master thesis - real option valuation of oil and gas megaprojects

Antoine Paillat

Financial Valuation of oil and gas megaprojects using real option theory

December 3, 2014

1. Problem Statement 2. Literature review of Real Option Theory 3. Methodology 4. Findings and Discussion 5. Conclusion

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© 2012, IHS Inc. No portion of this presentation may be reproduced, reused, or otherwise distributed in any form without prior written consent.

Problem Statement

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The E&P megaprojects budget overruns follow a long-term trend of growth in project size, driving E&P capital spending fourfold during the last decade, and draining more and more operators in such large projects.

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report schedule delays, which are one of the main reasons for budget overruns 4. More disturbing,

the proportion of large budget overruns has almost doubled from 2005 to 2011, according to a 10-

year industry survey carried out in 20115.

Projects facing costs overruns

Projects facing delays

Average budget overruns

This explosion of budget overruns follows a long-

term trend of growth in project size, driving E&P

capital spending fourfold during the last decade,

and draining more and more operators in such

large projects6. The global race to access the

resources is still on, and as the high post-crisis

prices’ euphoria is fading, operators start to see

the cost-related issues.

4 Ernst and Young (2014) Spotlight on oil and gas megaprojects 5 Schlumberger Business Consulting (2012) Energy Perspectives: Challenges of E&P Megaproject Delivery, Summer Issue. 6 Idem

1. Main Research Question Could we indentify and measure the added value of flexibility in oil and gas megaprojects, by performing simple real options financial valuations? 2. Secondary Research Question Using the valuation results, which investment recommendations and strategic guidance could be provided to oil and gas decision-makers regarding investments in megaprojects?

1. Problem Statement 2. Literature Review 3. Methodology 4. Findings and Discussion 5. Conclusion

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Literature Review

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1.  Dealing with the uncertainty (1994) Dixit and R. Pindyck, Investing under uncertainty, Princeton University Press

If the investment is subject to uncertainty and irreversibility, there is a posistive real option value which is not highlighted by the standard “NPV > 0 rule”

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amount of mathematics, when investment decisions are made at discrete points of time. Following

is their simple yet famous example of the widget factory. In this case, a firm has the opportunity to

invest = 1600 to build a factory able to produce one widget per year, with zero operating costs.

Currently the price of a widget is $200, but for next year the price there is a q probability that it

will rise to $300, and a (1-q) probability that it will fall to $100. Then price the price is assumed to

remain at this new level forever. The discount rate is set at 10%.

a) Payoff structure of the widget factory

t=0 t=1 t=2 t=3 …

P0 = 200

q=0.5 P1 = 300 P2 = 300 P3 = 300

1-q P1 = 100 P2 = 100 P3 = 100

b) Standard NPV calculation

Ö Investing right now, the only widget price expected is $200

c) NPV calculation with flexibility

Ö Wainting one year, and investing only if the widget price rises to 300 (q=0.5)

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t=0 t=1 t=2 t=3 …

P0 = 200

q=0.5 P1 = 300 P2 = 300 P3 = 300

1-q P1 = 100 P2 = 100 P3 = 100





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t=0 t=1 t=2 t=3 …

P0 = 200

q=0.5 P1 = 300 P2 = 300 P3 = 300

1-q P1 = 100 P2 = 100 P3 = 100






Literature Review

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2. Common real options in the oil and gas sector (2002) C.R. Harvey, Identifying real options, Duke University Press (2003) Oilfield Review, Unlocking the Value of Real Options

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financial implications of the project, while “in” options projects are revealed by changing the

technical design of the project.

A Flexible Manufacturing System (FMS) is a type of project design that aims at making those

“in” projects real options available. Such design frameworks are widely used in the oil and gas

industry. As this study does not cover the field of project engineering, we will not look at “in”

projects real options. In the oil and gas sector, common examples of “in” projects real options are

product flexibility options21, process flexibility options22, and intensity options23.

“On” projects real options in the following pages have been studied in greater details by C.R.

Harvey in his paper Identifying real options (2002), Duke University Press.

II.2.2 Delay option

Generic description: Exactly the one revealed above in the ‘widget factory’ case. It is the option to delay the investment until the economic conditions become more favorable.

Oil and gas: Equivalent to delaying the investment in an oilfield until the market price for crude oil makes it economically viable.

Financial markets analogy: Buying a call option which is not yet “in the money”.

S: Stock Price (PV of Cash-Flows)

X: Premium (First CAPEX)

T: Maturity (Time on lease)

21 Ex: Being able to dynamically vary the share of middle distillates in the refining output 22 Ex: Being able to switch from electricity or natural gas as a fuel to run the production facilities 23 Ex: Being able to dynamically increase or decrease the level of production each year

S X

T

Delay until the

projects start

+

-

2.1. Delay Option


Literature Review

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2.2. Abandon or Termination option

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II.2.3 Abandon option

Generic description: It is the option to definitely abandon a project during its life, i.e. the right to sell the remaining cash flows for some salvage value.

