Alaya created a 3D digital twin of a large client's tailings dam, which allows recommending the optimized discharge operation of tailings with high water content. This solution was developed for a copper mining company, but has the potential to be exported to any tailings dam in the world.
Water is an essential resource in mining: it is used in the comminution, mineral concentration and pulp transport processes, as well as supplying services external to the operation. In Chile, the use of water in this industry represents 3% of the country's total supply, according to the report "Water consumption in copper mining by 2019", prepared by the Directorate of Studies and Public Policies of the Chilean Commission of Copper (Cochilco). The same document indicates that many of these concessions and operations are located in areas where water scarcity is a limiting factor for regional development. For this reason, in recent years, mining companies have made an effort to improve the management of water resources within their processes.
Added to this is the concern that exists at the national level. In 2019, Chile was in 18th place in the ranking of countries with the most water stress in the world, according to the World Resources Institute (WRI). In this context, it is essential to have adequate and efficient water management for the sustainability and survival of the mining industry.
Based on the need to optimally reuse water in its processes and solve the generation of lagoons near the retaining walls of a tailings dam, a mining company opened a bidding process for the generation of proposals that included the use artificial intelligence in these processes. Until then, the company had a 2D simulator for the dam, and after Alaya was awarded this tender, they developed a process for simulating and optimizing tailings discharges in the basin, through a 3D digital twin (digital twin ).
This digital twin – a virtual representation that accurately reflects an object or physical system – simulates the behavior of the dam and deposits, providing tailings discharge recommendations "at the points that will allow them to obtain greater water recovery and where operationally the required slopes are maintained so that management continues to be optimal”, explains Pablo Salinas, Manager of New Businesses in Artificial Intelligence at Alaya.
Thus, it is possible to generate reliefs that allow the basin to be filled efficiently, predict the requirements of wall cambers and maximize the displacement of the water resource towards the recovery lagoon. In this way, the formation of parasitic lagoons is reduced and the geotechnical risks in the retaining walls are mitigated.
The development, which includes the digital twin of the dam trained with analytical techniques and artificial intelligence, gives the Operations Management dynamism for decision making. This thanks to the continuous simulation of all aspects of the dam, including the behavior of the discharges and the growth needs of the dam in the short, medium or long term.
“The mining company requested that the dam filling optimization model be accompanied by a 3D tool that would allow viewing the dam levels with the most recent information available. Thus, they see in that image which are the sectors where it would be convenient for them to deposit tailings or send material for the construction of walls”, explains Waldo Fishwick. Deputy General Manager at Alaya.
The solution is also oriented towards operational and operational safety, optimization and maximization of the recovery of the water resource, taking advantage of the useful life of the deposit and reducing the costs associated with the re-management of tailings. It also indicates precisely the exact moment when new investments in infrastructure attached to the project are required.
LiDAR topographies, conventional topographies and bathymetry are used to feed the model. Thanks to its 3D quality, it allows daily, weekly or monthly planning of the processes, and not annual, as is usually planned.
Other opportunities
Waldo Fishwick explains that other artificial intelligence solutions can be designed to optimize water use in mining. “From the analytical point of view, a mathematical function can be developed to establish the exact amount of water needed to make the material mixtures, which in turn are going to be deposited in the tailings dam. There, the client can define how much water they are going to use and not just how much water they are going to recover in the process”, he says.
There are other examples. In Peru, the miner Minsur -the third largest tin producer in the world- monitors the quality of the effluent water using artificial intelligence and in the eighth region the Penquista startup Konatec developed a technological tool to measure the flow and deformation of minerals in real time to that only the necessary water is consumed in the processes.
It is a revolution that has just begun.