual Hazardous Ore Bodies
<p>Project overview. (<b>a</b>) Mine location. (<b>b</b>) Ore body occurrence. (<b>c</b>) Goaf. (<b>d</b>) Pillar.</p> "> Figure 2
<p>Sensor position relationship and monitoring system network topology diagram within the microseismic monitoring area.</p> "> Figure 3
<p>Simplified diagram of residual ore body mining.</p> "> Figure 4
<p>The eastern and western parts of the mine and the overall ore output. (<b>a</b>) 2013–2018. (<b>b</b>) In the months of 2018.</p> "> Figure 5
<p>Comparison chart of actual ore production and filling volume underground.</p> "> Figure 6
<p>Spatial distribution of underground microseismic positioning events from 2013 to 2018.</p> "> Figure 7
<p>The magnitude frequency cumulative relationship and its fitting formula for microseismic positioning events.</p> "> Figure 8
<p>Probability distribution of cumulative occurrence of extreme magnitude values in 2019.</p> "> Figure 9
<p>Probability density distribution of extreme magnitude events in 2019.</p> "> Figure 10
<p>Probability index (P) distribution of microseismic energy release in 2019.</p> "> Figure 11
<p>Establishment of precursor patterns: (<b>A</b>) Time window for roof collapse occurrence; (<b>B</b>) Microseismic event rate curve; (<b>C</b>) Time window for roof collapse occurrence.</p> "> Figure 12
<p>37# probe area empty zone distribution map.</p> "> Figure 13
<p>Trend chart of microseismic event rate for probe 37#.</p> "> Figure 14
<p>Photos of roof-caving site.</p> "> Figure 15
<p>Description of the destruction of the goaf where the 43# probe is located.</p> "> Figure 16
<p>Microseismic event rate variation near probe 43#.</p> ">
Abstract
:1. Introduction
2. Engineering Background and Microseismic Monitoring
2.1. Summary of Engineering Background
2.2. Monitoring Network
3. Analysis of the Mining and Filling Process of Residual Ore Bodies in the Goaf
3.1. Mining Scale
3.2. Filling Volume
3.3. The Process of Mining and Filling and Its Proportional Relationship
4. Microseismic Data and Ground-Pressure Warning Analysis
4.1. Multi-Parameter Analysis of Microseismic Monitoring
4.1.1. Statistics and Evaluation of b-Value
- Theoretical basis for frequency magnitude relationship and b-value
- 2.
- Statistical analysis of magnitude and energy
- 3.
- Analysis of the magnitude, energy, and b-value of the mine
4.1.2. Extreme Distribution of Maximum Magnitude Based on the Gambell Distribution Model
4.1.3. Probability Analysis of Stability and Microseismic Energy Release
4.2. Construction of Warning Modes and Mechanisms
4.2.1. Microseismic Warning Precursor Mode
4.2.2. Mechanism of Precursor Mode
4.3. Early Warning and Reliability Analysis
4.4. Warning Cases
4.4.1. 37# Probe Case
4.4.2. 43# Probe Case
5. Conclusions
- (1)
- By studying the engineering location overview and microseismic monitoring network in on-site work and microseismic monitoring, we have gained a deeper understanding of the characteristics of the geological environment and the deployment of monitoring systems. The analysis of the engineering location overview provides us with a comprehensive understanding of geological conditions and engineering structures, laying the foundation for subsequent research. The construction of microseismic monitoring networks provides us with real-time monitoring and data support, helping us to more accurately grasp the dynamic changes of underground microseismic activities and providing a solid foundation and support for the prevention and early warning of geological disasters.
- (2)
- The mining and filling process of residual ore bodies in goaf is a complex engineering system that requires comprehensive consideration of multiple factors such as mining scale, filling volume, and mining filling ratio. Through in-depth analysis of these factors and case studies, we can better understand the inherent laws of the mining and filling process, providing a scientific basis for achieving efficient resource utilization and safe environmental protection.
- (3)
- Microseismic monitoring technology is crucial for mine safety production. It improves the accuracy of predicting ground-pressure activities through multi-parameter analysis, provides a scientific decision-making basis for mine managers, and effectively reduces geological disasters. The constructed warning mode and mechanism can quickly respond to the initial occurrence of ground-pressure anomalies, ensuring the safety of personnel and equipment. Continuous reliability analysis and system optimization ensure the stable operation of the early warning system in complex environments, improving the accuracy and timeliness of early warning. The combination of these technologies and methods provides a solid guarantee for mine safety production. With the continuous development of technology, microseismic monitoring will play a greater role in preventing ground-pressure disasters.
