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Gold Science and Technology ›› 2020, Vol. 28 ›› Issue (2): 246-254.doi: 10.11872/j.issn.1005-2518.2020.02.022

• Mining Technology and Mine Management • Previous Articles    

Application and Research of Microseismic Monitoring Technology and Disaster Early Warning Methods in Huangtupo Copper and Zinc Mine

Mingzhi DANG1(),Jun ZHANG2,Mingtao JIA3()   

  1. 1.Xinjiang Xituo Mining Co. ，Ltd，Hami 839000，Xinjiang，China
    2.Changsha Digital Mine Information Technology Co. ，Ltd，Changsha 410083，Hunan，China
    3.School of Resources and Safety Engineering，Central South University，Changsha 410083，Hunan，China
  • Received:2019-03-18 Revised:2020-02-21 Online:2020-04-30 Published:2020-05-07
  • Contact: Mingtao JIA E-mail:dmzem@163.com;mingtao_jia@163.com

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Abstract:

Huangtupo copper and zinc mine located southwest of Hami City，Xinjiang Uygur Autonomous Region，China.It is an underground mine，and there are several goaves in the mining area.There is another mine nearby the area，which is also mining ore.The mining activities of two mines have caused a great disturbance to the pressure environment in the area.Therefore，MicroSeis microseismic monitoring system was introduced to give early warning of the ground pressure disaster that may be caused by goaves in Huangtupo copper and zinc mine.This system monitors the stability of surrounding rock around the goaves and production area in real-time.The microseismic monitoring system has the advantages of broad range，high sensitivity，non-contact，and multi-parameters analysis.In order to ensure the reliability and real-time performance of the microseismic system，the system was optimized.Using network analysis tools to optimize the best microseismic network layout scheme，than the event positioning accuracy is effectively guaranteed.In this paper，through network analysis，the optimized positioning accuracy of the center practice is about 5 m，and the positioning accuracy of the production operation area is within 10 m，which can fully meet the requirements of ground pressure monitoring and disaster early warning.Microseismic systems always pick up signals in rock masses indiscriminately.However，there are many production noise signals in the general engineering environment，such as blasting signals，mechanical vibration signals，and electrical interference signals.In the aspect of signal recognition，the traditional approach is to rely on manual methods for identification and classification，with low efficiency.Therefore，an artificial intelligence method was proposed to identify the microseismic signals.This automatic identification model ensures the real-time performance of the microseismic system and is the basis of disaster early warning.The early warning method of microseismic monitoring technology is based on quantitative seismology.Moreover，quantitative seismology is based on the development of rock mechanics，seismology，and statistics.In this paper，seismological parameters such as microseismic event activity rate，spatial distribution characteristics，seismic moment，energy，and b value were used to analyze ground pressure activity.At the same time，a set of early warning and analysis methods of microseismic monitoring ground pressure disaster was put forward.This method can realize early warning of ground pressure，provide time for evacuation of mine personnel，and effectively grasp the development trend of ground pressure.Furthermore，it can guide mine personnel to go into the mine for production in a safe time，so it has the significance of popularization in the monitoring of underground mine pressure.

Key words: goaf, the activity of ground pressure, microseismic monitoring, the disaster of ground pressure, disaster early warning

CLC Number: 

  • TD76

Fig.1

Morphology and spatial distribution of goaves in Huangtupo copper and zinc mine"

Fig.2

Architecture of microseismic monitoring system"

Fig.3

Three-layer wavelet packet decomposition"

Fig.4

Automatic identification model of micro seismic signals"

Fig.5

Location error analysis cloud"

Fig.6

Stereo positioning error analysis cloud"

Fig.7

Layout schematic diagram of microseismic monitoring station network in Huangtupo copper and zinc mine"

Table 1

Network of microseismic monitoring in Huangtupo copper and zinc mine"

传感器编号分量XYZ
1#单分量31412305.0524719700.617262.330
2#三分量31412276.8834719851.497262.806
3#单分量31412353.5594719890.239262.642
4#单分量31412269.1304719959.101263.296
5#单分量31412330.5234719701.516212.845
6#三分量31412251.3964719830.411212.821
7#单分量31412397.3844719898.546213.618
8#单分量31412255.8244719988.817213.782

Table 2

Results of blasting position error"

位置爆破测量坐标定位坐标定位误差/m
XYZXYZ
260 m中段3#穿脉31412359.634719845.432263.32131412355.094719840.27262.7496.91
222.5 m分层5#穿脉31412410.314719883.231222.53231412408.14719886.84226.0235.49
210 m中段9#穿脉31412432.574719753.899212.12531412424.454719756.31213.4068.52

Fig.8

Time series diagram of microseismic event frequency"

Fig.9

Spatial distribution of microseismic events"

Fig.10

Relationship between energy and seismic moment in the monitoring area"

Fig.11

Relationship between energy and seismic mo-ment in surrounding rock(partial) near the 3# goaf"

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