APPRAISAL OF ECONOMIC PERFORMANCE OF GLOBAL EXPLORATION CONTRACTS

David A. Wood
International Petroleum Corp.
Dubai United Arab Emirates

An economic evaluation of 20 international exploration and production contracts shows a large diversity in their structure and in the post-tax profits a company can expect to receive from production controlled by them.

A systematic method for evaluating and comparing contract performance enables the relative importance of the key variables responsible for profit levels under the terms of a specific contract to be clearly identified.

Factors that limit a company's profits in a contract, such as cost recovery allowance, a government's right to back-in for an extra share of production, or an additional tax can be modeled for the purposes of contract negotiation or project evaluation using the techniques reviewed.

The results of the evaluation are presented graphically in order to provide a simple but comprehensive frame of reference against which the performance of other contracts may be compared.

E&P contract terms, combined with a number of other factors, determine the profitability of a project.

The reserves, costs to develop, production rates, operating and transport costs, oil and gas prices, and risks (exploration and political) associated with a project are the main factors that govern its profitability under the terms of the E&P contract.

A poor contribution by any one of these component factors can make a project uneconomic regardless of the quality of the other factors.

This analysis should be specifically useful to companies in the process of expanding internationally but without access to the detailed contract terms of many countries or computer models with which to evaluate them.

CONTRACTS EVALUATED

Twenty contracts currently in operation or recently terminated have been used as the data base for this study.

Each has been assigned a letter from A to T. This data base of contracts includes six from South America, five from Africa, four from the Middle East, four from the Far East, and one from Europe.

The countries and concessions to which each contract pertains cannot be disclosed for reasons of confidentiality.

Based on their fiscal structures these contracts can be subdivided into two main types, taxation driven and production driven, and seven sub-types as follows:

Taxation driven
1. Double taxation system with the liability to one tax controlled by the cumulative revenue to cumulative expenditure ratio, as in Contract A.
2. Double taxation system with the liability to one tax controlled by the contractor's rate of return calculated annually over the life of the project, as in contracts F and D.
Production driven 2a. Production splits are fixed, or varied on a sliding scale according to daily flow rates, and the contractor pays no income tax but in some cases a fixed royalty is taken from gross production.
These terms apply in contracts J, M, 0, R, and S. The production split for Contract M is one fixed percentage regardless of production rates, etc.
1. Production splits are fixed, or varied on a sliding scale according to daily flow rates, the contractor pays income tax on its profits, and in some cases a fixed royalty is taken from gross production.
  These terms apply in contracts B, E, G, H, 1, K, Q, and T. The production splits for contracts E and K are one fixed percentage regardless of production rates, and so on, although in the case of Contract E this can vary from field to field.
2. Production splits vary according to the contractor's cumulative revenue to cumulative expenditure ratio, with the contractor's share of production then being exempt from taxes, as in contracts N and P.
3. Production splits vary according to the contractor's rate of return calculated annually over the life of the project, with the contractor's profits additionally being subject to income tax as in Contract C.
4. Production splits vary according to the cumulative volume of reserves produced, with the contractor's profits additionally being subject to income tax as in Contract L.

There are two other specific characteristics of the contracts that are relevant to the results of this evaluation and can also be used to group and compare some of the contracts.

Those contracts in which the respective government or state oil company has the obligation to pay a share of development and operating costs. In some cases this is an option rather than an obligation.
1. Government pays more than 30% of capital and operating costs, as in contracts C, E in certain cases, H, K, L, N, and P. In the case of Contract C this is optional.
2. Government pays less than 30% of capital and operating costs, as in contracts E in certain cases, F, G, 1, S, and T. In contracts F, 1, and S this is optional.
  For this evaluation, in those contracts where the state oil company has the option to back-in to part of the contractor's share of production by paying a proportionate share of the costs, it is assumed that this option is exercised.
Those contracts in which the maximum allowance of production from which development costs incurred by the contractor can be recovered is limited to 50% or less in any year, as in contracts N, 0, P, Q, R, S, and T.
It should be understood that although the fiscal structures of the 20 contracts studied are representative of the international contracts being signed by the oil industry, other contracts exist and will undoubtedly be developed in the future that do not fall into any of the sub-groups outlined above.

Thus the above sub-division is designed for the contracts considered in this study and not as a comprehensive classification scheme for international exploration and production contracts.

EVALUATION METHODS

The type of evaluation procedure required depends to some extent on the overall objectives of the study required.

