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Artificial intelligence applied to detection of geotechnical instabilities


Deadline 05/03/2021

Closing Time

The ability to detect geotechnical instabilities today is strongly linked to two main characteristics: the precision of technologies and the technical skill of the person interpreting the measurement.

There are 3 types of detection technologies in Minera Centinela, which are the most prevalent in the mining market and have the best current technology.

The monitoring technicians have between 5 to 10 years of experience in geotechnical monitoring with high specialization in detection.

The objective of the challenge is to increase the capacity to interpret data based on AI, improving the prediction in size and time and pushing the available technology to the limit based on the continuous data that is recorded. Today detection is around 16 m.


Challenge scope

  • Increase the capacity to detect instabilities at the slope level.
  • Increase the ability to anticipate geotechnical events such as low speed falls or “sudden events”.


Background – Previous experiences 2020:

Development of algorithms to detect instabilities based on model A radar monitoring systems. Assisted detection of slope failure was up to 10-12 meters.

Keep geotechnical risks controlled:

  • Reducing the probability of non-compliance with production plans due to potential unidentified and uncontrolled geotechnical risks.
  • Increasing the accuracy in detection, which allows taking more timely measures than the current ones for the mitigation and control of instabilities to reduce the risk exposure of people.
  • Reducing non-productive times due to geotechnical alerts.

Improve productivity:

  • Do not increase the headcount and its cost for “specialized monitoring”, due to the know how of the current staff.


Operation and processes involved

Area of interest: Geotechnical

Interested management: Planning and development

Processes involved: Mining processes