Oil and gas: From the point of view of an oil and gas operator (a major), it is equivalent to abandoning the development of an oilfield and selling the expected cash-flows of the project to the resources owner (a NOC) at a contractually settled price.

Financial markets analogy: Buying a put option which will be exercised to abandon the project.

S: Stock Price (PV of Cash-Flows) X: Premium (First CAPEX) T: Maturity (Time on lease)

II.2.4 Contract option

Generic description: It is the option to contract – partially or entirely – the output of the project.

Oil and gas: From the point of view of an oil and gas operator (a major), it is equivalent to contracting the development of an oilfield to another society (an oilfield services company), thus selling the expected cash-flows by paying contractually settled fees.

Financial markets analogy: Buying a put option which will be exercised to contract the project.

S: Stock Price (PV of Cash-Flows) X: Premium (OFS fees) T: Maturity (Time on lease)

-

+ The project is

contracted

S T

X

T

X

S

The project is

terminated

+

-


Literature Review

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2.3. Contract option

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II.2.3 Abandon option

Generic description: It is the option to definitely abandon a project during its life, i.e. the right to sell the remaining cash flows for some salvage value.

Oil and gas: From the point of view of an oil and gas operator (a major), it is equivalent to abandoning the development of an oilfield and selling the expected cash-flows of the project to the resources owner (a NOC) at a contractually settled price.

Financial markets analogy: Buying a put option which will be exercised to abandon the project.

S: Stock Price (PV of Cash-Flows) X: Premium (First CAPEX) T: Maturity (Time on lease)

II.2.4 Contract option

Generic description: It is the option to contract – partially or entirely – the output of the project.

Oil and gas: From the point of view of an oil and gas operator (a major), it is equivalent to contracting the development of an oilfield to another society (an oilfield services company), thus selling the expected cash-flows by paying contractually settled fees.

Financial markets analogy: Buying a put option which will be exercised to contract the project.

S: Stock Price (PV of Cash-Flows) X: Premium (OFS fees) T: Maturity (Time on lease)

-

+ The project is

contracted

S T

X

T

X

S

The project is

terminated

+

-


Literature Review

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2.4. Expand option

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II.2.5 Expand option

Generic description: It is the option to expand the project the capacity in excess of what was initially planned.

Oil and gas: From the point of view of an operator (a major), it is equivalent to expanding production to a satellite oilfield nearby, thus increasing the production output.

Financial markets analogy: Buying a call option which will be exercised to lauch the expansion.

S: Stock Price (PV of Cash-Flows) X: Premium (Expansion CAPEX) T: Maturity (Time on lease)

II.2.6 Grow, defer, quit, and limitless possibilities

Just like financial options, real options can be combined (expand and/or contract, i.e. a

switching option), sequenced (multi-stage development, equivalent to sequenced expand options),

or compounded (option of an option, such as expanding the expansion) to create real options

fitting any sort of projects. The possibilities are truly limitless, and although extensive literature has

been produced on such matters24, we will try to stick to the basics in this overview. However, an

interesting mapping system has been elaborated by T.E. Copeland and P.T. Keenan (1998) with the

‘7S Framework’25. According to the authors, seven basic real options exist, which all could be

classified into three main categories: Growth options, Deferral/Learning options, and

Abandonment options.

24 L. Trigeorgis (1996) Real Options: Managerial flexibility and strategy in resource allocation, MIT Press, Cambridge, Mass. 25 T.E. Copeland and P.T. Keenan (1998) How much is flexibility worth?, McKinsey Quaterly, vol. 2.

+

The project is

expanded

S X

T

-


Literature Review

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3. Real option valuation methods 3.1. The Black-Scholes Model (1973) F. Black, M. Scholes and R. Merton, The Pricing of Options and Corporate Liabilities

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II.3 Overview of valuation methods

II.3.1 Black-Scholes model (BSM)

F. Black, M. Scholes and R. Merton (1973) showed that options can be priced using the risk-free

arbitrage principle, without the need to estimate distributions of returns26. The Black-Scholes

formula estimates the value of a call option C :

Where:

The price of a corresponding put option is:

Terms Financial option Oil and gas real option

Cumulative normal distribution function

Time to maturity Time on lease

Spot price of the underlying asset NPV of developed reserves

Strike price PV of expenditures

Volatility of stock price Volatility of cash-flows from the project

Dividends foregone Revenues or profits foregone

26 F. Black, M. Scholes and R. Merton (1973) The Pricing of Options and Corporate Liabilities, The Journal of Political Economy, vol. 81, issue 3, University of Chicago Press.