The most common objectives for such studies are:

To compare a new venture contract with those in an existing portfolio.
To establish the terms to be sought for an E&P contract being negotiated with a state authority.
To value and-or rank a portfolio of E&P contracts and prospects in order to select a drilling order.
Evaluate farmin or farmout projects.

For objective A the main steps of the evaluation procedure required are as follows:

Construct a computer program to combine petroleum production profiles, expenditure profiles, and the fiscal structure of each E&P contract in order to generate a post-tax cash flow for the contractor.
The cash flow calculated needs to be post-tax as the income tax rates and allowances vary significantly from contract to contract.
Analyze the cash flows produced in 1) by calculating a suite of relevant economic indicators discounted at various percentages where applicable.
In practice steps 1 and 2 would be calculated within the same computer program.
One method of doing this is to use commercially available spreadsheet software. It is possible with only limited experience to produce in a matter of hours a spreadsheet model for some of the most complex contracts.
Because of the diversity in the structures of E&P contracts it is the author's preference to develop a separate spreadsheet for each E&P contract rather than use complex coded programs that attempt to cope with all the different possible contract structures in a single package.
However, some all-embracing programs are commercially available, widely used, and also capable of producing the same answers.
Use the computer program to evaluate a set of hypothetical model "oil fields" each with selected reserves, production profiles, and cost profiles that evaluate specific attributes of the E&P contracts.
In this study three field sizes are used, with recoverable reserves of 15 million, 50 million, and 350 million bbl of oil. The details of these fields are listed (Table).
In practice there are advantages to considering some additional model oil field sizes between 50 million and 350 million bbl, especially when evaluating contracts in which production splits are dependent upon thresholds of production rate or reserves produced.
It is for brevity that they are excluded here. The two smaller "fields" were selected to test the lower end of the production split scales (where applicable) with peak production rates of 6,600 b/d and 20,000 b/d.
These fields have been assigned high capital and operating expenditures in order that they test the cost recovery mechanisms of the E&P contracts.
The large field has been assigned a peak flow rate of nearly 120,000 b/d to test the complete production split scale in most contracts.
Carry out a sensitivity analysis for each field size and each E&P contract using the computer program and vary the key input parameters of the base case field models by specific percentages.
Using a large computer it is possible to run thousands of sensitivity cases for each variable. However, if the sensitivity cases are carefully selected, it is possible to obtain almost the same results using some 20 cases for most contract structures.
The key input parameters that have been varied in this study are: capital expenditure, operating expenditure, inflation rate for capital and operating expenditures, oil price through production period, flow rate of the wells, and time of production start-up.
In this study for each E&P contract and field size a base case and 18 sensitivity cases were run. For 20 contracts and three field sizes this amounts to 1,140 cases.
The values of five key economic indicators were recorded for each case, and if a range of discount factors had been used this number could easily have doubled. Thus, even the modest sensitivity analyses presented require the generation and synthesis of more than 5,000 numbers.
Establish the values of key input parameters that are required to generate specific values of key economic indicators for each E&P contract and field size using the computer program.
As with the sensitivity analysis of the input parameters there is an infinite number of cases that can be run. In this study the author has one as an example, i.e., the oil price in dollars per barrel required to provide investor's rate of return of 15% for each field size and E&P contract.
Analyze the results calculated for the key economic indicators statistically and graphically to relate trends in these indicators to specific aspects of the fiscal structures of the E&P contracts studied.
Select the graphical illustrations of the economic indicators most suited for the contract and-or prospect evaluation objective being performed.
For objective B the evaluation procedure is almost the same as for A except that an additional sensitivity analysis would be performed on the negotiable fiscal terms.
For objectives C and D the hypothetical fields of step three of the procedure for objective A are replaced by real prospects or fields, and a new step 4 would be introduced consisting of risk analysis.
Also the sensitivity analysis of input parameters could either be replaced or supplemented with a Monte Carlo simulation, as the range of uncertainties associated with the input parameters of each prospect should be established well enough to express as probability distributions.
Some additional risk weighted economic indicators (including certain cash flow to investment ratios) become of value for objectives C and D.
For objective D a final step of sensitivity analysis is required to establish what acquired or farmed out interest in a project optimizes the appropriate economic indicators.
The evaluation presented here concentrates initially on objective A but touches on aspects of objectives B, C, and D in order to clarify the relative importance of contract terms to the economic analysis with those objectives.
In establishing the relative performance of E&P contracts using the above methodology it is accepted that some of the assumptions are somewhat artificial and designed for the ideal world.
For example, in all cases it is assumed that the contractor has no sunk costs or other past expenditures in a concession or country that can be used to reduce his tax liabilities under an E&P contract. Moreover, it is assumed that there is a similar tax treaty in effect between the country of each contract and the country in which the parent company of the contractor is registered and liable for taxes.
In the real world this is not the case and, regardless of the relative performance of the contracts, for a particular contractor such additional factors could make contracts in one area more favorable than another despite them having a poorer economic performance in terms of fiscal structure.

