Valuing investments in agile project design : example for upstream oil and gas development

Abstract

Traditional oil and gas companies will continue to face market uncertainties in the coming decades. With increased pressure to confront climate change and energy technology innovations, the future demand and pricing for petroleum products is unclear. Hydrocarbons will continue to play a part in the changing energy landscape. However, companies will need to revisit what capital is spent on and how they spend it. Instead of tying up capital in a one-time massive investment decision, made under long term assumptions, agile investing gives power back to the business decision maker. This thesis has developed a computationally efficient model for valuing systems built for agile investing. It combines system architecture principles, real options valuation, and object-oriented programming. Investment decisions under uncertainty are simulated by combining optimization algorithms and Monte Carlo sampling. The approach allows expansion decisions to be included in the early stages of system architecture design. In industry, definition of subsystem requirements is an influential step in project development, setting up the costlier and time intensive detailed engineering, procurement and construction. Practicality is demonstrated through application to a realistic, but hypothetical case study. We explore the development of an upstream, onshore oil field. The system is decomposed into several subsystems accomplishing fluid extraction, processing and sales. The model simulates their physical and economic interactions to calculate performance metrics of net present value, capital expenditure, system capacity, emissions and others. We investigate performance changes based on subsystem sizing and installation timing. The analysis shows how agility can increase expected value while reducing investment risk. Overall expected value increases by 5% and the initial capital commitment is only one-sixth the cost of a full production system. The value is created by earlier positive cashflows, hedging commitment against falling oil prices and quick expansion opportunism in the case of rising prices. Using the same model, subsystems are refined and then expanded to investigate combustion emissions. By incorporating cleaner fuel sources, combustion emissions can be reduced by 70%. We conclude by recommending specific subsystem requirements for an agile investment design. Keywords: agility, oil and gas, system architecture, real options, Monte Carlo simulation, integer optimization, managing uncertainty, design flexibility, object-oriented programming