Valuing Oil and Gas Options by Least-Squares Monte Carlo Simulation

Abstract

Summary Least-squares Monte Carlo (LSM) simulation is a promising new technique for valuing real options that has received little or no attention in the oil and gas industry. In this paper, we will demonstrate how LSM simulation can handle more-realistic valuation situations including the ability to (1) handle more-realistic (probabilistic) price models and (2) deal with multiple, possibly correlated, uncertain variables. The LSM method is applied here to an economics problem faced by many operators: What is the value of a gas field given the decision to trade the gas on the spot market as opposed to selling the gas through a long-term supply contract? A company that chooses to trade gas can decide when and how much to produce and can profit from changing market conditions, such as by increasing production during a high-price environment. Three uncertainties have been modeled: the gas price, the operational costs, and the rate of production decline. Increasing profitability associated with rising hydrocarbon prices typically is offset partially by increasing expenditures. Hence, the costs have been correlated with the gas price. The expectation of the remaining reserves is adjusted continuously on the basis of the performance of the field. The latter is simulated by stochastically modeling the rate of production decline. The paper shows that a gas field that can be produced and abandoned at will has a large value of flexibility. The net present value (NPV) of such an asset will underestimate the true economic value. A further benefit of using the real-option-valuation (ROV) approach discussed here is that the valuation procedure produces a strategy map showing actions within the project, not just numbers.