13423956 project finance modelling in the angolan oil industry 2001

8/14/2019 13423956 Project Finance Modelling in the Angolan Oil Industry 2001

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RISK ASSESSMENT AND RISK ALLOCATION IN THE CONSTRUCTION AND

OPERATION OF AN OFFSHORE PLATFORM FINANCED THROUGH THE

PROJECT FINANCE MODELLING IN THE ANGOLAN OIL INDUSTRY

Armando Celestino Gonalves Neto, DSc Candidate COPPE - UFRJ/ANP

(National Petroleum Agency) *1

Virgilio Jos Martins Ferreira Ferreira, DSc COPPE Universidade Federal do Rio de Janeiro**2

Csar das Neves, PhD York/ Universidade Federal do Rio de Janeiro***3

Abstract

Nowadays, many emerging countries face great difficulties to obtain capital to implementtheir infrastructure projects, as is the case of the oil industry in Angola. In order to overcome these

obstacles, many countries are looking for private partners to build their Greenfield oil projects.

Regarding this point, Project Finance modelling is a great alternative, despite the cost of raising

capital when compared with the traditional way of financing projects. The success of this kind of

financial modelling depends strongly on risk assessment and risk allocation, which implies an ability to

share risks with the parties most able to bear such particular risk.

JEL classifications: G22;L71

Keywords: Project Finance, Risk assessment, Risk Allocation, Oil Industry, Insurance

1. The importance of the Oil Industry for Angola

Besides the well known Angolan hazards, such as recent war and poverty, the

government has been making an effort to insert the country in the new context of global

economy. In order to achieve this goal over 250 parastatals have been reorganised into

over 800 smaller private firms.

Mbendi Information for Africa (1999) briefly pointed out the situation at present:

1 Address: Rua Paissandu, 93/801 CEP 22210-080 Rio de Janeiro/RJ e-mail: [email protected] e-mail:[email protected] [email protected]

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2. The role of Project Finance in Petroleum activity

Traditional finance, also known as Corporate Finance, makes no distinction between the

project and its executors. The risk of non-payment by the sponsor or the non-conclusion

(completion) or failure of the project (default), in this type of finance, is included in the spread

charged for the use of the capital employed. In addition, the assets of the sponsors of the

undertaking will serve as guarantees for the suppliers of credit, significantly reducing the latters'

risk.

When the government or a private company receives external finance for a domestic

project, in addition to the components already referred to; the spread is loaded with the country risk,

based on classifications by international rating agencies. So that, to the lack of government funds, is

added a risk component which is not always logical, corresponding to the evaluation that the rating

agencies give to Angola debt based on questionable criteria and, although its based on objectives

premises, without any standardization between the different agencies. Such evaluation is a

guideline for the international investor and does not represent incontestable truth. However, these

risk classifications are capable of frightening away long-term foreign capital, discouraging

investment in domestic projects especially those relating to infrastructure (whose payback is

slower). Very often, as a result of this vicious circle, the government is obliged to raise its basic

interest rate in order to hold on to foreign capital, and, in doing so, by way of contradiction, signals a

scenario of greater risk to the international investor overloading the spread charged to domestic

borrowers.

This situation has reduced emerging countries' investment capacity, including that of

Angola, which needs more and more third party capital to carry out urgent infrastructure projects.

Thus, the idea of the state as the main player in the economy is becoming increasingly unrealistic

and the tendency for the reduction in the size of the state and its transformation into a market

regulator is becoming more marked.

At this point, the question arises: where does Project Finance fit into this context?

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Before answering this question directly, we should give a broad-brush picture of this kind of finance

and its main characteristics. Project Finance is a financing instrument whose main characteristics

may be summarized as follows:

a) Segregation of business risk from company risk.

PF creates a separate juridical entity distinct from the borrowers and credit suppliers known as an

SPC (Special-purpose Company). This juridical entity has its own life, with management and

application of its revenues independent of the sponsors and investors.

b) The lenders' main security is the revenue of the project itself.

The PF mode has as its first and main security the revenues generated by the SPC and the assets

belonging to it. In this way, the main instrument for the projects risk analysis will be its cash flow -

from initiation to the point where operation is expected to begin.

c) A complex framework of guarantees and contracts between all the players.

All of the participants of a project financed by PF, whether they are sponsors, financiers (banks,

insurance companies, multilateral agencies, pension funds etc), suppliers of equipment and raw

materials and also purchasers of the products and/or services generated by the SPC (so called

SPV Special Purpose Vehicle), will seek to secure their rights through specific contracts and

guarantees against the risks being assumed by each player.

This complex framework of contracts and guarantees is the main task in setting up a PF. This

means that the cost of raising funds via PF will be higher than through Corporate Finance. PF is

therefore only justified for projects requiring a high level of capital investment.

d) Presence of Multilateral Agencies

The presence of domestic development bodies and foreign development bodies (such as OPIC,

IMF, IFC etc) signals to the private international investor the confidence of these bodies in a

particular project, indicate that the investment will be compatible with the exposure to risk. This

means that the rates charged by private international investors will be lower than they would have

been if such bodies had been absent.

