Considerations on Forecasting the time of failure of Tailings Dams and a heap leach facility through Satellite InSAR Data

This work addresses the complex challenge of forecasting the Time of Failure (ToF) for tailings dam and a heap leach facility using Satellite InSAR data. These structures can be susceptible to sudden instabilities due to the contractive and brittle behavior of tailings, and constant remodeling in mining areas can introduce bias in data retrieval from satellites. Moreover, these structures are seldom monitored and the cost-effective coverage of satellite InSAR data can be a useful tool to deploy. 

We developed a probabilistic and multi-model approach to forecast ToF and assess the confidence of these predictions, both qualitatively and quantitatively. Our method, the Reiterative Algorithm (RA), provides ToF forecasts using different forecasting method employing iteratively each new data available and yielding a broad range of predictions. The main purpose of this methodology is to fully exploit the predictive potential from slight acceleration signals before failure, monitored with low-temporal resolution instruments such as Satellite InSAR. Some recent papers claim the possibility of predicting brittle failures of such structures.   

Emphasis is placed on both the predictability of failure occurrence and the confidence of these forecasts, which is crucial for issuing warnings. 

Results are presented for four tailings dam – Dam B1 at the Córrego do Feijão mine in the town of Brumadinho (Brazil), Jagersfontein tailings dam (South Africa), NTSF Embankment at Cadia (Australia), and Zelazny Most (Poland) - and a heap leach facility at Copler Mine (Turkey). All except Zelazny Most experienced failure.

The findings advance the understandings of ToF predictability and highlight the need for further research to improve the accuracy of such forecasts.