- (4)
- By analyzing actual warning cases, the performance of the warning system can be further improved. Successful warning cases not only validate the effectiveness of the warning model but also provide us with valuable practical experience. By comparing and analyzing different cases, shortcomings in the early warning system can be identified, providing direction for future improvement and upgrading.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Year | Eastern Residual Mining Area | Western Regular Mining Area | Total Exposed Area Covered | Percentage of Coverage Area |
---|---|---|---|---|
2013 | 1.10 | 0 | 1.10 | 3.25% |
2014 | 1.10 | 0.31 | 1.41 | 4.17% |
2015 | 2.12 | 0.36 | 2.48 | 7.33% |
2016 | 2.45 | 0.50 | 2.95 | 8.72% |
2017 | 3.21 | 0.28 | 3.49 | 10.32% |
2018 | 2.92 | 1.15 | 4.07 | 12.03% |
Total | 12.90 | 2.60 | 15.50 | 45.82% |
Year | Mining Volume (10,000 tons) | Increase in Space ∆Ve | Filling Volume ∆Vf | Empty Area Variation ∆Vr | Reduction of the Percentage of Space Volume |
---|---|---|---|---|---|
2013 | 61.71 | 19.34 | 11.96 | 7.34 | * |
2014 | 43.16 | 14.27 | 20.00 | −6.23 | 2.07% |
2015 | 46.61 | 15.03 | 24.70 | −8.77 | 2.92% |
2016 | 47.73 | 15.06 | 34.90 | −19.88 | 6.63% |
2017 | 45.39 | 14.84 | 30.15 | −15.31 | 5.10% |
2018 | 45.51 | 14.26 | 34.70 | −20.44 | 6.81% |
Total | 290.11 | 92.8 | 156.36 | −63.29 | 21.10% |
No. | Date | Energy/J | Local Magnitude | No. | Date | Energy/J | Local Magnitude |
---|---|---|---|---|---|---|---|
1 | 1 February 2013 | 562.00 | −1.72 | 62 | 11 July 2013 | 84.60 | −2.02 |
2 | 2 March 2013 | 4.36 | −2.81 | 63 | 11 July 2013 | 69.80 | −2.22 |
3 | 12 March 2013 | 995.00 | −1.25 | 64 | 14 July 2013 | 9.86 | −2.39 |
4 | 30 March 2013 | 323.00 | −1.71 | 65 | 29 July 2013 | 13.30 | −2.38 |
5 | 31 March 2013 | 17.90 | −2.64 | 66 | 2 August 2013 | 24.80 | −2.07 |
6 | 31 March 2013 | 0.29 | −3.35 | 67 | 4 August 2013 | 0.35 | −3.58 |
7 | 31 March 2013 | 0.16 | −3.71 | 68 | 18 August 2013 | 1.72 | −3.17 |
8 | 31 March 2013 | 14.70 | −2.62 | 69 | 1 December 2013 | 24.20 | −2.42 |
9 | 31 March 2013 | 23.80 | −2.43 | 70 | 21 December 2013 | 280.00 | −1.59 |
10 | 31 March 2013 | 0.19 | −3.73 | 71 | 9 May 2014 | 0.74 | −3.16 |
11 | 6 April 2013 | 0.04 | −3.90 | 72 | 6 June 2014 | 22.00 | −3.02 |
12 | 6 April 2013 | 0.05 | −3.94 | 73 | 12 August 2014 | 1.64 | −3.08 |
13 | 6 April 2013 | 0.07 | −4.54 | 74 | 19 August 2014 | 7.39 | −2.59 |
14 | 8 April 2013 | 0.24 | −3.71 | 75 | 28 April 2016 | 3.35 | −2.88 |
15 | 8 April 2013 | 0.28 | −3.60 | 76 | 4 July 2016 | 0.63 | −3.54 |
16 | 3 May 2013 | 153.00 | −1.78 | 77 | 4 July 2016 | 0.04 | −4.16 |
17 | 21 June 2013 | 18.90 | −2.52 | 78 | 21 July 2016 | 0.08 | −3.95 |
18 | 28 June 2013 | 4.12 | −2.52 | 79 | 21 July 2016 | 0.10 | −4.07 |
19 | 28 June 2013 | 869.00 | −0.78 | 80 | 2 August 2016 | 151.00 | −1.84 |
20 | 28 June 2013 | 210.00 | −1.73 | 81 | 31 October 2016 | 2.87 | −2.01 |
21 | 28 June 2013 | 73.60 | −1.55 | 82 | 11 February 2017 | 21.00 | −2.89 |
22 | 29 June 2013 | 2.48 | −3.40 | 83 | 4 June 2017 | 102.00 | −1.98 |
23 | 2 July 2013 | 2.22 | −3.02 | 84 | 4 June 2017 | 14.50 | −2.36 |
24 | 2 July 2013 | 16.20 | −2.32 | 85 | 13 June 2017 | 4.82 | −3.14 |
25 | 3 July 2013 | 5.62 | −2.86 | 86 | 1 July 2017 | 7.19 | −2.44 |
26 | 3 July 2013 | 5.68 | −2.72 | 87 | 3 September 2017 | 85.20 | −2.66 |
27 | 3 July 2013 | 229.00 | −1.83 | 88 | 4 November 2017 | 4.51 | −2.72 |