The World Bank Group, represented by its organisms (IFC, OPIC, IMF and) have been helping with

capital and financial technology the developing countries and poor ones in order to setting up PF

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2. BOO (Build-Own-Operate): Similar to BOOT, with the exception that

the project company has a concession life as long as the expected

economic life of the facility.

In view of these characteristics of the PF, this financing model is an excellent alternative for

attracting private investors to infrastructure projects, making it possible for the government to

reduce further its role in the economy and to concentrate on the task of regulating the domestic

market through specific agencies for each sector.

3.Typical risks involved in the construction and operation of an Offshore Platform

Before we talk about assessment and allocation methods of risks, its advisable to mention

some kind of damages, material or personal ones, that always may occur in the construction and

operation of an Offshore Platform. At this moment we wont point out the mitigation techniques that

might possible be used. In the sequence below we do not present a complete list, only the most

common exposures as described by Bidino (1995):

3.1 Material Damages

3.1.1 Acts of Nature

a) Storms

b) streams

c) Bad weather

d) Thunderbolt

e) Windstorm

f) Seaquake

g) earthquake

h) soil strata movements

3.1.2 Operational Risks

a) Contact

b) Collision

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c) Shipwreck

d) Stranding

e) Moral hazard

f) Fire

g) Explosion

h) Blowout (well eruption caused by a uncontrolled flow of gas, oil or another fluid, outside the

well and above the earth surface)

i) Cratering

3.1.3 Damages caused by extra expenses:

a) well control

b) contention

c) leakage

d) pollution

e) Putting out fire

3.1.4 Business Interruption

This is a complex point of analysis when the decision makers are faced with the question:

Buy or not an insurance coverage? They have to examine the tradeoff benefits and costs of an

insurance coverage. It will depend so much on their attitudes facing the expected risks (neutral,

aversion or lover risks).

3.1.5 Damages caused by Third Parties Liability

a) Contracted

b) third parties in general

3.1.6 War, strikes and Political Risks

3.1.7 Removal of wreckage

3.2 Personal Damages

a) Death

b) Temporary Disablement

c) Permanent Disablement

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impact on project, and estimating the probability of the risk occurring and the likely size of the risk

(generally in terms of cost to the project).

Risk assessment is important as it helps project developers to concentrate their resources

(in terms of both time and money) in the areas where they can make the most significant

contribution to the eventual project outcome. It also allows project developers to understand which

aspects of the project are the most sensitive to risk events.

At this step, we can perform this task by qualitative or quantitative methods. In terms of

quantitative assessment we can mention two main concepts: Direct Calculation Technique and

Monte Carlo Simulation. Arndt(.2000) remarks:

Direct Calculation:

The direct calculation technique is one where the project is broken down into components

(such as design costs, construction costs, taxation changes etc.), each of which is attributed a

certain risk. A probability distribution is attributed to each of these components so that an estimate

can be made of its mean and standard deviation. If the risk events, which caused the estimated

probability distributions, are uncorrelated then the mean and standard deviation for each individual

component may be added to obtain the mean and standard deviation of the total project (which

would have a normal distribution if there were many components). This approach involves much

less computational efforts than that required by other quantitative methods such as Monte Carlo

analysis. However direct calculation only works for simple systems with uncorrelated events

(Grey,1995). It is therefore not likely to be suitable for the analysis of risks in Private Provision

Infrastructure projects.

Monte Carlo analysis

Monte Carlo analysis is the most commonly used form of quantitative risk assessment.

A Monte Carlo risk assessment is a method of evaluating all the

permutations of uncertain events that might impact the projected debt coverage

for each year of the project life. The inputs required for Monte Carlo analysis

are distributions for the significant inputs variables that enter into the debt

coverage calculation. ( Songer, Diekmann et al. 1997, p. 379)

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In other words Monte Carlo analysis involves the definition of a probability distribution for the key

variables influencing the project. The difference with this and the direct calculation technique is that

in Monte Carlo analysis a computer is used to generate values for these uncertain variables by

selecting the values from the defined distributions. Many, many runs of the model are carried out so

that a probability profile for the required output (such as total cost or schedule) may be constructed.

In this way project developers can determine the chance that their predicted cost for delivering the

project will be exceeded.

We can make this analysis using any software that proceeds this calculations like @RiskorCristall

Ball.

The third step is Risk Allocation where all parties involved in a PPI project financed by Project

Finance modelling decide who will bear each risk that can impact the project cashflow. Arndt (2000)

proposes some rules in order to obtain the Efficient Risk Allocation:

Risks should be allocated to those parties that are best able to control and manage them. This

means that those parties should:

1. Have a greater ability to influence the probability of the occurrence or the

degree of consequence of that risk;

2. Have the best access to suitable mitigation techniques for that risk;

3. Not be significantly risk averse (and hence charge a larger risk premium than is

strictly necessary).

