Longjun Dong , Xianhang Yan , Jiachuang Wang , Zhen Tang , Hongwei Wang , Wentang Wu
{"title":"Case study on pre-warning and protective measures against rockbursts utilizing the microseismic method in deep underground mining","authors":"Longjun Dong , Xianhang Yan , Jiachuang Wang , Zhen Tang , Hongwei Wang , Wentang Wu","doi":"10.1016/j.jappgeo.2025.105687","DOIUrl":null,"url":null,"abstract":"<div><div>Predicting rockbursts and implementing effective protection measures are of paramount importance for safe mining in deep underground mines. A more advanced approach to recognizing rockburst hazards in underground mining involves the integration of various techniques, including microseismic (MS) parameters, localization of high-magnitude MS events, seismic tomography, deep learning models, and on-site surveys. In this study, tomography results and the distribution of MS events were utilized to identify the mining activity region and velocity anomaly in the Shaanxi Zhenao mine. Subsequently, multiple MS parameters, such as microseismic moment (MSM), microseismic energy (MSE), apparent stress (AS), b-value, S value, and comprehensive microseismicity intensity (CMSI), were examined at the 842 level. Based on these analyses, a potential rockburst area was accurately determined, and appropriate protective measures were implemented in the short term at the goaf of 842 level by integrating the results from in-site surveys, deep learning predictions, and the microseismic method. It's noted that a rockburst incident occurred in the goaf four days later; however, the adjacent area remained undamaged due to the effectiveness of the protective measures in place. This case study indicates that the utilization of MS information and deep learning models can serve as a valuable pre-warning method for assessing the risk of rockburst.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"237 ","pages":"Article 105687"},"PeriodicalIF":2.2000,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Geophysics","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0926985125000680","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Predicting rockbursts and implementing effective protection measures are of paramount importance for safe mining in deep underground mines. A more advanced approach to recognizing rockburst hazards in underground mining involves the integration of various techniques, including microseismic (MS) parameters, localization of high-magnitude MS events, seismic tomography, deep learning models, and on-site surveys. In this study, tomography results and the distribution of MS events were utilized to identify the mining activity region and velocity anomaly in the Shaanxi Zhenao mine. Subsequently, multiple MS parameters, such as microseismic moment (MSM), microseismic energy (MSE), apparent stress (AS), b-value, S value, and comprehensive microseismicity intensity (CMSI), were examined at the 842 level. Based on these analyses, a potential rockburst area was accurately determined, and appropriate protective measures were implemented in the short term at the goaf of 842 level by integrating the results from in-site surveys, deep learning predictions, and the microseismic method. It's noted that a rockburst incident occurred in the goaf four days later; however, the adjacent area remained undamaged due to the effectiveness of the protective measures in place. This case study indicates that the utilization of MS information and deep learning models can serve as a valuable pre-warning method for assessing the risk of rockburst.
期刊介绍:
The Journal of Applied Geophysics with its key objective of responding to pertinent and timely needs, places particular emphasis on methodological developments and innovative applications of geophysical techniques for addressing environmental, engineering, and hydrological problems. Related topical research in exploration geophysics and in soil and rock physics is also covered by the Journal of Applied Geophysics.