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Where:










18






Where:










18






Where:










18






Where:










At the money (S=X)

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Working only for European27 options, the closed-form Black-Scholes formula has limited

applicability. However, the Black-Scholes partial differential equation can be used to price

American and compound options, thus having far wider applicability28. For ‘at the money

option’29, an approximate formula has been found by Brenner and Subrahmanyam for “at the

money” options30:

To enhance the practical applicability of the model, T.A. Luehrman proposed a simple framework

to link project financials with the five variables of the Black-Scholes model31:

The five variable of the BSM are aggregated to form only two new metrics…

… which allow decision-makers to locate investment opportunities in a two-dimensional space.

27 European options can only be exercised at a specific date, while American options can be exercised at any time 28 W. Bailey, B. Couët, A. Bhandari, S. Faiz, S. Srinivasan and H. Weeds (2003), Unlocking the Value of Real Options, Oilfield

Review, vol. 15, issue 4. 29 When S = X, the option is said to be ‘at the money’ 30 M. Brenner and M.G. Subrahmanyam (1988) A Simple solution to Compute the Implied Standard Deviation, Financial Analysts

Journal, pages 80-83. 31 T.A. Luehrman (1998) Investment opportunities as real options: Getting started with the number, Harvard Business Review, vol.

76, issue 4.


Literature Review

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3.2. Binomial option pricing model (1979) J.C. Cox, S.A. Ross and M. Rubinstein, Option pricing: A simplified approach

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II.3.2 Binomial options pricing model

First proposed by Cox, Ross and Rubinstein in 197932, the binomial options pricing model (BOPM)

uses a ‘discrete-time’ (lattice) model to value both European and American option.

In each time step, a binomial lattice could only

move up or down. Two factors u and d,

functions of the volatility σ , are applied to

determine the upward and downward moves.

;

In the case of Cox, Ross and Rubeinstein’s

demonstration, the discount rate used is the risk-

free rate (r). With the variables detailed above

we obtain the probability (p) such as:

Estimating volatility is the key part of constructing the lattice. Some ROA practitioners argue

whether technical and market uncertainties should be aggregated or separated33. Then, valuation is

performed by starting at the end nodes of the tree and then working backwards until the first

node. At each stage the binomial tree gives the option value at that point in time such as:

32 J.C. Cox, S.A. Ross and M. Rubinstein (1979) Option pricing: A simplified approach, Journal of Financial Economics 33 W. Bailey, B. Couët, A. Bhandari, S. Faiz, S. Srinivasan and H. Weeds (2003), Unlocking the Value of Real Options, Oilfield

Review, vol. 15, issue 4.

First proposed by Cox, Ross and Rubinstein in 197932, the binomial options pricing model (BOPM) uses a ‘discrete-time’ (lattice) model to value both European and American option.

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;











20








;











20








;











Estimating the volatility is the key part of constructing the tree.


Literature Review

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3.3. Finite differences method (1977) E.S. Schwartz, The Valuation of Warrants: Implementing a New Approach (2000) G. Cortazar, Simulation and Numerical Methods in Real Options Valuation

The two basic finite differences are the implicit and the explicit method. The former is the more robust one, and both have been proposed by E.S. Schwartz (1977)

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II.3.3 Finite difference methods

Using finite differences is an alternative to binomial trees to solve the valuation equation.

This resolution method being beyond the numerical capabilities of the author, the following lines

have been adapted from G. Cortazar (2000) Simulation and Numerical Methods in Real Options

Valuation, Pontificia Universidad Catolica de Chile34.

Under standard no-arbitrage conditions, the Black-Scholes differential equation can be derived for

the value of the option C(S,t):

Boundary equation at maturity: S being an absorption state:

The two basic finite differences are the implicit and the explicit method. The former is the more

robust one, and both have been proposed by E.S. Schwartz (1977)35. The second is relatively

clearly exposed by G. Cortazar in its working paper mentioned above.

We encourage the readers interested in the matter to go through these papers. The main insight of

the finite differences method is to provide a more precise valuation for options on dividend paying

stocks36.

34 This and several other working papers from G. Cortazar are great readings for those wanting to go deeper into the understanding of

the four valuation methods discussed in this chapter. The textbook by J. Rogers (footnote 8) might also be considered as a prior material.

35 E.S. Schwartz (1977) The Valuation of Warrants: Implementing a New Approach, Journal of Financial Economics, vol. 4, North-Holland Publishing.

36 Idem

21














stocks36.




36 Idem

21














stocks36.




36 Idem

The main idea is to simulate price trajectories following a geometric Brownian motion. Volatility is found through random sampling form the normal distribution. The method aims at approximating probability distributions of terminal asset values, using the risk-free interest rate as a point estimator of the option value. This method is harder to used with American option.