In Figure 4 we show a picture that resumes the Efficient Risk Allocation in the Private

Provision of Infrastructure projects:

In achieving the Efficient Allocation of the risks in PPI projects, we have to use some

mechanisms of sharing risks between the parties taking account the rules mentioned

above. There are four main methods for allocating risk in contracts. Arndt briefly explains

them:

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a) Entrenchment of rights:

The traditional, contractual, approach to risk allocation was clearly allocate specific

risks to the various parties by allocating a clear responsibility on one party or the

other. If risk eventuated but was not handled in the way set out in the contract then

one party is in breach of the agreement. The other, aggrieved, party can seek

compensation according to the methods set out in the contract and, if this does not

succeed, then ultimately via legal system.

This approach to risk allocation is called entrenchment of rights approach because

each party has specifically defined rights and obligations. It is also sometimes

called the default-compensation approach because default of the contract leads to

a claim for compensation by the aggrieved party due to a breach of contract.

This is the most clear and certain of all the approaches to risk allocation. It is also

the mechanism, which is most likely to be used to allocate most of the risks in a

PPI contract;

b) Material Adverse Effect (MAE) approach

The MAE approach seeks to define certain risk events, which will be borne by

government or shared in some way. The MAE approach is similar to the

entrenchment of rights approach in that it clearly allocates the responsibility for

certain, defined risks to specific parties.

MAE methods of risk allocation specify a mechanism to determine what effect the

risks crystallisation has had on the project and how to determine the ensuing

compensation. Mechanisms may include reference to an agreed financial model in

order to determine objectively any effects on the project. For example the effect of

the risk can be entered into the model and the variation in project variables such as

rate of return on equity, internal rate of return and net present value can be

objectively determined. Alternatively this analysis may be limited to an independent,

open book audit of the project.

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Forms of compensation may be pre-defined and include options such as allowing

the tariffs to be increased or extending the term of the concession (effectively a

transfer of the risk to consumers). Other options may allow for altering the franchise

fees or direct financial compensation by the government;

c) Agree to negotiate approach

The most flexible approach to risk sharing is simply for the parties to agree to meet

and to renegotiate the contract in the event of a major risk occurrence. While this

approach offers little by the way of certainty for the financial markets, it is the most

flexible option. It may therefore be a suitable way of addressing risk for extremely

unlikely events or events which were not contemplated at all at the time of

contracting. Agreeing to negotiate following the occurrence of a major risk is a

common way of dealing with risk events in some European countries and seems to

be supported strongly by sponsoring organisations from that region (Arndt and

Maguire 1999; Eves 1995; Fillet 1995).

However, the agree to negotiate approach gives little comfort to debt providers and

to those sponsors who view governments cynically. Many private sector participants

will not rely on any compensation being forthcoming unless it is clearly specified in

the contract. Therefore this approach is not used regularly and is usually limited in

its application. It is also usually coupled with an alternative dispute resolution

approach to reduce the chances of potentially costly litigation.

d) Payment and termination provisions

There are other ways to allocate risk apart from the direct contractual provisions

discussed above. The most frequent, non direct, risk allocation occurs in the tariff

calculation formulae and the default and termination provisions of the contract. For

example, if the sponsor is to bear the risk of rises in input costs except inflation

then the payment which they receive in return for providing the service should

adjust for inflation, but not for the general cost of inputs.

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Tariffs are often split into a number of components. Historically, the most

common structure has been a two part system comprising a fixed (or availability)

component and a variable (or usage) component. Private sector bidders will

normally prefer the fixed component of the tariff to cover their fixed costs such as

debt service and fixed operating costs. They will be more comfortable in allowing

the tariff to vary when their costs are variable and so are not incurred if the service

is not provided. The variable component of the tariff may include an escalation

formula, which compensates the service provider for increases in input costs

related to inflation, using an agreed indicator. This type of tariff structure transfers

little demand or market risk to the private provider.

In the figure 5 we show the main characteristics of the principal contractual

methods for allocating risk:

5. The use of Project Finance modeling to finance an Offshore Platform

Having reached the core of this paper, wed like now to describe the risk management in the

construction and operation of an Offshore Platform financed by Project Finance Modeling.

As mentioned earlier in sections 3.1 and 3.2, we showed the main physical and personal damages

that can occur during construction and operating period. Now, we increase the list of risks

enumerating other kinds of risks, such as commercial and political ones. Regarding political risks,

although Angola has a higher political risk, Salinger (2000) remarks that when a project involves a

key activity in the countrys economy, the government becomes interested in increasing its

participation in the added value of economy and takes all steps to assure this sector, as is the case

of the Oil sector in Angola, where the political risks tends to be accepted by Insurers (statal or

private).

The figure 6 shows a possible Project Finance Structure for the construction and operation of an

Offshore Platform.

Another important question is the contractual structure that can be used. So, figure 7, we illustrate

a possible contractual environment involving all parties of a Project Finance:

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6.1 The attitudes of the main contractor and operator (Oil Company) and the insurers

toward risk events

Project Finance involves most parties that are interested in the project in different ways. Because of

their access to the risk mitigation techniques and their understanding about each kind of risk,

whose factors will determine the risk premium to bear a specific risk, a risk allocation has to be

made. A successful risk allocation is key to the success of the Project Finance in order to

implement the PPI project, despite the fact that some risk might occur.

