scholarly journals A dynamic stochastic programming approach for open-pit mine planning with geological and commodity price uncertainty

2020 ◽  
Vol 65 ◽  
pp. 101570 ◽  
Author(s):  
Adrien Rimélé ◽  
Roussos Dimitrakopoulos ◽  
Michel Gamache
2021 ◽  
Vol 6 (2) ◽  
pp. 142-150
Author(s):  
Fontes MP ◽  
Koppe JC ◽  
Silva Neto JA

Long-term open pit mine planning is a complex process which deals with numerous uncertainties, whether they are economical (commodity price, operational costs, production schedule, discount rate, inflation, among others); geological (grade distribution, density, hardness, etc); or physical constraints (property limits, environmental issues, legislation, etc). In this context, this paper aims to evaluate the effects of the variation of two important variables: commodity price and discount rate, with regard to the economic criterion, represented by the Net Present Value (NPV) of the mining business. Starting from a baseline value of US$ 80/t, the commodity (phosphate rock was used as a case study) price was varied within a 50% range, above and below the baseline value, obtained from historic values from the last 5 years. The discount rate values adopted in the analyses were 6%, 8%, 10%, 12%, 14%, 16%, 18% and 20%. The results showed increases in the market price yielded higher NPV and life of mine values. On the other hand, it was noted that increases in the discount rate can significantly alter the NPV, materially reducing the value of the mining undertaking. It is also worth noting that, in contrast to more robust approaches such as Real Options Theory (ROT), traditional Discounted Cash Flow (DCF) methods, such as NPV, assume variables, such as commodity price, to be fixed, which could either lead to the undervaluation or overvaluation of a project.


2019 ◽  
Vol 4 (10) ◽  
pp. 1740-1747
Author(s):  
Hanxi Bao ◽  
Zhiqiang Zhou ◽  
Georgios Kotsalis ◽  
Guanghui Lan ◽  
Zhaohui Tong

Herein we address the feedstock uncertainty for a robust lignin valorization process through a dynamic stochastic programming approach.


2009 ◽  
Vol 19 (6) ◽  
pp. 709-717 ◽  
Author(s):  
Afshin Dehkharghani AKBARI ◽  
Morteza OSANLOO ◽  
Mohsen Akbarpour SHIRAZI

Minerals ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 108 ◽  
Author(s):  
Nelson Morales ◽  
Sebastián Seguel ◽  
Alejandro Cáceres ◽  
Enrique Jélvez ◽  
Maximiliano Alarcón

Long-term open-pit mine planning is a critical stage of a mining project that seeks to establish the best strategy for extracting mineral resources, based on the assumption of several economic, geological and operational parameters. Conventionally, during this process it is common to use deterministic resource models to estimate in situ ore grades and to assume average values for geometallurgical variables. These assumptions cause risks that may negatively impact on the planned production and finally on the project value. This paper addresses the long-term planning of an open-pit mine considering (i) the incorporation of geometallurgical models given by equiprobable scenarios that allow for the assessing of the spatial variability and the uncertainty of the mineral deposit, and (ii) the use of stochastic integer programming model for risk analysis in direct block scheduling, considering the scenarios simultaneously. The methodology comprises two stages: pit optimization to generate initial ultimate pit limit per scenario and then to define a single ultimate pit based on reliability, and stochastic life-of-mine production scheduling to define block extraction sequences within the reliability ultimate pit to maximize the expected discounted value and minimize the total cost of production objective deviations. To evaluate the effect of the geometallurgical information, both stages consider different optimization strategies that depend on the economic model to be used and the type of processing constraints established in the scheduling. The results show that geometallurgical data with their associated uncertainties can change the decisions regarding pit limits and production schedule and, consequently, to impact the financial outcomes.


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