Abstract
This work addresses the long-term open-pit mine production planning. The solution for this problem indicates how and when the ore reserves will be extracted in order to maximize the value of the mining business, generating a promise that commits the mine production over time. Usually, due to the complexity of the problem, the planning process is divided into stages, generating three related problems that are sequentially solved to obtain a tentative production plan, that is: (i) determination of the final pit, which consists of delimiting the subregion of the mine where the extraction will be carried out; (ii) pushbacks selection, that corresponds to a partition of the final pit that allows to guide the sequence of extraction and to control the design; and finally, (iii) temporary production scheduling, which defines when the different zones will be extracted and which of them will be processed.
One of the disadvantages of the traditional methodology is the geological uncertainty is not taken into account, despite the great impact it can have on the production objectives. In this work we show some approaches to incorporate the uncertainty by means of conditional simulations to different stages of production planning, evaluating their impact. The results show that, on one hand, it is possible to increase the expected value of the business, and on the other hand, to reduce the risk of failure to meet production targets, allowing to generate more robust plans. In the case study presented, the results show that it is possible to obtain a discounted expected value increase of 2% and an uncertainty total cost decrease of 69% with respect to the usual methodology, which does not consider the geological uncertainty. Therefore, better decisions could be made in the long-term open pit mine production planning.
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References
Lerchs, H., Grossmann, I.: Optimal design of open-pit mines. Trans. C.I.M. 68, 17–24 (1965)
Dimitrakopoulos, R., Farrelly, C., Godoy, M.: Moving forward from traditional optimization: grade uncertainty and risk effects in open-pit design. Min. Technol. 111(1), 82–88 (2002)
Morales, N., Seguel, S., Cáceres, A., Jélvez, E., Alarcón, M.: Incorporation of geometallurgical attributes and geological uncertainty into long-term open-pit mine planning. Minerals 9(2), 108 (2019)
Emery, X., Lantuéjoul, C.: TBSIM: a computer program for conditional simulation of three-dimensional Gaussian random fields via the turning bands method. Comput. Geosci. 32(10), 1615–1628 (2006)
Ravenscroft, P.: Risk analysis for mine scheduling by conditional simulation. Trans. Inst. Min. Metall. Sect. A. Min. Ind. 101, A104–A108 (1992)
Smith, M., Dimitrakopoulos, R.: The influence of deposit uncertainty on mine production scheduling. Int. J. Surf. Min. Reclam. Environ. 13(4), 173–178 (1999)
Osanloo, M., Gholamnejad, J., Karimi, B.: Long-term open pit mine production planning: a review of models and algorithms. Int. J. Min. Reclam. Environ. 22(1), 3–35 (2008)
Jélvez, E.: Metodología multietapa para la planificación de la producción de largo plazo en minas a rajo abierto bajo incertidumbre geológica. Ph.D. thesis, Departamento de Ingeniería de Minas, Universidad de Chile, Santiago, pp. 1–189 (2017)
Godoy, M.: The efficient management of geological risk in long-term production scheduling of open pit mines. Ph.D. thesis, University of Queensland, Brisbane, pp. 1–256 (2003)
Dimitrakopoulos, R., Ramazan, S.: Stochastic integer programming for optimising long term production schedules of open pit mines: methods, application and value of stochastic solutions. Min. Technol. 117(4), 155–160 (2008)
Mai, N.L., Topal, E., Erten, O., Sommerville, B.: A new risk-based optimisation method for the iron ore production scheduling using stochastic integer programming. Resour. Policy 62, 571–579 (2018)
Jélvez, E., Morales, N., Ortíz, J.M.: Stochastic ultimate pit limit: an efficient Frontier analysis under geological uncertainty (submitted)
Rockafellar, R., Uryasev, S.: Optimization of conditional value-at-risk. J. Risk 2, 21–42 (2000)
Marcotte, D., Caron, J.: Ultimate open pit stochastic optimization. Comput. Geosci. 51, 238–246 (2013)
Jélvez, E., Morales, N., Askari-Nasab, H.: A new model for automated pushback selection. Comput. Oper. Res. (2018, in press)
Meagher, C., Dimitrakopoulos, R., Avis, D.: Optimized open pit mine design, pushbacks and the gap problem: a review. J. Min. Sci. 50(3), 508–526 (2014)
Acknowledgements
Enrique Jélvez and Nelson Morales were supported by CONICYT/PIA Project AFB180004 – Advanced Mining Technology Center – Universidad de Chile.
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Jélvez, E., Morales, N., Ortíz, J.M. (2020). Impact of Geological Uncertainty at Different Stages of the Open-Pit Mine Production Planning Process. In: Topal, E. (eds) Proceedings of the 28th International Symposium on Mine Planning and Equipment Selection - MPES 2019. MPES 2019. Springer Series in Geomechanics and Geoengineering. Springer, Cham. https://doi.org/10.1007/978-3-030-33954-8_9
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