6.2 Oil Company behaviour toward risks:

Walls (1995), has made a research on the 25 most important USA Oil Companies during

the period of 1983 to 1995. Based on Expected Utility Theory, he supposes that the

preference structure of the decision makers of those Oil Companies can be represented by

a logarithmic function showed below:

U(x) = I e-x/R

Where:

X variable of interest

R Risk Tolerance Coefficient

I Constant depending on each firm

Taking into account this assumption, he developed the concept of Risk Tolerance Ratio,

that represents the maximum capital amount that an Oil Company is willing to invest in

greenfield oil project.

We illustrate the outcome of Walls work in table 4 that presents the risk Tolerance for the

USA Oil most Important companies.

6.3 Insurers Attitudes toward risk

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Insurers are not only mitigators but also participants. They can also invest part of their

reserves in a greenfield Oil Project. Their specialising in risk mitigation techniques is very

important to hedge the project.

To exemplify the case of an offshore platform we listed the main policies used:

a) Bid phase

Guarantee insurance for contractual obligations, of the bid and performance bond (the latter only for

the winning consortium or company) types.

c) Construction phase

Builder Risk Hull Insurance, with additional cover for crossed civil liability, projects error and voyage

(which covers the platform's sea voyage), Marine Insurance (covering the transportation of the raw

materials and equipment used in construction).

d) Pre-operation phase

Guarantee insurance for contractual obligations, perfect functioning mode.

e) Operation phase

London Platform Form including Clauses A, B or C of the London Cargo Institute Clauses.

General civil liability insurance.

Business Interruption

Environmental risk insurance.

7. Conclusions

The purpose of this was to help the Angolan government practitioners understand the risk

attitudes of private participants in an Oil Project, in order to best allocate the risks and attract

these private partners to keep competition and improve the developing of the oil market in

Angola.

Bibliography

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(1) Arndt, R.H.: Is Build-Own-Operate-Transfer a solution to Local Governments Infrastructure

funding problems?, presented at International Congress of Local Government Engineering and

Public Works, Sidney, August 1999.

(2) Arndt, R. H. : Getting a fair deal: Efficient Allocation in Private Provision of Infrastructure, The

University of Melbourne, Ph.D. Dissertation, July 2000.

(3) Aschauer, D.: Is Public Expenditure Productive?, Journal of Monetary Economics, n 23, p.177-

200, Mar.1990.

(4) Benoit, P. The World Bank Groups Financial Instruments for Infrastructure. Working Papers

(Viewpoint 16891). January 1997

(5) Bidino, M. H.: Curso de Introduo ao Seguro de Risco de Petrleo. Funenseg. Rio de Janeiro.

1995

(6) Contador, C.R. : Economic Activity in 2001: What the leading indicators forecast, Estudos

Econmicos, Silcon, Rio de Janeiro, Novembro 2000.

(7) Ferreira, P.C. :Essays on Public Expenditure and Economic Growth, University of Pennsylvania,

1993, Ph.D. Dissertation.

(8) Finnerty, J.D. :Project Financing: Asset-based Financial Engineering, New York, John Wiley and

Sons, 1998.

(9) Heins, R.M. & Williams,A.C. : Risk Management and Insurance. 5th Edition . McGraw Hill.1985

(10) IFC: Project Finance in Developing Countries, Washington, 1999

(11) IFC: Lessons of Experience- financing Private Infrastructure, Washington, Sep.1996.

(12) Mbendi: Africa: Oil and Gas Industry- Exploration & Production in

www.mbendi.co.za/indy/oilg/ogus/af/p0005.htm

(13) Nevitt, P. ; Fabozzi, F. : Project Financing, Sixth Edition, Euromoney Publications, 1995.

(14) Energy Balances of OECD Countries.2000

(15) OPEC. Monthly Oil Market Report. February 2001

(16) Salinger, John J. : Guarantee and Insurance: Future Directions for Public Agencies. Private

Infrastruture for Development: Confronting Political and Regulatory Risks (Seminar). Rome. 1999.

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(17) Walls, Michael R. : Corporate Risk-Taking and Performance: a 15 year look at the Oil Market.

Society of Petroleum Engineers 49181. 1996

(18) Towsend, D. :Project Finance-powering ahead, Petroleum Economist, April 2000.

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Table 1. Macroeconomic Index in Angola: 1996 - 1999

Series 1996 1997 1998 1999

Commercial energy use (kg of oil equivalent per capita) 622 620 595 .Current revenue, excluding grants (% of GDP) . .. .. ..Electric power consumption (kwh per capita) 61 64 60 ..Exports of goods and services (% of GDP) .. .. 57 ..Foreign direct investment, net inflows (current US$) 181,000,000 412,000,000 1,114,000,000 2,471,000,000GDP at market prices (current US$) 7,522,010,000 7,690,180,000 6,448,710,000 8,544,930,000GDP growth (annual %) 10 6 3 3Gross domestic investment (% of GDP) .. .. 24 ..Imports of goods and services (% of GDP) .. .. 48 ..Industry, value added (% of GDP) 68 61 56 77Overall budget deficit, including grants (% of GDP) .. .. .. ..Population growth (annual %) 3 3 3 3Population, total 11,318,100 11,661,500 12,006,500 12,356,900Present value of debt ($) .. .. .. 8,493,700,000

