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

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.