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

Abstract

Abstract Least-Squares Monte Carlo simulation (LSM) 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 can handle more realistic valuation situations including the ability to (i) handle more realistic (probabilistic) price models and (ii) 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, 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 is typically partially offset by increasing expenditures. Hence the costs have been correlated with the gas price. The expectation of the remaining reserves is continuously adjusted 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 large value of flexibility. The Net Present Value of such an asset will underestimate the true economic value. A further benefit of using the real option valuation approach discussed here is that the valuation procedure produces a strategy map showing actions within the project, not just numbers.