Services, etc., value added (% of GDP) 25 30 31 16Short-term debt ($) 1,168,800,000 1,267,000,000 1,709,500,000 1,623,500,000Total debt service (TDS, current US$) 987,700,000 991,500,000 1,127,600,000 1,143,600,000Trade (% of GDP, PPP) 29 29 18 16Trade (% of goods GDP) 117 122 113 88

Source: World Development Indicators database

Table 2. Proved Reserves

At end 1979At end 1989At end 1998At end 1999At end 1999At end 1999At end 1999

Thousand Thousand Thousand Thousand Thousand

million million million million Share of R/P

Proved Reserves barrels barrels barrels tonnes Total ratio

USA 33,7 33,6 30,1 28,6 3,5 2,80% 10,0

Canada 8,1 8,4 6,8 6,8 0,8 0,70% 9,3

Mexico 31,3 56,4 47,8 28,4 4,1 3% 24,5

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Total Noth America 73,1 98,4 84,7 63,7 8,4 6,2% 13,8

Argentina 2,4 2,3 2,6 2,7 0,4 0,3% 9,1

Brazil 1,2 2,8 7,1 7,3 1,0 0,7% 18,1

Colombia 0,7 2,1 2,6 2,6 0,4 0,2% 8,5

Ecuador 1,1 1,5 2,1 2,1 0,3 0,2% 15,3

Peru 0,7 0,4 0,3 0,4 ** ** 8,9

Trinidad & Tobago 0,7 0,5 0,5 0,6 0,1 0,1% 12,9Venezuela 17,9 58,5 72,6 72,6 10,5 7,0% 65,2

Other S. & Cent. America 0,6 0,6 1,2 1,2 0,2 0,1% 25,0

Total S & Cent. America 25,3 68,7 89,0 89,5 12,9 8,6% 37,7

Denmark 0,4 0,8 0,9 1,1 0,1 0,1% 9,7

Italy 0,6 0,7 0,6 0,6 0,1 0,1% 15,8

Norway 5,8 11,5 10,9 10,8 1,4 1,0% 9,3

Romania n/a n/a 1,4 1,4 0,2 0,1% 30,4

United Kingdom 15,4 4,3 5,2 5,2 0,7 0,5% 5,0

Other Europe 4,4 3,2 1,7 1,6 0,2 0,2% 13,3

Total Europe 26,6 20,5 20,7 20,7 2,7 2,0% 8,3

Azerbajian n/a n/a 7,0 7,0 1,0 0,7% 69,5

Kazakhstan n/a n/a 8,0 8,0 1,1 0,8% 36,5Russian Federation n/a n/a 48,6 48,6 6,7 4,7% 21,8

Turkmenestan n/a n/a 0,5 0,5 0,1 ** 10,2

Uzbekistan n/a n/a 0,6 0,6 0,1 ** 10,0Other Former SovietUnion n/a n/a 0,7 0,7 0,1 0,1% 15,8Total Former SovietUnion 67,0 58,4 65,4 65,4 9,1 6,3% 24,2

Iran 58,0 92,9 89,7 89,7 12,3 8,7% 69,9

Iraq 31,0 100,0 112,5 112,5 15,1 10,9% *

Kuwait 68,5 97,1 96,5 96,5 13,3 9,3% *

Oman 2,4 4,3 5,3 5,3 0,7 0,5% 15,9

Qatar 3,8 4,5 3,7 3,7 0,5 0,4% 14,7

Saudi Arabia 166,5 257,6 261,5 263,5 36,0 25,5% 87,5

Syria 2,0 1,7 2,5 2,5 0,4 0,3% 12,3

United Arab Emirates 29,4 98,1 97,8 97,8 12,6 9,4% *

Yemen - 4,0 4,0 4,0 0,5 0,4% 27,9

Other Middle East 0,2 0,1 0,2 0,1 ** ** 9,1

Total Middle East 361,8 660,3 673,7 675,6 91,4 65,4% 87,0

Algeria 8,4 9,2 9,2 9,2 1,2 0,9% 20,6

Angola 1,2 2,0 5,4 5,4 0,7 0,5% 19,0

Cameron 0,1 0,4 0,4 0,4 0,1 ** 11,6Rep. of Congo(Brazzaville) 0,4 0,8 1,5 1,5 0,2 0,1% 14,1

Egypt 3,1 4,5 3,5 2,9 0,4 0,3% 10,0

Equatorial Guinea - - ** ** ** ** 0,3Gabon 0,5 0,7 2,5 2,5 0,3 0,2% 20,1

Libya 23,5 22,8 29,5 29,5 3,9 2,9% 57,4

Nigeria 17,4 16,0 22,5 22,5 3,1 2,2% 30,6

Tunisia 2,3 1,8 0,3 0,3 ** ** 10,1

Other Africa 0,1 0,6 0,6 0,6 0,1 0,1% 8,1

Total Africa 57,0 58,8 75,4 74,8 10,0 7,2% 28,2

Australia 2,1 1,7 2,9 2,9 0,4 0,3% 15,0

Brunei 1,8 1,4 1,4 1,4 0,2 0,1% 20,8

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China 20,0 24,0 24,0 24,0 3,3 2,3% 20,6

