Real Option Decision Rules for Oil Field Development under Market Uncertainty Using Genetic Algorithms and Monte Carlo Simulation

Abstract A decision to invest in the development of an oil reserve requires an in-depth analysis of several uncertainty factors. Such factors may involve either technical uncertainties related to the size and economic quality of the reserve, or market uncertainties. When a great number of investment alternatives are involved, the task of selecting the best alternative or a decision rule is very important and also quite complicated due to the considerable number of possibilities and parameters that must be taken into account. This work proposes a model based on Genetic Algorithms and on Monte Carlo simulation which has been designed to find an optimal decision rule for oil field development alternatives, under market uncertainty, that may help decision-making with regard to: developing a field immediately or waiting until market conditions are more favorable. This optimal decision rule is formed by three mutually exclusive alternatives which describe three exercise regions along time, up to the expiration of the concession of the field. The Monte Carlo simulation is employed within the genetic algorithm for the purpose of simulating the possible paths of oil prices up to the expiration date, and it is assumed that oil prices follow a Geometric Brownian Motion.A decision to invest in the development of an oil reserve requires an in-depth analysis of several uncertainty factors. Such factors may involve either technical uncertainties related to the size and economic quality of the reserve, or market uncertainties. When a great number of investment alternatives are involved, the task of selecting the best alternative or a decision rule is very important and also quite complicated due to the considerable number of possibilities and parameters that must be taken into account. This work proposes a model based on Genetic Algorithms and on Monte Carlo simulation which has been designed to find an optimal decision rule for oil field development alternatives, under market uncertainty, that may help decision-making with regard to: developing a field immediately or waiting until market conditions are more favorable. This optimal decision rule is formed by three mutually exclusive alternatives which describe three exercise regions along time, up to the expiration of the concession of the field. The Monte Carlo simulation is employed within the genetic algorithm for the purpose of simulating the possible paths of oil prices up to the expiration date, and it is assumed that oil prices follow a Geometric Brownian Motion.