PROBABILISTIC DECISION ANALYSIS USING LEAST SQUARES MONTE CARLO SIMULATION

摘要

Oil and gas operators commonly use a "one size fits all" single corporate discount rate method for valuing uncertainty in the PSC Block Evaluation. A new approach is introduced as an alternative tool for PSC block evaluation, one where uncertainty variables and strategic decisions options are incorporated into the evaluation process. Through this new approach, we can move beyond the static "now or never" decision framework that is implicit in most current analysis to an explicit modeling and analysis, using Least Squares Monte Carlo simulation (LSM) approach, to examine the effects of the contingent decision sequences that actually occur in most business situations. This paper aims to demonstrate that the conventional Net Present Value (NPV) can under-or over-estimate the true economic value of an asset and could lead to a decision to continued operate under sub-economic conditions or to pre-maturely dispose / abandon the field. This paper will also demonstrate how LSM can handle more realistic valuation situations, including the ability to incorporate strategic options, uncertainties and risks. Least Squares Monte Carlo simulation (LSM) is a promising technique for valuing assets, one that should be used in the oil and gas industry.