India 2,6 7,5 4,0 4,8 0,6 0,5% 17,8

Indonesia 9,6 8,2 5,0 5,0 0,7 0,5% 9,7

Malaysia 2,8 3,0 3,9 3,9 0,5 0,4% 14,0

Papua New Guinea - 0,2 0,3 0,3 ** ** 9,4

Thailand - 0,2 0,3 0,3 ** ** 8,6

Vietnam - - 0,6 0,6 0,1 0,1% 5,7Other Asia Pacific 0,4 0,4 0,7 0,8 0,1 0,1% 12,9

Total Asia Pacific 39,3 46,6 43,1 44,0 5,9 4,3% 16,3

Total World 650,1 1011,7 1052,0 1033,7 140,4 100,0% 41,0

Of which: OECD# 98,6 119,1 106,7 85,6 11,3 8,3% 11,8

OPEP 434,0 764,9 800,5 802,5 109,1 77,6% 77,4

Non-OPEC*** 149,1 188,4 186,1 165,9 22,3 16,0% 13,6

n/a Not available.

* Over 100 years.

** Less than 0.05.

# 1979 & 1989 exclude Central European members.

*** Excludes Former Soviet Union.

Source: British Petroleum Statistic Review (1999)

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Table 3. Oil Production

Production*

Thousand barrels daily Change 1999

1999 over share

Proved Reserves 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 1998 of total

USA 9160 8915 9075 8870 8585 8390 8320 8295 8270 8010 7760 -3,8% 10,3%

Canada 1960 1965 1980 2060 2185 2275 2400 2480 2590 2670 2595 -3,5% 3,5%

Mexico 2895 2975 3125 3120 3130 3140 3065 3275 3410 3500 3345 -4,8% 4,8%

Total North America 14015 13855 14180 14050 13900 13805 13785 14050 14270 14180 13700 -4,0% 18,6%

Argentina 490 515 525 585 630 695 760 825 875 890 850 -4,9% 1,2%

Brazil 615 650 645 645 655 680 705 795 855 990 1115 13,0% 1,6%

Colombia 405 445 430 440 460 460 590 635 665 775 840 8,2% 1,2%

Ecuador 285 290 305 330 355 390 395 395 395 385 380 -0,5% 0,6%

Peru 130 130 115 115 125 130 125 120 120 120 110 -7,9% 0,2%

Trinidad & Tobago 150 150 150 145 135 140 140 140 135 135 135 1,1% 0,2%

Venezuela 2010 2245 2500 2500 2590 2750 2960 3135 3320 3510 3125 -11,3% 4,7%

Other S. & Cent. America 75 80 80 75 85 90 95 100 115 125 135 9,5% 0,2%

Total S & Cent. America 4160 4505 4750 4835 5035 5335 5770 6145 6480 6930 6690 -3,7% 9,8%

Denmark 115 125 145 160 170 190 190 210 235 240 300 26,5% 0,4%

Italy 90 90 85 85 90 95 100 105 115 110 110 - 0,2%

Norway 1585 1740 1985 2265 2430 2765 2965 3315 3360 3215 3195 -0,6% 4,3%

Romania 195 165 145 140 140 140 140 140 140 135 130 -2,3% 0,2%

United Kingdom 1925 1915 1915 1975 2115 2670 2740 2730 2705 2800 2895 3,4% 4,0%

Other Europe 520 515 505 490 460 470 440 405 385 370 345 -7,7% 0,5%Total Europe 4430 4550 4780 5115 5405 6330 6575 6905 6940 6870 6975 1,6% 9,6%

Azerbajian 270 255 240 225 210 195 185 185 185 230 280 20,8% 0,4%

Kazakhstan 535 550 570 550 490 430 435 475 535 535 630 15,7% 0,9%

Russian Federation 11135 10405 9325 8040 7175 6420 6290 6115 6225 6170 6180 0,1% 8,8%

Turkmenistan 120 120 115 110 90 85 85 90 110 130 150 15,6% 0,2%

Uzbekistan 65 70 70 80 95 125 170 175 180 190 190 -0,9% 0,2%

Other Former Soviet Union 170 170 160 145 140 140 135 135 140 135 130 -3,7% 0,2%

Total Former Soviet Union 12295 11570 10480 9150 8200 7395 7300 7175 7375 7390 7560 2,1% 10,7%

Iran 2870 3255 3500 3525 3685 3690 3695 3705 3725 3800 3550 -6,7% 5,1%

Iraq 2840 2155 280 525 465 520 575 625 1200 2160 2580 19,4% 3,6%

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Kuwait 1410 965 185 1095 1965 2100 2135 2140 2145 2195 2025 -8,2% 2,9%

