Risk management and alarming based on a new atmospheric correction algorithm for ground-based radars - Cabrejo, A.; Bellett, P.; Stickley, G.; Silva, R.; Gunaris, Y.; Pérez, J. (Slope Stability 2020: Proceedings of the 2020 International Symposium on Slope Stability in Open Pit Mining and Civil Engineering, 2020)
For the last five years, GroundProbe has been developing a new atmospheric correction technique, which has been tested for about three years at Collahuasi mine and other mines around the world. The challenging operational and atmospheric conditions at Collahuasi have allowed GroundProbe to further calibrate the algorithms to account for some of the most difficult conditions faced by the radar onsite. Collahuasi is a large open pit in northern Chile, with a combination of severe atmospheric conditions along the year which makes it a perfect scenario for testing and calibration of the new algorithm called precision atmospherics. The algorithm was also tested in other large mine sites with challenging atmospheric conditions. A statistical analysis of the results is presented here, intending to quantify the improvement brought by the new method in regards to the reduction of noise and ability to better detect ongoing deformations. This new algorithm has been designed to overcome some of the limitations of current atmospheric correction methods that exist in the current technology while guaranteeing the same reliability of existent techniques in the market. During this testing period, we managed to compare the data from traditional GroundProbe algorithms against data from precision atmospherics on live operational mode, and the improvements in the capability of detection of rapid instabilities, and the ability to easily differentiate noise from real displacements have been highly valued. As a consequence of the improvements in the quality of the data, it is now possible to use tighter alarms during real-time monitoring, as an extra aid to the 24/7 monitoring team onsite. This allows better risk management and reduction of uncertainty.