Also it is clear that model fields do not reflect the real world, except by chance, for most contract areas.

For example, an oil field of a particular reserve size would have very different capital, operating, and transportation cost profiles depending on the geographic location of both field and contract area, the depth and flow rates from the reservoir, and the distance from existing infrastructure and markets.

Thus, evaluating the economic results generated for a set of contracts with model field sizes can only be the first step in establishing the true performance of each contract.

The next step is to evaluate each contract with a field size and cost, production and tax profiles appropriate for the contract area and the contractor. This will provide a better idea of the real value of the contract terms and lead on to the analysis of real prospects and-or fields in the contract area.

Notwithstanding the above, evaluating contracts with model fields is the only way to obtain an objective comparison of the economic performances of a set of contracts.

ECONOMIC COMPARISON RESULTS

Here are results of such an analysis on the set of 20 international contracts referred to in the first part of this article.

KEY INDICATOR CROSS-PLOTS

The net present value discounted at 15% (NPV-15%) is plotted against the percentage of post-tax profit revenue to the contractor using the base case field parameters (Table) for each contract.

The 15 million bbl oil field shows good positive correlation between these two economic indicators.

The variation among the contracts is remarkably high; the percentage profit revenue to the contractor varies from about 7.5% to 55%. There is also extensive variation recorded by all other commonly used economic indicators.

Those contracts with poor cost recovery mechanisms have been circled to show that they plot below the main trend. This demonstrates that for a given percentage of profit to the contractor such contracts provide the contractor with a lower NPV-15% than contracts with better cost recovery provisions.

Although the contractor gets a certain percentage of profits, he gets it later with the poor cost recovery contracts. Hence when the time value of the profits is considered, by economic indicators such as NPV, investor's rate of return (IRR) etc., this relatively late payout is distinguished.

The payout time in years time from the start of investment until the cumulative cash flow becomes positive--also discriminates such contracts.

Five contracts have NPVs below zero. This indicates that if a company considers a discount rate of 15% as its yardstick for profitable ventures, this 15 million bbl field would be uneconomic under those five contracts.

Fig. 1 for the 50 million bbl field shows a similar trend, but only one contract distinguishes the field as uneconomic. The same contracts with poor cost recovery mechanisms are also readily distinguished.

Contract C plots significantly above the main trend. This is because in Contract C the contractor's production split is controlled by its periodic rate of return; i.e., the contract optimizes the contractor's IRR for a given percentage of profits when the IRR of the project is less than 30%.

This also has the effect of providing the contractor with a higher NPV relative to its percentage share of profits than other contracts in such cases.

Fig. 1 for the 350 million bbl field shows a much higher degree of correlation and less scatter between these parameters than the smaller fields. This field is economic under all the contracts assuming a 15% discount factor is the appropriate threshold.

Because of the higher revenue levels of a large field, costs can be recovered in an adequate time frame, even using those contracts with poor cost recovery provisions. Consequently the poor cost recovery contracts are not distinguished from the main trend on this graph.

This demonstrates that the cost recovery allowance is most important for fields with a low revenue-high cost ratio.

Contract C is also not distinguished from the main trend. It is distinguished on a plot of IRR vs. percent profit revenue (not shown here), because the contract provides the contractor with its greatest profit share early in the production history but then dramatically reduces the contractors profit share in later years.

However, for the major part of the contractor's production share the production split to the contractor is low, because the periodic rate of return is above 30%, and therefore the contractor's revenue, total discounted cash flow, and percentage of profit revenue are reduced.

Contract C is a good example of where using IRR as the only economic indicator a company might tend to overvalue projects due to the high IRR values calculated, despite lower overall revenues and NPVs.

Previous studies have demonstrated how IRR can be an unreliable economic indicator, and this provides a further example.

In Fig. 1, it is of interest to note that the order of the contracts changes significantly.

Whereas some contracts become relatively more profitable for the larger fields, such as G and Q, others become relatively less profitable, such as A, F, and D--the taxation driven contracts.