Oman 650 695 715 750 785 820 870 895 910 905 910 0,7% 1,3%

Qatar 405 435 420 495 460 450 460 570 695 745 715 -4,4% 1,0%

Saudi Arabia 5635 7105 8820 9100 8960 8875 8890 9035 9215 9220 8595 -7,0% 11,9%

Syria 340 405 470 520 570 570 600 590 580 580 560 -3,4% 0,8%

United Arab Emirates 2025 2285 2640 2510 2445 2480 2505 2660 2665 2725 2505 -8,7% 3,2%

Yemen 180 180 195 185 210 345 350 355 370 380 395 4,6% 0,6%

Other Middle East 55 50 55 55 55 50 50 50 50 50 50 - 0,1%

Total Middle East 16410 17530 17280 18760 19600 19900 20130 20625 21555 22760 21885 -4,0% 30,5%Algeria 1275 1345 1345 1320 1325 1320 1330 1380 1410 1385 1340 -4,0% 1,6%

Angola 460 475 495 550 505 555 630 715 740 730 780 6,9% 1,1%

Cameron 160 155 145 135 130 115 105 110 125 105 95 -9,7% 0,1%

Rep. of Congo (Brazzaville) 160 160 160 175 190 195 185 210 235 275 295 7,0% 0,4%

Egypt 885 905 900 910 945 930 930 900 880 860 835 -3,7% 1,2%

Equatorial Guinea - - - ** 5 5 5 20 65 90 100 9,7% 0,1%

Gabon 205 270 295 290 305 335 355 365 365 335 340 0,9% 0,5%

Libya 1165 1425 1440 1475 1400 1430 1440 1450 1490 1480 1425 -3,8% 2,0%

Nigeria 1715 1810 1890 1950 1985 1990 2000 2140 2305 2165 2030 -6,2% 2,9%

Tunisia 105 95 110 110 100 95 90 90 80 85 85 1,4% 0,1%

Other Africa 35 35 35 30 40 45 50 70 75 70 120 71,3% 0,2%

Total Africa 6165 6675 6815 6945 6930 7015 7120 7450 7770 7580 7445 -2,0% 10,2%

Australia 555 640 605 600 565 610 585 610 670 645 575 -10,7% 0,7%

Brunei 150 150 165 180 175 180 175 165 165 155 180 16,4% 0,3%

China 2760 2775 2830 2840 2890 2930 2990 3170 3210 3205 3195 -0,4% 4,6%

India 730 730 700 640 620 705 790 770 790 780 775 -0,6% 1,0%

Indonesia 1480 1540 1670 1580 1590 1590 1580 1580 1555 1520 1445 -4,7% 2,0%

Malaysia 600 635 660 670 660 675 725 735 765 810 815 ** 1,1%

Papua New Guinea - - - 55 125 120 100 105 75 80 95 18,3% 0,1%

Thailand 50 65 75 85 85 85 85 95 115 120 125 1,0% 0,1%

Vietnam 30 55 80 110 125 140 150 175 200 240 290 20,7% 0,4%

Other Asia Pacific 130 140 145 155 155 140 135 145 155 140 140 0,2% 0,2%

Total Asia Pacific 6485 6730 6930 6915 6990 7175 7315 7550 7700 7695 7635 -0,7% 10,5%

Total World 63960 65415 65215 65770 66060 66955 67995 69900 72090 73405 71890 -2,3% 100,0%

Of which: OECD 18760 18840 19410 19615 19715 20590 20795 21430 21750 21565 21130 -2,4% 28,7%

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OPEP 22830 24555 24690 26070 26870 27200 27560 28425 29730 30910 29330 -5,4% 40,8%

Non-OPEC# 28840 29285 30040 30545 30985 32360 33140 34300 34985 35110 34990 -0,5% 48,4%

Source: British Petroleum Statistic Review (1999)

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Figure 1. IBRD loan to SPC

Figure 2. IBRD or IDA lending through the Country

IBRD/IDA

CountryCommercial

lenders

SPC

ShareBolder

Loan/Credit Project

Agreement

Loans Loans

Equity

IBRD Country

SPC

Comercial Lenders

Sharehold

Guarantee of

loan repayment

LoanLoans

Equity

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Time

Figure 3. The Risk Management Process (Arndt 2000)

Risk Identification

Risk Assessment

Risk Allocation

Risk Mitigation

Risk Management

Risk Eventoccurs

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Figure

Figure 4 Efficient Risk Allocation in the Private provision of Infrastructure (Arndt,2000)

Possible Risk Event

Is one of the parties significantly risk averse?(Is the market immature?)

Is the risk suitable for pass through toconsumers?

Is the consequence of the risk permanent?

Relax service standards for a limited period

seek symmetry of risk allocation(Consider the influence of asymmetric risk preferences)

* Degree of influence overprobability of occurrence or

consequences of the risk* Acess to mitigationechniques

Can the iskclearly bettercontrolled by

one of theparties

Is only risk averse for highmagnitudes?

Allocate risk to that party.(Cap risk if risk averse for high

magnitudes)

Allocate risk to the otherparty.

