AI for predictive monitoring of tailings storage facilities
10 June 2021

Ensure the safety and reliability of your tailings dam or storage facility with AI predictive analytics

It is imperative that mining operators ensure the safety and compliance of all types of tailings storage facilities, be it ponds, dams, paste tailings, dry stacking or underground storage. Throughout history, the failure of tailings storage facilities have caused significant disasters, with severe human and environmental casualties.  One of the recent disasters was at the Vale SA iron ore mine in Brumadinho Brazil, in 2019, which killed 259 people and released about 12 million cubic meters of tailings with long term ecological impact on over 300kms of the São Francisco River.

In the last decade there have been 37 major tailings dam failures1, and the World Mine Tailings Failures (WMTF) states that these events are becoming more frequent and are predicted to have more devastating impacts as the cumulative tailings depositions continue to grow exponentially. 

Tailings storage facilities play an important role in mine waste management, storing sludge and toxic metals and minerals.  As the world continues to mine massive amounts of metals and minerals, the volume of the waste increases, this is further amplified as lower grades are mined which contain a larger volume of waste.  It is essential that this waste isn’t released into the atmosphere or waterways as it will have a long-term ecological impact.

Dam’s containing tailings have historically failed more than 100 times the rate of water-holding dams.2 In particular, upstream dams which are constructed  during the life of the mine are at greater risk of failure from an increased weight being added to the original starter dam.

Increased safety and compliance measures are being enforced to help the mining industry construct, monitor and maintain tailing storage facilities with multiple sources of data. The accurate analysis of this data in real time can help engineers significantly in their important role of ensuring the structural integrity, safety and reliability of these facilities while ensuring and demonstrating compliance to regulations.  

VROC’s AI platform can provide mine operators with the live monitoring and predictive analysis in real time which would allow the early identification of anomalies.  By analysing all available data, including weather data, the AI can provide future predictions on critical elements such as liquefied tailings, water levels, drainage, overflow, water discharge, structural integrity and stability, dust and seismic activity.

Advanced notification of deviations and future faults allows mining operators and engineers the critical time to intervene and prevent disasters.

VROC is pleased to be able to provide mining operators with critical insights to ensure the safety of these facilities, and help prevent future failures which put both the environment and our communities at risk.

Get in touch with our team to learn how your existing tailings storage data can be used to help you monitor and maintain the safety of your facility, or learn more about our mining solutions here.




References:

  1. https://www.wise-uranium.org/mdaf.html
  2. https://www.sciencemag.org/news/2020/08/catastrophic-failures-raise-alarm-about-dams-containing-muddy-mine-wastes
  3. https://worldminetailingsfailures.org/
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