Article ID Journal Published Year Pages File Type
1757060 Journal of Natural Gas Science and Engineering 2016 21 Pages PDF
Abstract

•Application of a suite of optimizers to gas and oil asset portfolios.•A strategically-based multi –objective function test to monitor portfolio performance.•Interaction of rank & cut, linear and evolutionary optimization algorithms.•Integrated, stochastic asset portfolio risk-optimization-valuation methodology driven by VBA-Excel-coded models.•Optimization displayed in terms of feasible envelopes and efficient frontiers.

Applying optimization algorithm to identify high-performing portfolios is an essential component of gas and oil portfolio analysis and decision making. As oil and gas companies wish to strategically optimize their performance with respect of multiple valuation and non-financial key performance indicators (KPIs) optimization algorithms that facilitate multi-objective optimization are desirable. The benefits of applying a suite of optimizers to mean versus semi-standard deviation stochastic multi-year cash flow and income models are explored with the aid of the hypothetical Portfolio X consisting of eleven upstream assets (with a summary dataset of mean values of KPI simulation distributions plus some general simulation input assumptions applied to the portfolio included as Appendix A). The methods and results of three distinct optimizer algorithms are compared, i.e., rank and cut, linear (Simplex) and evolutionary (genetic) algorithms in terms of a multi-KPI function test score, which is also used as the objective function for the genetic algorithm. The calculations described using the Portfolio X dataset are produced using Excel workbooks driven by VBA macros, and can be scaled up for use with larger asset sets. The results of variously constrained optimization runs using the three optimizers are further evaluated in terms of feasible-envelope and efficient-frontier concepts for value metrics, and for chances of achieving specified KPI targets on an annual basis. A risked portfolio value metric including a risk aversion factor is also derived in order to capture portfolio value and risk in a single metric. An overall portfolio analysis and valuation framework into which a suit of optimizers can meaningfully be deployed is described.

Graphical abstractSchematic illustrating how the integrated three-staged, strategic valuation and optimization of an oil and gas asset portfolio might be performed using spreadsheet models for moderate numbers of oil and gas assets. This involves a significant amount of number crunching and data handling, but if carefully structured, can provide detailed analysis using a limited number of workbooks linked by Visual Basic for Applications (VBA) macros.Figure optionsDownload full-size imageDownload high-quality image (198 K)Download as PowerPoint slide

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Physical Sciences and Engineering Earth and Planetary Sciences Earth and Planetary Sciences (General)
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