Allow tariff increase orextend concession

Share the riskMaintain incentive for both

parties(Pro-rata or indept, arbitrator)

YES

NOYES

NO

NO

YES

NO

YES

NO

YES

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Figure 5. Efficient Risk Allocation in the Private Provision of Infrastructure

Entrenchment of Rights

Characteristics:

Very Clear/certain

Inflexible - may restrict future decisions

Types of Risk:

Almost all.

eg. Design and constructions.

Operating risks (generally).

Financing risks

Indermnities such as contamination

Material Adverse Effect

Characteristics:

Less certain but clear framework for

resolution

Allows some flexibility and does notfetter government decisions

Types of Risk:

Limited, specified, potentialy

significant risks which the

government and/or consumers

accept or share.

eg. Networks risks

Change of law and policy

Some force majeure.

Agree to negotiate

Characteristics:

Very Flexibile

Provides litle certainty -may be

inadequate for capital marketfinancing.

Types of Risk:

Limited, unidentifield, very major

risks.

eg. Force majeure

Extreme demand growth

Unforseen risks.

Tariff Adjustment(To be consistent with general risk

alocation)

May be used as a form of redress May be used as a form of redress

Increasing certainty

Increasing flexibility

Increasing frequency of use

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Figure 6. Possible Structure for a Project Finance

SPV

( this SPV was formed to

construct and operate the

Offshore Platform)

Lenders

Security

trustee

Bonding

institutions for

contractors,

subcontractors

and suppliersOperator

Purchasers

and users

Contractor

Insurance Sponsors Governmentagency

Suppliers

Financing

agreement

Repayment of

debt

Surplus of revenue

Bond

agreement

Project revenues assigned to security trustee

O&Magreement

Salesagreement

Constructionagreement

Supplyagreem

Supply

agreement

Concession agreementShareholder

agreement

Insuranceagreement

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Figure 7 . Possible Contractual Structure for a Project Finance (Arndt,2000)

Financial advisers

Technical

advisers

Legal advisers ConstructionContractor

Insurer

SubcontractorsDesigner

SuppliersOperator

SPONSOR

(spv)

regulator

Government

AgencyCustomers

+

End Users

Quasi Equity

Retail Investors

InstitutionalInvestors

Long Term Equity

Mezzanine Debt

Construction Debt

Bondholders

Long Term Debt Bilateral Aid

Agencies

Cofinance

Organisations

Export-Import

Agencies

Equity DebtGovernment Aid

Funding Agreements

Advisers 3rd Party Agreements

GovernmentConcession agreement

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Table 4. Risk Tolerance Ratio Level for some USA Oil Companies (Walls, 2000)

(millions of Dollars)

Ordered on Basis of E&P Assets

Company 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 1984 1983E&P Asset1995

EXXON 36,9 26,2 46,5 33,5 22,1 20,1 17,8 25,3 20,4 22,2 18,4 24,4 39,4 68852

CHEVRON 4,6 7,1 10,0 12,4 15,0 NA NA 28,7 9,8 7,8 8,4 11,3 20,1 27913

TEXACO 176,7 38,1 27,2 27,8 19,7 19,3 205,0 15,6 15,0 12,4 11,1 27,6 11,3 18734

AMOCO 5,2 12,0 16,4 11,5 7,2 3,8 10,2 14,2 12,1 7,2 10,4 13,4 12,4 15241

MOBIL 22,3 27,8 43,7 52,1 533,5 193,7 20,0 12,0 8,0 7,1 5,3 7,4 10,2 14393

SHELL 19,8 29,0 21,7 40,6 47,0 67,8 53,6 55,5 35,0 34,3 50,0 48,9 58,0 11976

USX 10,9 7,4 6,2 158,3 5,3 8,2 6,1 11,7 10,1 9,9 5,0 7,6 45,3 10109

ARCO 23,1 101,7 55,5 31,9 27,6 33,7 22,6 25,8 28,0 32,9 25,9 23,9 35,0 9127

CONOCO 24,6 37,6 38,6 37,1 46,7 60,8 47,6 50,6 45,9 NA 37,4 NA NA 6649

PHILLPS 34,2 20,2 26,1 30,0 38,9 33,4 53,0 116,1 192,0 22,1 20,6 25,0 25,6 4828UNOCAL 87,5 215,7 30,4 35,1 51,0 40,0 35,4 56,8 30,7 NA NA NA NA 4719

OCCIDENT 20,1 36,2 29,7 NA 33,4 51,4 29,7 28,5 31,9 25,3 28,2 23,8 69,9 4594

AMERADA 13,9 30,0 37,2 9,8 NA NA 95,0 10,7 12,1 NA 10,3 9,6 15,9 3873

ANADARKO NA 14,6 11,4 18,4 16,3 23,1 6,1 9,4 9,8 14,8 11,6 15,7 NA 2267

PENZOIL 2,5 4,9 6,8 NA 3,2 2,8 3,9 7,2 NA NA NA NA NA 1992

KERRMCGE NA 26,7 NA NA 13,2 9,0 33,1 10,3 11,5 9,8 13,5 8,5 20,9 1748

UNIONTEX NA NA NA NA NA 9,6 22,6 23,5 11,3 15,5 15,7 33,9 46,6 1695

13423956 project finance modelling in the angolan oil industry 2001

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