3.4. The Monte-Carlo specialized methods (1977) P. Boyle, Options: A Monte-Carlo Approach, Journal of Financial Economics


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Methodology

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1.  Selection of Projects

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III. METHODOLOGY

III.1 Selection of Projects

The year of reference is 2013. All data is updated as of January 1st, 2013. A ‘project’ is composed

of the main oilfield development and of the possible expansions to its satellite oilfields43.

11 megaprojects have been selected according to the following criteria:

Ö Total CAPEX of the project above $1 billon

Ö Operating costs and Government take data availability

Ö Capital costs data availability

Ö Projects types: Conventional Land, Deepwater Oil, LNG, Oil Sands and EOR projects44

Ö Recent or upcoming activity on the project45

Project Type Land Deepwater LNG Oil Sands EOR

Countries Iraq Azerbaijan, Nigeria, Brazil Russia Canada Norway

Projects 2 3 2 2 2

Possible expansions 1 3 1 1 2

The five following tables summarize the main features of the projects, classified by project type.

Additional details and some background information will be provided in the next sections.

Exploration maps can be found in the Appendices.

43 Ex: Marlim being the main field of the Marlim complex in Brazil’s Campos basin, its possible expansions would be Marlim South and Marlim East.

44 Please refer to ‘Main types of upstream projects’ in the introduction of this study for definitions 45 Either the main phase or the expansion has to start between 2013 and 2017, the sole exception being the Snorre EOR project45.


Methodology

15

2. Data Collection

Sources: IHS (CERA, Herold and EDIN), Rystad Energy, US EIA, WoodMackenzie, Reuters, WorldBank, NYU Stern, misc.

3.  Valuation Method

3.1. Why the binomial tree? §  All the data was available at the annual frequency, making then more sense for a

discrete time model. §  Forecast data available enabled most of the uncertainty to be restrained to price

volatility, making it suitable for a NPV-modified calculation. §  Ease of use and little amount of mathematics.


Methodology

16

3.  Valuation Method

3.2. Parameters

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III.3.2 Parameters

As we use a standard DCF method to compute the modified NPV with flexibility, the parameters

are the ones commonly used to value a project: Price, Production, CAPEX, OPEX, discount rate,

and time.

a) Crude oil prices

Parameters:

Calibration targets

It is not really surprising to see that u > d. Crude oil being a finite resource, its scarcity leads to a

permanent upward pressure on prices in the long term. u and d have been set at respectively 0.20

and 0.15 in order to calibrate the average prices on the long-term crude oil prices forecasts

available, i.e. IHS until 2040, and Rystad afterwards, as below:

IHS Rystad Lattice IHS Rystad Lattice Brent Brent Average Brent Brent Average

Year $/bbl $/bbl $/bbl Year $/bbl $/bbl $/bbl 2014 106.15 106.33 111.27 2033 168.00 162.92 177.89 2015 103.75 104.46 114.06 2034 171.00 166.99 182.34 2016 102.86 107.07 116.91 2035 175.00 171.17 186.89 2017 105.51 109.75 119.83 2036 178.00 175.45 191.57 2018 108.20 112.49 122.83 2037 182.05 179.83 196.36 2019 112.11 115.30 125.90 2038 187.13 184.33 201.26 2020 117.40 118.18 129.04 2039 194.24 188.94 206.30 2021 123.76 121.14 132.27 2040 200.35 193.66 211.45 2022 130.00 124.17 135.58 2041 - 198.50 216.74 2023 137.00 127.27 138.97 2042 - 203.46 222.16 2024 145.00 130.45 142.44 2043 - 208.55 227.71 2025 152.00 133.72 146.00 2044 - 213.76 233.40 2026 156.00 137.06 149.65 2045 - 219.11 239.24 2027 159.00 140.48 153.39 2046 - 224.59 245.21 2028 161.00 144.00 157.23 2047 - 230.20 251.31 2029 162.00 147.60 161.16 2048 - 235.96 257.50 2030 163.00 151.29 165.19 2049 - 241.85 263.71 2031 164.00 155.07 169.32 2050 - 247.90 269.80 2032 165.00 158.95 173.55 2051 - - -

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We can notice that the average price given by the model is slightly higher than the forecast data.

The main explanation is that the starting year is 2013, a year where the barrel averaged $108.6/bbl,

thus making the simulation starting on a high basis. The price effect is a real issue which will be

discussed later on.

At each node:

n t=1

q=0.5

1-q

Using Excel’s random function, at each node the price follows the upward or downward path.

For instance, at the first nodes of the tree:

b) Carbon prices

Carbon prices are simulated in order to calculate the carbon emissions costs at the wellhead. As we

will see, it does not make that much a difference at the end. However, as we had to forecast cash-

flows as far as 2050, it makes some sense to consider rising environment-related costs constraints.

