Stochastic Economic Ranking – A Prudent Way to Address Risk and Uncertainty for Decision Makers

Abstract

AbstractScreening and Ranking of opportunities based on project value and company strategy is an integral part of managing an upstream portfolio. Screening identifies those projects which meet or exceed a predetermined threshold, whereas ranking orders those projects from most desirable to least desirable. A screening criterion is necessary for investment opportunities to ensure only those investments which will contribute to achieving the desired portfolio objectives. In unconventional projects, allocating capital to emerging resource plays needs to be streamlined to ensure funding is allocated to the best opportunities taking in to account the range of uncertainty and risk at every stage. Ranking criteria are recommended for allocation of capital for deserving appraisal and pilot activities. All of the above form a quintessential part of decision making in effective portfolio management. Notwithstanding the above, a prudent method to ensure that both sub-surface uncertainty and commercial risks are addressed is through stochastic economics. Screening and ranking stochastically will provide scientific investigation of economic results aiming to understand the inter-dependency, randomness and connection between various technical and commercial inputs. This will help to ensure capital is invested on projects that yield the maximum return possible given limited available capital.Stochastic approach is that scientific investigation context of economics, where economic phenomena and connections between them are considered. Methods and techniques used to describe the movement of economic phenomena are specific to probability theory and mathematical statistics. In project economic predictions, stochastic approach is prevalent and proves to be the most natural approach to address the uncertainty by considering technical and commercial uncertainties. In contrast to a deterministic approach, a stochastic Monte Carlo simulation helps us understand the range of possible outcomes to enable effective decision making. A structured stochastic approach integrating all key variables, probability distributions, random variable functions and multiple realizations combined with a customized in-house economic evaluation workflow was completed. The aim is to help management with tangible, measurable economic metrics that will be used to graduate, rank and manage emerging play opportunities in alignment with strategic objectives.Using a structured stochastic approach, all possible combination of inputs that affects the commerciality of unconventional developments were considered. These inputs were sampled using Monte Carlo simulation and used to generate a multitude of trials. From the full range of statistical outcomes, Probability of commerciality (Pc), Expected Monetary Value (EMV) and peak funding exposure were considered as the three critical parameters that form the building blocks for ranking criteria. A swift tactical screening and ranking workflow for an unbiased quick review of opportunities was established on a revolving door basis. This study is completely based on synthetic data, for illustration purposes only.This paper will present a how traditional stochastic approach in project economics used for screening and ranking can sometimes limit management visibility of all possible outcomes in a project. The proposed stochastic work flow integrates sub-surface and commercial to provide a scientific investigation of the range of possible economic outcomes. The result is ranking criteria to assist decision makers with making informed capital allocation decisions in support of the portfolio strategy.