Quantifying Economic Uncertainties and Risks in the Oil and Gas Industry

Quantifying Economic Uncertainties and Risks in the Oil and Gas Industry

Sorin Alexandru Gheorghiu (Kuwait Oil Company, Ahmadi, Kuwait) and Cătălin Popescu (Petroleum-Gas University of Ploiesti, Romania)
DOI: 10.4018/978-1-7998-5083-0.ch008
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Abstract

The present economic model is intended to provide an example of how to take into consideration risks and uncertainties in the case of a field that is developed with water injection. The risks and uncertainties are related, on one hand to field operations (drilling time, delays due to drilling problems, rig failures and materials supply, electric submersible pump [ESP] installations failures with the consequences of losing the well), and on the other hand, the second set of uncertainties are related to costs (operational expenditures-OPEX and capital expenditures-CAPEX, daily drilling rig costs), prices (oil, gas, separation, and water injection preparation), production profiles, and discount factor. All the calculations are probabilistic. The authors are intending to provide a comprehensive solution for assessing the business performance of an oil field development.
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Introduction

Assessing the risks and uncertainties are the main challenges in the today professional and non-professional activities. Risk management of any risk type requires the use of various tools and techniques, which could be specific to every single field. Related to the oil and gas field, these tools and techniques allow the identification and analysis of risks as part of the evaluation of investments made in both the upstream and downstream sector.

The two terms, risk and uncertainty are implying ranges and probabilities. The economic model that the authors constructed and described in this chapter is based on probabilistic methods. The authors are intending to provide a practical solution for evaluating, from the economic point of view, the profitability of a field development by using the probabilistic approach.

The mathematical model is based on the well-known Discounted Cash Flow method, where some of the input parameters are defined as distributions of probabilities. The whole model was built in Excel and the probabilistic engine used was Oracle Crystal Ball.

The risks and uncertainties taken into account are related to drilling, well completion, production rates and possibility to lose the well due operation failures. It is obvious there are many other risks that eventually can be taken into account, but the authors refrain to the above-mentioned ones. The outputs of the model are economic performance indicators: Pay Out Time, Internal Rate of Return, Profit-Investment Ratio, Cumulated Net Cash Flow, Total Taxes, Profit Tax and Number of Profitable Years.

The field development scenario is considering a real oil field, where the field name, wells’ names and specific field data were changed to keep the confidentiality of the data, required by the oil company. The useful information is that the oil field is situated in the northern edge of Eastern Arabia. The production and injection profiles were created by using the ECLIPSE™ (mark of Schlumberger) simulator and the data were exported to Excel by using the Eclipse Office package (mark of Schlumberger).

On the other hand, there is some other software, for instance the CASPAR (Computer Aided Simulation for Project Appraisal and Review) program that can be applied in risk analysis and modelling.

Basically, the main objective of the chapter is to build a probabilistic Discounted Cash Flow model to evaluate the economic performance of an oil field developed with producer and injector well embedding uncertainties and risks related to oil field operations (drilling, production and wells interventions). As results the final user will get:

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    the economic performance parameters as a range instead of a unique solution;

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    the main influencers from the input parameters and their magnitude to economic performance indicators.

These outputs will help the user in the short, medium and long term decisions related to company’s evolution and performance.

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Literature Review

In the current context of development of our society it is needed the utilization of the advanced techniques and technologies for forecasting the future of a business. Due to the fact that the results of a business are influenced in one way or another by a lot of parameters (controllable and uncontrollable), a deterministic approach is not sufficient. The petroleum industry is a good example of an industry that is characterized by high investments and high uncertainty (Kvalevåg, 2009). In this regard, the topics of investments and investment behavior of the companies are analysed in detail, starting with the so-called traditional theory of investment and continuing with the approach that introduced the analogy with the theory of options in financial markets (Dixit & Pindyck, 1994).

Key Terms in this Chapter

Risk: Situation involving exposure to danger and/or loss.

Uncertainty: State of limited knowledge where it is impossible to describe the existing state, a future outcome etc.

Discounted Cash Flow: Method used to estimate the value of an investment based on its future cash flows.

Reservoir Simulation: The process of mimicking the behavior of fluid flow in a petroleum reservoir system.

Water Injection: Water injected into the oil field in order to increase pressure and stimulate production.

Economic model: Set of mathematical equations to describe a theory that is used for quantifying the effects of something on an economy or a company.

Net Cash Flow (NCF): Amount of money produced or lost during a period of time by calculating the difference between cash inflows from outflows.

Profitability Index (PI): Index that represents the relationship between the costs and benefits of a project.

Optimization: The action of making the best or most effective use of a situation or resource.

Field Development: Exploiting the potential to benefit from the reservoir performance.

Oracle Crystal Ball: Application used for the risk measurement that is based mainly on the Monte Carlo simulation approach.

Internal Rate of Return (IRR): Discount rate that makes the net present value (NPV) of all cash flows from a project equal to zero.

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