Such constraints could reasonably be assumed to contain some uncertainty materialized by volatile

carbon market met prices. As a result, those prices have been modeled using the same method as

described above.


Methodology

17

30

We can notice that the average price given by the model is slightly higher than the forecast data.

The main explanation is that the starting year is 2013, a year where the barrel averaged $108.6/bbl,

thus making the simulation starting on a high basis. The price effect is a real issue which will be

discussed later on.

At each node:

n t=1

q=0.5

1-q

Using Excel’s random function, at each node the price follows the upward or downward path.

For instance, at the first nodes of the tree:

b) Carbon prices

Carbon prices are simulated in order to calculate the carbon emissions costs at the wellhead. As we

will see, it does not make that much a difference at the end. However, as we had to forecast cash-

flows as far as 2050, it makes some sense to consider rising environment-related costs constraints.

Such constraints could reasonably be assumed to contain some uncertainty materialized by volatile

carbon market met prices. As a result, those prices have been modeled using the same method as

described above.

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Parameters:

Calibration targets

Once again, u > d. Environmental costs follow an upward trend, and it does not seem irrelevant to

assume that those costs will be higher in 2050 than there are today. u and d have been set at

respectively 0.30 and 0.10 in order to calibrate the average prices on the long-term carbon prices

forecasts available, i.e. IHS until 2040, as below:

IHS Lattice

IHS Lattice

EU ETS Average

EU ETS Average

Year $/metric ton $/metric ton Year $/bbl $/bbl 2014 9.08 6.60 2033 51.46 40.38 2015 13.68 7.26 2034 54.63 44.42 2016 17.09 7.99 2035 57.96 48.86 2017 19.46 8.79 2036 61.43 53.75 2018 20.78 9.67 2037 64.99 59.12 2019 22.27 10.63 2038 68.66 65.03 2020 23.65 11.70 2039 72.50 71.53 2021 25.22 12.87 2040 76.42 78.69 2022 26.88 14.15 2041 - 86.56 2023 28.45 15.57 2042 - 95.21 2024 30.23 17.12 2043 - 104.74 2025 32.06 18.84 2044 - 115.21 2026 33.98 20.72 2045 - 126.73 2027 35.95 22.79 2046 - 139.40 2028 38.18 25.07 2047 - 153.31 2029 40.51 27.58 2048 - 168.56 2030 43.09 30.34 2049 - 185.22 2031 45.71 33.37 2050 - 203.29 2032 48.51 36.71 2051 - -

We can notice that the average price given by the model is slightly lower than the forecast data in

the early years of the simulation, and then tend to converge towards the forecasts.

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At the first node 2013-2014, we obtain:

n t=1

q=0.5

1-q

As above, here is an example of the price path at the early nodes of the tree:

c) Production

Production data in kboe/d. Natural gas output has been converted into barrels equivalent using

standard conversion factors50.

d) CAPEX

Capital expenditures in million US dollars. Distinction has been made between initial CAPEX and

intermediary project CAPEX.

50 BP, Conversion factors [Online], Available : http://www.bp.com/en/global/corporate/about-bp/energy-economics/statistical-

review-of-world-energy/using-the-review/Conversionfactors.html

32

At the first node 2013-2014, we obtain:

n t=1

q=0.5

1-q

As above, here is an example of the price path at the early nodes of the tree:

c) Production

Production data in kboe/d. Natural gas output has been converted into barrels equivalent using

standard conversion factors50.

d) CAPEX

Capital expenditures in million US dollars. Distinction has been made between initial CAPEX and

intermediary project CAPEX.

50 BP, Conversion factors [Online], Available : http://www.bp.com/en/global/corporate/about-bp/energy-economics/statistical-

review-of-world-energy/using-the-review/Conversionfactors.html


Methodology

33

e) OPEX

Ö Projects’ operating costs: Forecast data (MUSD)

Ö Government take: Forecast data (MUSD)

Ö Carbon emissions compensation costs: 51

f) Discount rate

The oil and gas cost of -capital is calculated as:

In 2013, for oil and gas producing activities, we have52:

51 Wellhead carbon emissions per barrel produced. Approximated using crude oil benchmarks data, source IHS CERA. 52 Aswath Damadoran, Oil and gas upstream industry average metrics, 2013 review including 176 companies. Datasets available

online: http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/wacc.html.htm

33

e) OPEX




f) Discount rate





33

e) OPEX




f) Discount rate






Methodology

3.3. Assumptions: A quick summary

34

Adding the relevant 2013 country risk premiums, we obtain the projects’ discount rates:

Country 2013 Country Risk Premiums53 Discount rates Australia 0.00% 8.68%

Azerbaijan 3.38% 12.06%

Brazil 3.00% 11.68%

Canada 0.00% 8.68%

Iraq 6.89%54 15.57%

Nigeria 5.40% 14.08%

Norway 0.00% 8.68%

Russia 2.55% 11.23%

United States 0.00% 8.68%

g) Time

Time until production output data remains available on IHS Herold. Residual production output

appears to be marginal after that, especially in comparison of the incremental output brought on-

stream by the expansion projects. Please see the projects summary tables in section ‘Selection of

projects’.

