Feasibility study for seismicity forecasting in seismically active underground mines
Purpose and goal
The complexity of the physical phenomena in combination with spatial inhomogeneous and time dependent physical rock properties imply that classical methods for forecasting of natural earthquakes most likely are not applicable for the specific tasks of forecasting in mines. The main objective is to investigate and evaluate if beyond state-of-the-art techniques including Artificial Intelligence, Machine Learning and Big Data analyses can be utilized to identify parameters that have a potential for forecasting for mining-induced seismicity in a future full-scale project.
Expected results and effects
-Conclusion about the most suitable methodologies and techniques for seismicity forecasting that could be applied in mines (based on literature review and some computer tests on small data samples) -Practical guidelines for warning in the mine in case of a forecasted future seismic event -Develop an integrated approach for research on forecasting of mining-induced seismicity and full proposal for SIP STRIM project
Planned approach and implementation
-Integration of the expertise from different research areas within LTU through a new collaboration for analysis of the best practices in forecasting developed for natural earthquakes and other types of induced-seismicity and possible implementation for mining-induced seismicity. -Testing suitable approaches, procedures, and methodologies on representative data sets -Defining practical guidelines for warning in the mine in case of a expected future seismic events -Preparation of a full-scale proposal for forecasting of mining-induced seismicity