Aplicación del modelo estadístico de Monte Carlo en la predicción del precio de los metales y valor de mineral para evaluación de rentabilidad del proyecto minero Sofía D – U.E.A. María Teresa ejecutando el método sub level stoping con relleno hidráulico cementado
Date
2020-02-18
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Journal ISSN
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Publisher
Pontificia Universidad Católica del Perú
Abstract
Hoy en día, los modelos estadísticos juegan un papel importante en las todas industrias ya que generan mayor nivel de confianza durante la toma de decisiones, dado que se basa en un análisis matemático que puede predecir diferentes escenarios para un proceso; tal es el caso de la simulación de Monte Carlo, metodología basada en la generación de números aleatorios respecto a una o más variables que forman parte de un proceso, parametrizado matemáticamente, y cuyo resultado expondrá diferentes escenarios futuros para un evento en particular.
La U.E.A. María Teresa, propiedad de Minera Colquisiri S.A., pretende explotar el proyecto de profundización “Sofía D”, a través del método de extracción “Sublevel Stoping” usando el Relleno Hidráulico Cementado (RHC) a una razón de 1,600 toneladas por día (TPD) y que a la fecha junio 2019 posee 6,596,963 toneladas métricas (TM) de reserva mineral con una ley promedio 6.85 %.
Ante el contexto descrito, la tesis desarrolla una ruta del uso de la herramienta Monte Carlo, aplicada al precio de los metales, y su posterior evaluación de rentabilidad en base al proyecto en mención. La investigación consta de tres etapas: (1) Metodología de Monte Carlo, cuyo output es la simulación de diferentes escenarios respecto a los Ingresos Brutos Anuales (IBA) para 1,600 TPD entre los años 2019 al 2032; (2) Evaluación de rentabilidad, que busca calcular los indicadores de rentabilidad, que son el Valor Actual Neto (VAN) y Tasa Interna de Retorno (TIR), cuyos inputs son los IBA, Costo Capital (CAPEX) y Costo de Operación (OPEX); y (3) Análisis de los indicadores de rentabilidad, que determinó un VAN de 99,902,835 USD con un TIR de 25.4 % que demuestran la viabilidad del proyecto y sus posibles ingresos durante su tiempo de operación. Adicionalmente, se simuló escenarios futuros para el caso de 2,500 TPD, donde se obtuvo un VAN de 153,508,993 USD con un TIR de 21.9 %, que en comparación con los indicadores de 1,600 TPD resulta una más rentable y se recomienda como una alternativa factible de operación.
En conclusión, queda demostrado que el método de Monte Carlo y su posterior análisis estadístico puede trabajar en sinergia en la evaluación de rentabilidad de un proyecto; no solo por su practicidad del método, sino también porque permite explorar escenarios futuros y en consecuencia elegir la mejor opción para una operación en particular.
Nowadays, the statistical models play an important role in all industries, since they generate a greater level of confidence during the decision making, due to it is based on mathematical analysis which can predict various scenarios for a process. Such is the case of Monte Carlo simulation, a methodology based on random samples generation relying on one or more variables which are part of one process, mathematically parameterized, and whose result will expose different future scenarios for a particular event. The A.E.U. María Teresa, Minera Colquisiri S.A. property, intends to explore the "Sofía D" deepening project through the “Sublevel Stoping” extraction method using the Cemented Hydraulic Fill (CHF) at a rate of 1,600 tons per day (TPD) and that as of June 2019 it has 6,596,963 metric tons (MT) as mineral reserve with an average grade of 6.85%. In the described context, the thesis develops a route of the use of the Monte Carlo tool, applied to the price of metals, and its subsequent evaluation of profitability based on the project in question. The investigation consists of the following three stages: (1) Monte Carlo methodology, whose output is the simulation of different scenarios with respect to the Annual Gross Income (IBA) for 1,600 TPD between the years 2019 to 2032; (2) Profitability assessment, which seeks to calculate the profitability indicators, which are the Net Present Value (NPV) and Internal Rate of Return (IRR), our inputs are IBA, Capital Cost (CAPEX) and Operating Cost (OPEX); and (3) profitability indicators analysis, which determined an NPV of USD 99,902,835 with an IRR of 25.4% that demonstrate the viability of the project and its possible income during its operating time. Furthermore, Future scenarios were simulated in the 2,500 TPD case, where an NPV of USD 153,508,993 was obtained with an IRR of 21.9%, which in comparison with the indicators of 1,600 TPD is a more profitable one and consequently is recommended as a feasible operation alternative. In conclusion, has been demonstrated that the Monte Carlo method and its subsequent statistical analysis can work in synergy in the evaluation of the profitability of a project; not only because of its practice of the method but also because it allows to explore future events and to choose the best option for a particular operation.
Nowadays, the statistical models play an important role in all industries, since they generate a greater level of confidence during the decision making, due to it is based on mathematical analysis which can predict various scenarios for a process. Such is the case of Monte Carlo simulation, a methodology based on random samples generation relying on one or more variables which are part of one process, mathematically parameterized, and whose result will expose different future scenarios for a particular event. The A.E.U. María Teresa, Minera Colquisiri S.A. property, intends to explore the "Sofía D" deepening project through the “Sublevel Stoping” extraction method using the Cemented Hydraulic Fill (CHF) at a rate of 1,600 tons per day (TPD) and that as of June 2019 it has 6,596,963 metric tons (MT) as mineral reserve with an average grade of 6.85%. In the described context, the thesis develops a route of the use of the Monte Carlo tool, applied to the price of metals, and its subsequent evaluation of profitability based on the project in question. The investigation consists of the following three stages: (1) Monte Carlo methodology, whose output is the simulation of different scenarios with respect to the Annual Gross Income (IBA) for 1,600 TPD between the years 2019 to 2032; (2) Profitability assessment, which seeks to calculate the profitability indicators, which are the Net Present Value (NPV) and Internal Rate of Return (IRR), our inputs are IBA, Capital Cost (CAPEX) and Operating Cost (OPEX); and (3) profitability indicators analysis, which determined an NPV of USD 99,902,835 with an IRR of 25.4% that demonstrate the viability of the project and its possible income during its operating time. Furthermore, Future scenarios were simulated in the 2,500 TPD case, where an NPV of USD 153,508,993 was obtained with an IRR of 21.9%, which in comparison with the indicators of 1,600 TPD is a more profitable one and consequently is recommended as a feasible operation alternative. In conclusion, has been demonstrated that the Monte Carlo method and its subsequent statistical analysis can work in synergy in the evaluation of the profitability of a project; not only because of its practice of the method but also because it allows to explore future events and to choose the best option for a particular operation.
Description
Keywords
Minería--Aspectos económicos, Metales--Precios--Rentabilidad, Método de Monte Carlo