# Microseismic Electronic Fencing for Monitoring of Transboundary Mining in Mines
## 4 Discussion and Recommendations  
(1) A microseismic electronic fence system, combining both well and surface sensors for monitoring cross-boundary mining, is proposed, comprising sensors deployed both on the ground and in the wells. The surface sensors are arranged in two nested near-circular observation systems, one inside and one outside the mine boundary. This observation system focuses on localizing microseismic events at the mine boundary, making it effective for monitoring transboundary and cross-stratigraphic mining activities.  
The feasibility of the nested observation system is analyzed through numerical simulations and implemented in real-world projects, and the results indicate that the system holds promising application prospects for mine transboundary mining supervision.  
(2) Three different localization algorithms are compared and analyzed. Based on the testing of simulated and measured data, it is evident that the grid search method and simplex method demonstrate higher localization accuracy for monitoring, while the Geiger method is less effective due to its dependence on the initial value of the seismic source. Therefore, grid search and simplex algorithms are recommended for monitoring cross-boundary and cross-stratum mining, and simplex methods are highly recommended when the target area is large.  
(3) The vibration signals used for source localization in the analysis of measured data are the more energetic blast signals, for which the first arrival times are more readily available. However, in practical applications, there may be many kinds of effective signals, such as signals generated by mining activities and transportation vehicles, etc., which are  
Figure 7: Localization results: (**a**) seismic event distribution (**b**) horizontal direction (**c**) vertical direction.  
characterized by a low signal-to-noise ratio. How to utilize such signals for monitoring will be a future research goal.  
Conceptualization, D.Z., G.L. and L.L.; methodology, L.L.; software, J.Y., D.Z. and L.L.; validation, J.Y.; formal analysis, J.Y.; investigation, J.Y.; resources, G.L.; data curation, J.Y.; writing--original draft preparation, J.Y.; writing--review and editing, J.Y. and D.Z.; visualization, J.Y.; supervision, G.L. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Natural Science Foundation of China, grant number 41974148; the Natural Resources Science and Technology Project of Hunan Province, grant No. 2022-01; the Science and Technology Research and Development Project of China Railway Co., Ltd., grant No. 2022-Special-07. the National Key R&D Program, grant No. 2023 YFP0718000; the Natural Science Foundation of Hunan Province, grant No. 2023 JJ30663; and in part by The Changzhou Science and Technology Support Project, grant No. CE20235069.  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
We are grateful to the faculty for their guidance, to the reviewers for their suggested revisions, and to the editorial board for their support!  
The authors declare no conflicts of interest.