III.3.3 Assumptions: A quick summary

Ö Crude oil price is the main source of uncertainty, price volatility can be estimated using a binomial-lattice tree building according to the parameters detailed above.

Ö A project is studied at the scale of a complex of oilfields. Expansions projects concern undeveloped satellite oilfields.

Ö Current shareowners rights, specific contracts’ clauses and other transaction costs are neglected.

53 Aswath Damadoran, Country Risk Premiums, 2013. Dataset available online: http://pages.stern.nyu.edu/~adamodar/ 54 World Bank data, Iraq risk premium on lending 2012-2013, available online: http://data.worldbank.org/indicator

35

Ö Taxation costs are reflected by the ‘government take’ forecast data.

Ö The project discount rate is equal to the upstream industry average cost of capital plus a country risk premium.

Ö Natural gas production can be monetized for its equivalent volume in liquids at the market crude oil price.

Ö Carbon wellhead emissions can be estimated using crude oil benchmarks data.

Ö Time remaining on lease is equal to the time until production output from the field become marginal.


20


Findings and Discussion

1. Projects Valuation A striking example : Bonga Deepwater & Bonga Southwest-Aparo extension

46

b) Financial metrics

As of 2013 ACG Chirag

Expansion Bonga

Bonga

Southwest-

Aparo

Lula Lula South

Time length 18 years 7 years 12 years 21 years 18 years 21 years

Peak rate

kboe/d

1,035

kboe/d

183

kboe/d 250 kboe/d 225 kboe/d

1,000

kboe/d 120 kboe/d

Wellhead

emissions 28 kCO2/bbl 28 kCO2/bbl 77 kCO2/bbl 77 kCO2/bbl 32 kCO2/bbl 32 kCO2/bbl

First

CAPEX $0 $6.0 billion $0 $9.0 billion

$10.0

billion

$3.75

billion

Total

CAPEX $0 $6.0 billion $0

$12.0

billion

$80.0

billion

$3.75

billion

Discount

rate 12.06% 12.06% 14.08% 14.08% 11.68% 11.68%

c) Real Option Valuation

DEEPWATER OIL AZERI-CHIRAG-GUNESHLI

Project Flexibility (with/without) No flexibility Abandon Expand

Average NPV (MUSD) 37 270 38 800 40 480

Option Value (MUSD) 0 1 530 3 210

VaR at 10% 6 000 0 11 000

VaR at 20% - - 0

VaR at 33% - - -



47

VaR = 0 Probability 15% 5% 20%

Initial CAPEX (MUSD) 0 0 6 000

Total CAPEX (MUSD, post-2013) 0 0 6 000

PIR (Profit Investment Ratio) - - 7,75

DEEPWATER OIL PROJECTS BONGA

Project Flexibility (with/without) No flexibility Abandon Expand Delay +

Expand + Abandon

Average NPV (MUSD) -2 400 500 7 300 23 700

Option Value (MUSD) 0 2 900 6 800 26 100

VaR at 10% 6 000 0 8 200 0

VaR at 20% 5 000 0 4 000 0

VaR at 33% 4 000 0 0 0

VaR = 0 Probability 80% 80% 33% -

Initial CAPEX (MUSD) 0 0 9 000 12 000

Total CAPEX (MUSD, post-2013) 0 0 12 000 12 000

PIR (Profit Investment Ratio) - - 1.61 2.98



50

Bonga NPV distribution – No flexibility VS Expand

For the Bonga project, it seems really interesting to take a close look at the expand option (above).

Without flexibility, the average NPV is negative at - $2.4 billion, even taking into account that all

CAPEX has already been spent. Therefore, except if the abandon option can be obtained for free, a

rational investor would rather pass. The expand option (Bonga SW-Aparo) considerably increase

the average NPV up to $7.3 billion, and is worth $6.8 billion. However, this move also increases

VaR at 10% by 2.2 billion, reaching 8.2 billion. Still, the profit ratio stands at 1.61x, as the

expanded project has 2 chances out of 3 to create some value, as VaR = 0 at 33% (below).

To avoid such risk, an option

worth $16.4 billion is to delay

the expansion investment

until 2017. Altogether, the

three options are worth $26.1

billion, maximizing both the

average NPV and the profit

ratio, respectively up to $23.7

billion and 2.98x.

Bonga VaR – No flexibility VS Expand

50

















billion and 2.98x.


