Monte Carlo Simulation. Monte Carlo simulation has been used for risk analysis since 1940s which is an important statistical technique to evaluate the uncertainty (X. Xxxxxx, X.X. Xxxxxxx and X. Xxxxxx, et al., 2007). In general, Monte Carlo simulation uses repeated random sampling of key primary variable that may have great impact on NPV and makes strategies through analyzing the probability distributions of the cash flows or NPV. It is widely used in petroleum industry for dealing with uncertainty in investment decisions. Typically, in some real investment projects, managers may have an idea about the range of values but not aware of the meaning of exact numbers. Monte Carlo simulation could generate any number of forecasts by the overall cash flow distribution. Monte Carlo simulation usually follows these steps when implementing in petroleum sector (Xxxxxxxxxx Xxxxx, 1996).
Step 1: Create a cash flow model of the project, using a set of mathematical equations and identifying all important cash flow components such as temperature or volume structures in the actual pipes. The objective of this model is to maximize the total net present value for all involved fields including transportation costs. Step 2: Based on the past data, specify probability of distribution of each important component which is heavily impacted by uncertainty. Step 3: Try to determine discount rates and discount method.
Monte Carlo Simulation. Monte Carlo simulation is a computerized mathematical technique that gives to the project team a range of possible outcomes and the probabilities they will occur for any choice of action. This is very useful when there are multiple scenarios and it is important to determine what are the statistically correct outcomes for each scenario. The technique was first used while working on the atom bomb; it was named for Monte Carlo, the Monaco resort town renowned for its casinos.
