Mine Valuation Based on Sensitivity Analysis for an Open Pit Gold Mine

In the realm of open-pit gold mining, it is imperative to conduct a thorough analysis of diverse factors influencing the success or potential economical failure of a mining project, aiming to avoid decisions that might lead to such failures. Net present value (NPV) stands as a crucial indicator offering profound insights into the project's future, with risk considered an inherent component of its evaluation. This study delves into sensitivity analysis, a potent tool enabling a comprehensive understanding of how alterations in project parameters can affect the outcomes. Unlike risk analysis, sensitivity analysis treats each parameter independently, implying that a change in one parameter does not impact the outcome of others. This paper demonstrates a sensitivity analysis of key factors such as price of gold, mining and processing costs, and recovery rates to study their influence on the NPV of open-pit gold mining project. Through rigorous Python-based simulations, similar to Monte Carlo simulation but distinct in its approach, a diverse set of logical input scenarios has been generated to gauge the effect on the NPV. This approach focuses on identifying the most impactful factors by treating them independently, altering one while others are kept constant. Additionally, these experiments were replicated using integrated mining software to compare the results. This investigation aims to shed light on the advantages of utilizing Python's computational capabilities for efficient and streamlined sensitivity analysis in comparison to conventional software. A notable discovery was that alterations in gold price wielded the most significant influence on a project's success. This discernment empowers stakeholders to make informed decisions and effectively manage risks within the gold mining industry.