NPV analysis of multiple surface constraints for pit expansion scenarios under geological uncertainty
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2019Tipo
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Abstract
To optimize a mining project, it is necessary to deal with several technical aspects and constraints, such as orebody modelling, reserve estimation, blending strategy, optimal and operational pit designs, cost control, environmental issues, among others. In this sense, locating surface infrastructures is one of the most critical mine planning concerns, as approximating these facilities to the pit in order to reduce the operational costs, might interfere with future pit expansions in new favorab ...
To optimize a mining project, it is necessary to deal with several technical aspects and constraints, such as orebody modelling, reserve estimation, blending strategy, optimal and operational pit designs, cost control, environmental issues, among others. In this sense, locating surface infrastructures is one of the most critical mine planning concerns, as approximating these facilities to the pit in order to reduce the operational costs, might interfere with future pit expansions in new favorable scenarios. In such cases, impacts on the project's net present value (NPV) are inevitable and must be technically dealt with, evaluating alternative scenarios to propose a strategy that increases profitability. The aim of this study is to evaluate, through NPV comparisons, different constrained scenarios, under geological uncertainty, determining the possibility of moving the constraints from their current position and/or defining priorities measuring the impact that each of them represents on the project's profitability. The methodology is applied to a phosphate mine, to determine the best alternative from a long-term mine planning perspective. The use of the hybrid pit approach, applied to a simulated grade model, allowed to identify the occurrence of probability zones within a mathematical pit, providing further information to support decision making regarding infrastructure relocation. ...
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REM : international engineering journal. Ouro Preto, MG. Vol. 72, no. 2 (Apr./June 2019), p. 293-300
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