Deep mining, driven by the increasing need of the sustainable use of mineral resources, yields a chance to exploit untapped resources. Nevertheless, large depths remain challenging and complex environment, posing geotechnical risks such as stress driven damage. The violent damage mechanisms in deep mines are spalling and strainburst in their most severe forms. Real-time monitoring can not only assist in preventing a failure, but can also assist in post failure mitigations. It can help identify the possible systemic failure of adjacent areas and can therefore help is evacuating people and machinery from these areas. The long-term goal is to develop a real-time risk management concept for intelligent deep mines. The objective of this paper is to summarize the outcomes of I2Mine and DynaMine, formulate a risk concept suitable for real-time analysis and to produce a tangible measure of the risk levels. In this paper the Fault Tree – Event Tree methodology is proposed and an example is worked out using strainburst as an example risk case. The proposed methodology seems to work well and using a scenario with both property damage and ore loss, the risk expressed as financial consequences multiplied with probability drops from $128,621 to $25,766 corresponding to a -80% reduction in risk. The financial consequences together with the associated risk level can be expressed visually using a modified FN graph with financial loss on x-axis and probability on the y-axis. The developed geotechnical risk management concept suits the need of semi-automated or fully automated risk management. It would fit well in the analysis stage of the raw data and would produce a stress state change, which could be used as input in the risk management chain for intelligent deep mines.
|Conference||ISRM European Rock Mechanics Symposium|
|Ajanjakso||20/06/2017 → 22/06/2017|