28 | 3 July 2013 | 28.20 | −2.38 | 89 | 5 June 2018 | 2.99 | −2.83 |
29 | 3 July 2013 | 27.40 | −2.30 | 90 | 14 June 2018 | 1.38 | −3.15 |
30 | 3 July 2013 | 0.16 | −3.93 | 91 | 141 June 2018 | 0.25 | −3.81 |
31 | 3 July 2013 | 0.24 | −3.81 | 92 | 22 June 2018 | 0.01 | −3.59 |
32 | 3 July 2013 | 0.46 | −3.37 | 93 | 20 August 2018 | 119.00 | −2.20 |
33 | 3 July 2013 | 112.00 | −2.53 | 94 | 3 October 2018 | 6.20 | −2.59 |
34 | 3 July 2013 | 134.00 | −1.94 | 95 | 3 October 2018 | 125.00 | −1.58 |
35 | 3 July 2013 | 7.05 | −2.68 | 96 | 8 October 2018 | 9.19 | −2.58 |
36 | 3 July 2013 | 13.70 | −2.80 | 97 | 12 October 2018 | 0.06 | −4.12 |
37 | 4 July 2013 | 0.60 | −3.10 | 98 | 16 October 2018 | 1.42 | −3.33 |
38 | 4 July 2013 | 6.08 | −3.06 | 99 | 22 October 2018 | 0.09 | −3.88 |
39 | 4 July 2013 | 31.50 | −2.36 | 100 | 27 October 2018 | 4.42 | −2.79 |
40 | 4 July 2013 | 240.00 | −2.16 | 101 | 27 October 2018 | 4.27 | −2.98 |
41 | 4 July 2013 | 1.50 | −3.07 | 102 | 27 October 2018 | 1.63 | −3.06 |
42 | 4 July 2013 | 11.90 | −2.78 | 103 | 27 October 2018 | 1.36 | −3.30 |
43 | 6 July 2013 | 53.40 | −1.74 | 104 | 27 October 2018 | 6.43 | −2.81 |
44 | 6 July 2013 | 3.09 | −2.90 | 105 | 27 October 2018 | 0.21 | −3.87 |
45 | 6 July 2013 | 39.40 | −1.90 | 106 | 27 October 2018 | 0.55 | −3.79 |
46 | 6 July 2013 | 115.00 | −1.58 | 107 | 27 October 2018 | 1.95 | −3.21 |
47 | 7 July 2013 | 36.60 | −2.42 | 108 | 27 October 2018 | 12.30 | −2.51 |
48 | 8 July 2013 | 3.71 | −2.36 | 109 | 27 October 2018 | 0.61 | −3.69 |
49 | 8 July 2013 | 3.27 | −3.19 | 110 | 27 October 2018 | 1.01 | −3.44 |
50 | 9 July 2013 | 0.09 | −3.90 | 111 | 27 October 2018 | 0.12 | −4.24 |
51 | 9 July 2013 | 0.51 | −3.59 | 112 | 27 October 2018 | 6.06 | −2.56 |
52 | 9 July 2013 | 67.90 | −2.36 | 113 | 27 October 2018 | 0.28 | −3.87 |
53 | 9 July 2013 | 81.80 | −2.41 | 114 | 27 October 2018 | 3.46 | −2.81 |
54 | 9 July 2013 | 315.00 | −1.67 | 115 | 27 October 2018 | 0.16 | −3.95 |
55 | 10 July 2013 | 5.65 | −2.43 | 116 | 27 October 2018 | 4290.00 | −0.37 |
56 | 10 July 2013 | 3.29 | −2.93 | 117 | 9 November 2018 | 0.94 | −3.32 |
57 | 10 July 2013 | 3.84 | −2.84 | 118 | 11 November 2018 | 2.79 | −2.92 |
58 | 11 July 2013 | 0.28 | −3.85 | 119 | 11 November 2018 | 3.54 | −2.87 |
59 | 11 July 2013 | 0.14 | −3.54 | 120 | 14 November 2018 | 24.10 | −2.60 |
60 | 11 July 2013 | 0.24 | −3.70 | 121 | 18 November 2018 | 0.15 | −3.83 |
61 | 11 July 2013 | 0.30 | −3.98 | 122 | 13 December 2018 | 460.00 | −1.27 |
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Zhou, Z.; Huang, Y.; Zhao, C. Microseismic Monitoring and Disaster Warning via Mining and Filling Processes of Residual Hazardous Ore Bodies. Minerals 2024, 14, 948. https://doi.org/10.3390/min14090948
Zhou Z, Huang Y, Zhao C. Microseismic Monitoring and Disaster Warning via Mining and Filling Processes of Residual Hazardous Ore Bodies. Minerals. 2024; 14(9):948. https://doi.org/10.3390/min14090948
Chicago/Turabian StyleZhou, Zilong, Yinghua Huang, and Congcong Zhao. 2024. "Microseismic Monitoring and Disaster Warning via Mining and Filling Processes of Residual Hazardous Ore Bodies" Minerals 14, no. 9: 948. https://doi.org/10.3390/min14090948
APA StyleZhou, Z., Huang, Y., & Zhao, C. (2024). Microseismic Monitoring and Disaster Warning via Mining and Filling Processes of Residual Hazardous Ore Bodies. Minerals, 14(9), 948. https://doi.org/10.3390/min14090948