Without flexibility, NPV is negative at - $2.4 bn, even taking into account that all CAPEX has already been spent. Except if the abandon option can be obtained for free, a rational investor would rather pass. The expand option considerably increase the average NPV up to $7.3 bn, and is worth $6.8 bn. This move also increases VaR at 10% by 2.2 bn, reaching 8.2 bn. Still, the profit ratio stands at 1.61x, as the expanded project has 2 chances out of 3 to create some value, as VaR = 0 at 33%

50

















billion and 2.98x.


50

















billion and 2.98x.




2.  Investment Recommendations

70

IV.2 Investment Recommendations

Majnoon: Invest without flexibility Without any flexibility possible, the project is still highly profitable as its NPV = $133.0 billion.

Considering the size of such project, the initial CAPEX requirement is reasonable at $4 billion.

MAJNOON Conventional Land – without flexibility – Targets

CAPEX NPV objective VaR

(main, greenfield)

$4 billion

$133 billion No value at risk

West Qurna: Invest and buy the Expand option The main project is profitable at NPV = $133.3 billion, although there is a massive initial CAPEX

required of $50 billion. The option to expand with West Qurna 2 is worth $62.5 billion, and it

should be seriously considered as the initial $25 billion CAPEX is lower than the option value.

WEST QURNA Conventional Land – with Expand option – Targets


$50 billion (main, greenfield)

+ $25 billion (expansion)

= $75 billion

$195.8 billion No value at risk

ACG: Invest and buy the Abandon option The main project without flexibility is profitable, NPV = $37.3 billion. All the CAPEX has already

been spent, so the buy-out price should be under that value to guarantee a return. For risk-averse

investors willing to avoid the value at risk at a 10% probability, the abandon option can be

considered if such option can be negotiated for less than its value of $1.53 billion. The expand

option should not be taken as the $6 billion initial CAPEX required exceeds the option value.

ACG Deepwater – with Abandon option – Targets

70






(main, greenfield)

$4 billion









= $75 billion










70






(main, greenfield)

$4 billion









= $75 billion








71


$0 - $34 billion (main, buy-out)

+ $0 - $1.4 billion (abandon option)

= $0 to $35.4 billion

$38.8 billion

VaR = 0 at 5%

Bonga: Invest and buy the Delay, Expand and Abandon options Without flexibility, the main project is not profitable as its NPV is negative (-$2.4 billion).

However, adding the three possible options, the project’s average NPV increases up to $23.7

billion. If the Bonga Southwest-Aparo expansion is delayed, the initial CAPEX required amounts

to $12 billion. The buyout of the main project should be obtained for free, the delay option would

need to bring the remaining $3 billion CAPEX, the abandon option should be negotiated under its

value of $2.9 billion.

BONGA Deepwater – with Delay, Expand and Abandon options – Targets


$0 (main, buy-out)

+ $0 - $2.9 billion (abandon)

+ $12 billion (expand and delay)


$23.7 billion VaR = 0 at 5%

Lula: Invest and buy the Delay, Expand and Abandon options

Without flexibility, the main project is profitable (NPV $69.1 billion) but risky as $35 billion and

$9 billion are respectively at risk at a 10% and a 20% probability. Adding the three possible

options, the average NPV increases up to $111.6 billion. The expansion Lula South costs an initial

CAPEX of $3.7 billion, while the abandon and delay options should be negotiated contractually at

a cost lower than their estimated value.

LULA Deepwater – with Delay, Expand and Abandon options – Targets


$80 billion (main, greenfield) $111.6 billion No value at risk



71





$38.8 billion

VaR = 0 at 5%









$0 (main, buy-out)
















71





$38.8 billion

VaR = 0 at 5%









$0 (main, buy-out)














72


+ $3.75 billion (expand)

+ $0 - $9.7 billion (delay)

= $83.75 to $99.35 billion

Sakhalin: Invest and buy the Expand option The main project is profitable, NPV = $137.5 billion, all the CAPEX has already been spent. The

expand option Sakhalin-3 worth $11.6 billion should be considered as the initial $5 billion CAPEX

is lower than the option value.

SAKHALIN LNG – with Expand option – Targets


$0 - $137.5 billion (main, buy-out)

+ $5 billion (expand)

= $5.0 to $142.5 billion


Yamal: Invest and buy the Delay option The project is profitable, NPV = $47.2 billion, a massive $27 billion CAPEX is required. As the

first oil is planned for 2017, the delay option is extremely interesting and increases the NPV up to

$137.5 billion. The abandon option has no real interest as no project value is at risk here.

YAMAL LNG – with Delay option – Targets




= $27.0 to $117.3 billion


AOSP: Invest and buy the Abandon option The project is profitable, NPV = $25.0 billion, all CAPEX has already been spent. An abandon

option is worth $1.3 billion, and avoids $5 billion of project value to be at risk at a 10% probability.