Contracts Q and A are highlighted to emphasize these different relationships, which are due to the large variation in the fiscal structures of the contracts studied. It is therefore important to evaluate more than one field size when performing a comparative economic analysis of contract terms.

DATA REDUCTION

For interpretation it is necessary to reduce the quantity of numbers involved in the sensitivity analysis of the input variables in a statistically meaningful way.

Hence an arithmetic mean and a standard deviation for each economic indicator have been calculated for the 19 sensitivity cases run for each field size and contract evaluated.

Due to the symmetrical design of the sensitivity analysis performed--the input parameters are varied by about the same positive and negative percentages from a base case--the calculated means are very close to the respective base case values.

However, the spread of data about the means, given by the standard deviations is a good indication of how sensitive the respective contracts are to the input variables used.

Fig. 2 illustrates for the 15 million, 50 million, and 350 million bbl fields, respectively, the arithmetic mean (dot) plus and minus one standard deviation (bar) for the percentage of post-tax profit revenue to the contractor.

The x axis in these graphs is the constant oil price value required to provide the contractor with an IRR of 15% for the base case field input parameters (Table). This provides a synthesis of the results of the sensitivity analysis performed on both input parameters and economic indicators.

These graphs are particularly instructive about the relative economic viability of the contracts for specific field sizes. They also indicate those contracts in which the greatest uncertainties exist in the level of contractor profits to be expected.

A reasonable negative exponential correlation exists between these parameters for the 15 million bbl field.

Contract C falls below the main trend for reasons explained above.

This field is only economic, assuming a 15% IRR threshold, with eight contracts for a constant oil price of $20/bbl. The field becomes economic with 15 contracts for a constant oil price of $23/bbl.

The contracts with the poorest cost recovery mechanisms--0, P, Q, R, and Shave large standard deviations. This is because the profit revenue to the contractor, and other economic indicators, drop significantly for the high cost sensitivity cases as these costs have to be recovered from the contractor's "profit oil" split.

The standard deviations for the taxation driven contracts are also quite high in Fig. 2 for the 15 million bbl field, particularly for Contract D. This is because the secondary taxes in these contracts become payable, or the rates increase dramatically, at certain economic thresholds.

They are designed this way to help small fields to be economic for the contractor even in a low oil price environment. The high and low sensitivity cases straddle these thresholds, thereby resulting in a wide range of profitabilities for the contractor under the terms of Contract D.

For the 50 million bbl field the relationship of these parameters is similar to that shown for the 15 million bbl field but with a greater scatter.

This field is economic (assuming a 15% IRR threshold) with 14 of the contracts for a constant oil price of $20/bbl. The field becomes economic with 19 contracts for a constant oil price of $25/bbl.

Those contracts in which the state oil company contributes significantly to the development and operating expenditures (C, H, K, L, N, and P) of the field plot distinctly on the lower side of the trend. This indicates that by paying less the contractor recovers a smaller share of the profits.

The negative correlation between these parameters is very poor for the 350 million bbl field size.

The standard deviations of the contractor profit revenue for all contracts, except Contract S (zero cost recovery), are small. This indicates that the level of contractor profit is much less sensitive to uncertainties in cost, prices, and production rates than for the smaller fields.

This field is economic (assuming a 15% IRR threshold) with 1 0 of the contracts for a constant oil price of $10/bbl. The field becomes economic with 19 contracts for a constant oil price of $15/bbl.

The scatter in Fig. 6 is caused by three groups of contracts:

The tax driven contracts tend to plot towards the bottom left corner on this graph. This reflects taxes limiting contractor profits at high revenue levels. However, these contracts remain economic at very low oil price thresholds, due to lower taxation rates or allowances against taxes when projects become less profitable.
The production driven contracts with relatively low average production splits, and-or with high associated income tax rates, also plot towards the bottom left corner on this graph.
This is due to these contracts limiting the contractors profits for the larger fields or, more correctly, for fields with high daily production rates.
The contracts with poor cost recovery mechanisms plot towards the upper right corner on this graph. This signifies that providing revenues are sufficient for contractor costs to be adequately recovered from the cost oil allowance these contracts are capable of being highly profitable.

However, the economic threshold of these contracts remains at a relatively high oil price. As the oil price falls it becomes increasingly difficult for the contractor to recover costs and maintain profits with these contracts.

The relationships between the mean and standard deviations of NPV, IRR, and payout time when plotted against the constant oil price required to provide the contractor with an IRR of 15% show similar trends to those illustrated for percentage of profit revenue in each element of Fig. 2.

END PART 1 of 2