Long range rockburst prediction: A seismological approach |
| |
| Affiliation: | 2. National Institute of Rock Mechanics, Kolar Gold Fields, 563117 Karnataka, India;3. Department of Applied Geophysics, Indian School of Mines, Dhanbad, 826004, Bihar, India;1. Norwegian University of Science and Technology (NTNU), Trondheim, Norway;2. Mikula Geotechnics Pty. Ltd., Kalgoorlie, Australia;3. Glencore Company, Sudbury, Canada;4. The University of New South Wales (UNSW), Sydney, Australia;5. SRK Consulting, Johannesburg, South Africa;6. China University of Mining and Technology, Xuzhou, China;7. Sichuan University, Chengdu, China;1. State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, 102249, China;2. Chair of Computational Science and Simulation Technology, Faculty of Mathematics and Physics, Leibniz Universität Hannover, Hannover, 30167, Germany;1. Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization, Institute of Deep Earth Sciences and Green Energy, College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, 518060, China;2. School of Resources Environment and Safety Engineering, University of South China, Hengyang, 421001, China;3. MOE Laboratory of Deep Earth Science and Engineering, Sichuan University, Chengdu, 610065, China;4. State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource & Hydropower, Sichuan University, Chengdu, 610065, China;1. Department of Civil Engineering, Zanjan Branch, Islamic Azad University, Zanjan, Iran;2. Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran;3. Department of Civil Engineering, Technical and Engineering Faculty, Central Tehran Branch, Islamic Azad University, Tehran, Iran |
| |
| Abstract: | Rockbursts are one of the most dreadful operational hazards of mining. While it is not possible to eliminate them from deeper level mining, the risk of their occurrence and consequential losses can be minimized if the spatio-temporal occurrence of the impending rockburst can be predicted. This paper describes an empirical approach for predicting rockbursts in a mining ensemble with a lead time of 6 months, based on the analysis of past seismic data of rockbursts. The steps involved are the seismic zonation of the mine, analysis of the stress regime for finding out their migration pattern, and the number-size distribution of the past rockbursts in each zone. The projected rockburst figure matches the ones actually recorded with an accuracy of 70–80%. Even the projected location of future rockburst activity falls in line with the recorded ones. This approach is discussed with reference to the rockbursts recorded in the Champion Reef mine of the Kolar Gold Fields of India. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