72




= $83.75 to $99.35 billion








= $5.0 to $142.5 billion









= $27.0 to $117.3 billion




72




= $83.75 to $99.35 billion








= $5.0 to $142.5 billion









= $27.0 to $117.3 billion






72




= $83.75 to $99.35 billion








= $5.0 to $142.5 billion









= $27.0 to $117.3 billion




73

AOSP Oil Sands – with Abandon option – Targets


$0 - $25 billion (buy-out)




Kearl Lake: Invest and buy the Expand option With an average NPV = $35.4 billion, the main project is profitable and requires an initial CAPEX

of $11.1 billion. The expansion is highly recommended, as it costs a $8.9 billion CAPEX and

increases the value by $42.9 billion. The profit ratio with the expansion rises at 4.59x, up from

3.75x.

KEARL LAKE Oil Sands – with Expand option – Targets


$12.9 billion (main, greenfield)


= $21.8 billion


Snorre: Invest and buy the Abandon option Without flexibility the main project is profitable as NPV = $3.3 billion, all CAPEX has already

been spent. The abandon option avoids $2 billion and $0.6 billion potential losses at respectively

10% and 20%. With such option, the VaR = 0 probability decreases from 26% to 5%. The

expansion is not advised as its cost, $7.16 billion, is way above its real option value, estimated at

$1.95 billion.

SNORRE EOR – with Expand option – Targets






73










3.75x.





= $21.8 billion






$1.95 billion.









73










3.75x.





= $21.8 billion






$1.95 billion.







74

Troll: Invest without flexibility The NPV of the main project without flexibility is $30.5 billion, all CAPEX has already been spent.

As no value is at risk, the abandon option has no interest. The remaining expand option cannot be

considered, as it actually decreases the average project value by $1.1 billion and costs $1.7 billion

in CAPEX.

TROLL EOR – without flexibility – Targets


(main, buy-out)



IV.3 Discussion

Throughout this study, we encountered several assumptions and findings that might be

discussed. As many of them have been detailed in the ‘Methodology’ section, here would be only

the main points subject to discussion.

First and foremost, the crucial point subject to discussion is the price effect inflating the

valuation of the projects. As a matter of fact, the reference year chosen to start the price simulation

using the binomial tree is 2013, a year which saw an average Brent price at the quite high level of

$108.56 per barrel. Plus, the parameters of the model assumed an upward pressure on prices over

the long term. In comparison, recent prices were below $90 per barrel, for instance $84.02 per

barrel for the Brent in October 15th, 2014. Many of the projects studied have a breakeven cost per

barrel between $70 and $90 per barrel. This may explain why some projects have a high NPV

while they are planned to be shutdown or delayed in reality. Hence, it should not be forgotten that

the managers of the companies operating the megaprojects studied had those high levels of prices


Findings and Discussion 3. Discussion

3.1. Price effect The modelized oil price starts at the average 2013 value of $108.56, and follows a long-term upward trend of +5% in average. As of December the 3rd, the current Brent oil price is around $70. 3.2. Discount rate Is the discount rate sufficient to modelized the global risk of oil and gas operations in a high above-the-ground risks country? What should be the discount rate for operations in Mauritania or Kurdistan? 3.3. Taxation The government take is not a precise measure of the country oil and gas taxation level, as parallel tax mechanisms may apply such as oil and gas VAT, expatriate workforce taxation, social and environmental taxes, and “off-the-book” paybacks mechanisms. 3.4. Existence of delay options in JV and partnerships How real is the possibility to delay investment when multiple partners are involved in the projects, as it is often the case for megaprojects? 3.5. Microeconomics of oil and gas projects Common industry constraints such as rig availability, access to infrastructures and skilled workforce, role of management, right of the shareowners and market for natural gas, are not taken into in this study.


Conclusion

Main Research question: Identifying and measuring real options helps to highlight the added value of flexibility of oil and gas megaprojects. This can be done with simple models if in discrete time, things become a bit tougher if to study American options in continuous time. Secondary Research question: The results can make a case for investment recommendations, although ideally we should know the level of risk aversion and the cost of capital of the investor. Of the interest to consider uncertainty in oil and gas megaprojects At $108.6/bbl in average in 2013, most of these megaprojects were profitable, and real options could help capture added value. At $70/bbl in average in early December 2014, most of the projects are priced out and the few ones able to reach their break even point are the Iraqi conventional projects and the Azeri deepwater project. Most expansions become unprofitable at such level of prices. Considering buying contractual real options to avoid lock-in situations seems highly interesting indeed.

Thanks for your attention !

Antoine Paillat [email protected] +(33) 636 359 212

master thesis - real option valuation of oil and gas megaprojects

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