即使组织没有资源瓶颈，项目筛选和排名也是不可避免的。在项目经济预测中，随机方法很普遍，并且被证明是解决技术和商业不确定性的最自然方法。与确定性方法相比，随机蒙特卡罗模拟有助于了解可能结果的范围，从而实现有效的决策。整篇论文的目的是提出一个集成的随机工作流程，解决地下、表面和成本的不确定性，以便在去风险过程的早期筛选、排名和分级机会。
所提出的工作流程可以同时通过蒙特卡罗模型解决所有技术和商业不确定性，并通过定制的经济分析工具预测一系列可能的经济结果。
Project screening and ranking is inevitable even when an organization faces no resource bottlenecks. In project economic predictions, the stochastic approach is prevalent and proves to be the most natural approach to address technical and commercial uncertainties. In contrast with a deterministic approach, a stochastic Monte Carlo simulation helps in understanding the range of possible outcomes to enable effective decision-making. The objective of the complete paper is to present an integrated stochastic work flow that addresses the subsurface, surface, and cost uncertainties to screen, rank, and grade opportunities early in the derisking process.
The proposed work flow simultaneously can address all technical and commercial uncertainties with a Monte Carlo model and predict a range of possible economic outcomes with customized economic analysis tools.
