Luis Montiel

Optimizing mining complexes with multiple processing and transportation alternatives: An uncertainty-based approach

Mining complexes contain multiple sequential activities that are strongly interrelated. Extracting the material from different sources may be seen as the first main activity, and any change in the sequence of extraction of the mining blocks modify the activities downstream, including blending, processing and transporting the processed material to final stocks or ports. Similarly, modifying the conditions of operation at a given processing path or the transportation systems implemented may affect the suitability of using a mining sequence previously optimized. This paper presents a method to generate mining, processing and transportation schedules that account for the previously mentioned activities (or stages) associated with the mining complex simultaneously. The method uses an initial solution generated using conventional optimizers and improves it by mean of perturbations associated to three different levels of decision: block based perturbations, operating alternative based perturbations and transportation system based perturbation. The method accounts for geological uncertainty of several deposits by considering scenarios originated from combinations of their respective stochastic orebody simulations. The implementation of the method in a multipit copper operation shows its ability to reduce deviations from capacity and blending targets while improving the expected NPV (cumulative discounted cash flows), which highlight the importance of stochastic optimizers given their ability to generate more value with less risk.

Stochastic Mine Production Scheduling with Multiple Processes: Application at Escondida Norte, Chile

Mining complexes can contain multiple mines operating simultaneously along with multiple processing streams, stockpiles and products. Stochastic optimization methods developed to date generate only local optimal solutions in the sense that they do not consider the entire mining complex. This paper presents an extension of a multi-stage method used for generating long-term risk-based mine production schedules, to operations with multiple rock types and processing streams. The developed method uses a simulated annealing based algorithm during the optimization stage, seeking to minimize deviations from production targets for waste and different ore processing streams. The proposed approach is applied at Escondida Norte copper deposit, Chile, in which sulphide, oxide, mixed and waste materials are present with milling, bio-leaching and acid-leaching being the available processing streams. The stochastic schedule generates expected deviations from mill and waste production targets smaller than 5%, which avoid indirect costs associated to idle capacities. A schedule generated conventionally exhibits expected deviations of the order of 20%.

Globally optimising open-pit and underground mining operations under geological uncertainty

A mining complex may be comprised of multiple components, including open-pit and underground operations. Traditional approaches in mine planning do not account for the various components simultaneously leading to under-value solutions. Over the last decade, some methods have been developed to incorporate multiple components of the mining value chain during optimisation. Even though these new methods incorporate more decisions and flexibility to the optimisation of a mining complex, they may either ignore uncertainties associated with the mining project or consider decisions taken before optimisation. This paper presents a method that optimises mining complexes comprised of multiple open-pits, underground operations and processing destinations. Mining, blending, processing and transportation decision variables are simultaneously optimised while accounting for geological uncertainty. The method uses a simulated annealing algorithm at different decision levels in order to generate a stochastic-based extraction sequence and processing policies. A case study shows its ability to generate a higher NPV while facing a reduced amount of risk when compared to traditional optimisation methods.

Stochastic strategic planning of open-pit mines with ore selectivity recourse

Abstract Stochastic mine planning algorithms have been extended to better represent ore selection decisions. Under geological uncertainty, existing algorithms generate plans that may violate the mineral processing capacity; under such geological scenarios, the excess ore undergoes a recourse action which is not as profitable as regular processing, hence decreasing the net present value. This decrease has previously been represented as a penalty on excess ore, which may not accurately represent actual operations. The new framework considers the most typical recourse: increasing the cut-off grade into the mineral process. This approach is demonstrated by adapting the VND algorithm of Lamghari et al.

A heuristic approach for the stochastic optimization of mine production schedules

Traditionally, mining engineers plan an open pit mine considering pre-established conditions of operation of the plant(s) derived from a previous plant optimization. By contrast, mineral processing engineers optimize the processing plants by considering a regular feed from the mine, with respect to quantity and quality of the materials. The methods implemented to optimize mine and metallurgical plans simultaneously are known in the mining industry as global or simultaneous optimizers. The development of these methods has been of major concern for the mining industry over the last decade. Some algorithms are available in commercial mining software packages however, these algorithms ignore the inherent geological uncertainty associated with the deposit being considered, which leads to shortfalls in production, quality, and expected cashflows. This paper presents a heuristic method to generate life-of-mine production schedules that consider operating alternatives for processing plants and incorporate geological uncertainty. The method uses iterative improvement by swapping periods and destinations of the mining blocks to generate the final solution. The implementation of the method at a copper deposit shows its ability to control mine and processing capacities while increasing the expected net present value by 30% when compared with a solution generated using a standard industry practice.

Simultaneously Optimizing Open-Pit and Underground Mining Operations Under Geological Uncertainty

A method that optimizes mining complexes which are comprised of multiple processing destinations, open pits and underground operations is presented. Mining, blending, processing and transportation decision variables are simultaneously optimized while accounting for geological uncertainty. The method uses a simulated annealing algorithm at different decision levels in order to generate a stochastic-based extraction sequence and processing policies. A case study shows its ability to generate a higher NPV while facing a reduced amount of risk when compared to traditional optimization methods.