The terms uncertainty and risk are never far off in the analysis of an exploration prospect or an oilfield investment project. Risk arises because there is uncertainty about the course of future events. Monte-Carlo simulation can be used to quantify risk. This process consists of treating uncertain input parameters of a problem as stochastic variables. All valid combinations of these input parameters are then tried, to simulate all possible outcomes. This results in specification of the model output as a statistical distribution of probable values.

The specific oilfield to which this analysis was applied is the Wilmington steamflood project previously operated by Union Pacific Resources (UPRC) at Long Beach, California. The methodology used is general and can be applied to any project which has uncertain input parameters. The software used will easily run on personal computers (PC's) and is available as an add-in program for a commonly used spreadsheet program for PC's.

Oil production rates for the steamflood had been predicted by using Ramey's generalization of Marx and Langenheim's method (SPE 29669). An economic analysis of the steamflood was carried Out using capital budgeting and discounted cash flow techniques. Monte-Carlo simulation was done for both the production rate calculations as well as the economic analysis. A statistical analysis of the oil production calculations and economic analysis was carried out, which also proved to be a sensitive method for checking the convergence of the Monte-Carlo simulation.

The simulation output consisted of probability distributions of produced oil volume, yearly cash flows, net present value (NPV) and internal rate of return (IRR) for the project.

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