To enhance the value of open pit QRAs (Quantitative Risk Assessments), we developed a probabilistic vulnerability analysis of open pit slopes. The analysis employs a previously published semi-empirical quantitative methodology to evaluate the annualized probability of failure (PoF) of potentially unstable slopes under varying factors of safety (FoS) and maintenance levels (Contreras, Oboni, Oboni, 2024).
The analysis is based on case studies of two pit profiles in a mine in Southern Africa requiring a stability assessment under varying operational and care scenarios. The analysis encompasses four scenarios representing different degrees of maintenance and dewatering:
- Dewatered and Maintained “As Is”: Regular dewatering and maintenance activities depicting current slope stability conditions.
- Dewatered with No Maintenance: Release of monitoring and maintenance activities while maintaining dewatering efforts.
- No Maintenance, No Dewatering: Phreatic levels rise, reducing the FoS to 80% of its original value.
- Further Reduction of FoS: Extending the previous scenario with a FoS reduction to 60% of its original value, emphasizing the vulnerability of mine pit slopes under neglect or closure conditions.
Results indicate that maintenance practices, particularly dewatering, significantly influence slope stability, with decreasing levels of care leading to higher PoF. The analysis spans multiple time horizons, from annual assessments to long-term projections of five, 10, 20, and 50 years. Long-term projections reveal that while increasing FoS generally reduces PoF, scenarios with reduced maintenance and FoS exhibit persistent vulnerabilities, especially over longer time frames. This emphasizes the importance of quantifying the impacts of maintenance strategies.
Profiles in challenging geological conditions demonstrate heightened vulnerability, underscoring the necessity for tailored maintenance strategies. Comparisons with benchmark values from historical performance data of the global pit portfolio provide further insights into the effectiveness of current maintenance practices.
This analysis reaffirms the significance of contemporary standards of care within the examined pit. The approach is complemented by Bayesian updates, which allow for the integration of new data over time, refining model parameters and improving the accuracy and reliability of predictions to inform long-term operations and closure designs. This adaptive framework ensures that the analysis remains robust and reflective of real-world conditions throughout the life of the pit.
By facilitating risk-informed decision-making, the study supports efforts to achieve ALARP (As Low As Reasonably Practicable) conditions, enhancing the safety and sustainability of mining operations. The innovative methodology and its applications present a significant advancement in the field of mine slope stability analysis, offering valuable tools for practitioners and researchers alike.
