Correlating the Returns of Oil-Producing Projects Realistically

Abstract

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 150909, ’How To Measure the Correlation Between Return of Oil-Production Projects Realistically,’ by G.A. Costa Lima, SPE, A.T. Gaspar Ravagnani, SPE, and D.J. Schiozer, SPE, Unicamp, prepared for the 2012 North Africa Technical Conference and Exhibition, Cairo, 20-22 February. The paper has not been peer reviewed. Portfolio theory has been an important tool for economic-risk management. There are only three input parameters: mean return, standard deviation of return, and correlation between pairs of such things as assets, projects, and prospects. Although the model is simple, a problem with it is estimating the correlation because there are no historical data. Alternatively, correlation on return of projects is assumed subjective (typically 70%), but with this model it can be estimated in a much more sound way. Results indicate that the main determinants of correlation are fixed cost, variable cost, and oil quality. With this information, managers can select best portfolios (e.g., by means of farm in and farm out) to create value for stakeholders considering means, risk, and possible benefits from diversification. Introduction Often, decision makers must manage portfolios containing many projects, including exploration, development, production, and decommissioning. The life span of these portfolios is similar to that of the company, possibly several decades. Most company portfolios are updated yearly. In this process, the return to stakeholders depends on such factors as the skill of decision makers to add and remove projects, performance of individual projects (and the synergistic interaction in terms of geologic features), operating infrastructure, and marketing conditions. In portfolio management, decisions are made on the basis of the mean and standard deviation (risk) of the rate of return of investments. The risk depends on the standard deviation of each individual asset, correlation between pairs of assets, proportion of investment allocated in each asset, and the number of assets in the portfolio. Of these variables, only the risk of the individual asset is beyond the manager’s control because it depends on variables such as oil production, operating cost, fiscal regime, reservoir conditions, and geologic aspects; therefore, it is called systematic risk. The use of portfolio theory to solve real-world problems depends strongly on calculations/estimations of correlations. Therefore, the focus in this paper is on the methodology to estimate correlations between pairs of net present value (NPV) of oil projects. Correlation vs. Diversification Consider an oil company with an opportunity to construct a portfolio having two oil-production projects. Initially, professionals complete a traditional economic analysis at the project level to estimate mean and standard deviation of the NPV of each project. Results of this initial analysis are shown in Table 1.