8.3. A Closer Look at the Stakeholders and Their Investment Decision Making

To uncover the feedback structure of the oil industry the modeller led a discussion of the investment decision making of each main producer group. The same formulation principles introduced in Chapter 7 apply once again, including the Baker criterion, fit to industry practice, robustness and recognition of bounded rationality. For example, what do executives in commercial oil companies know and pay attention to as they make their upstream investment decisions? What information really matters to OPEC oil ministers as they agree quotas and set production targets? Which organisational, social and political factors shape and filter the signals used by different producer groups and their leaders to justify investment and production decisions? The diagrams that follow are similar to the flip-chart drawings from team meetings in which all these questions, and more, were thoroughly explored. Two versions of the model are described that differ only in their assumptions about the available pool of commercial reserves and development cost per barrel. The first version of the model reflects conditions in 1988, during the Soviet era, when the oil market excluded communist areas. The second version reflects conditions in 1995 when Russian oil was trading in the world market. A selection of equation formulations is included in the description that follows. Full documentation of the equation formulations can be found in the file named Oil World 1988 Equation Description in the CD folder for Chapter 8.

8.3.1. Investment by the Independent Producers

The independents are all those producers – state-owned oil companies, the majors and other private producers – that are not part of OPEC and who expand crude oil output on the basis of commercial criteria. This category includes international oil companies such as BP Amoco, ExxonMobil and Shell, and non-OPEC nations such as Norway. The independents are assumed to produce at economic capacity all the time. Their production rate is therefore dictated by available capacity. The rationale for capacity expansion is dominated by commercial factors as shown in Figure 8.4. The circular symbol represents independent producers' upstream investment or capacity expansion policy – often known as 'capex'. The independents add new capacity when they judge it is profitable to do so.

The figure shows the main information inputs to upstream investment decisions used to calculate the average profitability of potential projects. Independents estimate the development costs of new fields and the expected future oil price over the lifetime of the field. Knowing future cost, oil price, the likely size of a new field and the tax regime, financial analysts can calculate the future profit stream and apply a hurdle rate to identify acceptable projects. In reality, each project undergoes a thorough and detailed screening, using well-tried upstream investment appraisal methods. The greater the estimated profitability, the more projects exceed the hurdle rate and the greater the recommended expansion of capacity. There is a scale effect too represented by information feedback from independents' capacity. The more capacity, the bigger are the independents and the more projects in their portfolio of investment opportunities.

Executive control of recommended expansion is exercised through capex investment optimism that captures collective investment bias among top management teams responsible for independents' investment (rather like 'delivery delay bias' in the market growth model of Chapter 7). Optimism can be viewed on a scale from low to high. High optimism means that oil company executives are bullish about the investment climate and approve more capacity expansion than financial criteria alone would suggest. Low optimism means executives are cautious and approve less expansion than recommended. It is important to appreciate the distance from which we are viewing investment appraisal and approval. We are not concerned with the detail of individual oil field projects. Rather, we are seeing investment in terms of commercial pressures that lead to fractional growth of existing capacity, where the growth rate can be up to 25 per cent per year. The formulation is explained in more detail later.

8.3.2. Development Costs

Development costs in Figure 8.5 are experts' views of industry marginal costs as a function of remaining undeveloped reserves. In 1988, experts estimated remaining reserves to be 580 billion barrels of oil. Of this quantity, about 30 billion barrels (in the decreasing range 580 to 550 on the graph) were believed to be low-cost reserves recoverable at less than $9 per barrel. Once these low-cost reserves are used up there is a steep shoulder to the cost profile. Development cost rises from $9 per barrel to $26 per barrel as reserves fall from 550 billion to 450 billion barrels – a fall of 100 billion barrels. Then the cost profile stays quite flat, rising gently to 40 dollars per barrel as reserves fall from 450 billion to 100 billion barrels. Thereafter, the cost rises gently to 44 dollars as reserves fall to 50 billion barrels. Cost rises sharply to 1000 dollars per barrel as reserves are exhausted reflecting an assumed finite supply of commercially viable oil.

By 1995, experts' views had changed. Remaining reserves were now thought to be about 470 billion barrels - down by more than 100 billion barrels from the 1988 estimate of 580 billion barrels due to usage. However, the cost is much lower and the profile is flatter than before meaning that cost is expected to rise less steeply with depletion. Cost rises gently from 12 dollars per barrel to 20 dollars per barrel as reserves fall 470 to 100 billion barrels. Moreover, there is a new possibility of replenishing low cost reserves by adopting 240 billion additional barrels of Russian oil. For this reason the scale for reserves runs out to 710 billion barrels. The process of adoption is described later in the section called 'Incorporating the Unforeseen'. The overall effect is to further flatten development cost.

Technology can undoubtedly be expected to lower cost as more efficient production and recovery methods are devised. In both the 1988 and 1995 models the effect of technology on cost starts at a neutral value of 1 as shown in Figure 8.6.

In 1988, experts anticipated that technology would improve rapidly over the decade 1988 to 1998, so the effect of technology on cost falls to a value of 0.64 by 1998. This fall means that technology improvements were expected to cut development cost by 36 per cent (1−0.64) over the decade. Interestingly, the experts in 1988 were very conservative beyond a 10-year technology horizon, anticipating no further efficiency improvement. Hence, after 1998 the effect of technology on cost remains constant at 0.64. By 1995, experts' views of technology were more optimistic for the long term and they were prepared to look across a 25 year horizon. The effect of technology on cost falls steadily to a value of 0.5 by 2020. This fall means that technology improvements were expected to cut development cost by a further 50 per cent relative to the advances already made by the end of 1995.

8.3.3. Policy Structure and Formulations for Upstream Investment – Fractional Asset Stock Adjustment

More detail about the formulations behind the investment policy is shown in Figure 8.7. Notice the two-stage accumulation for capacity that distinguishes capacity in construction from independents' capacity in operation. The annual onstream rate is assumed to be a quarter of capacity in construction to represent an average construction delay of four years. Independents' production is exactly equal to production capacity, reflecting an important assumption that commercial producers fully utilise capacity once it comes onstream.

The grey region contains all the variables used to operationalise the investment policy. Capacity initiation (the rate of approval of new upstream investment) is a fractional asset stock adjustment formulation, similar to capital investment in the market growth model in Chapter 7, but driven by financial rather than operational pressures. The units of measure are millions of barrels per day, per year. The equation is written as the product of independents' capacity, viable fractional increase in capacity and capex optimism.

Upstream investment projects are deemed attractive when the profitability of new capacity exceeds the hurdle rate. In the equation below this condition is met when the profitability ratio is greater than one. The hurdle rate is set at (0.15) 15 per cent per year, a high value that reflects the inherent risk of upstream investment. The profitability of new capacity depends on the total profit expected from a new oil field in relation to its development costs. Total profit is defined as the difference between expected future oil price and current development cost per barrel multiplied by the average size of a field in millions of barrels. This gross profit is adjusted for tax according to the expression (1 − tax rate). The ratio of total profit to overall development cost then yields profitability expressed as a fraction per year.

The profitability ratio determines the viable fractional increase in capacity through the non-linear function in the equation below. When the profitability ratio takes a value of 1 the fractional increase in capacity is a modest six per cent per year (0.06). The function is upward sloping. When the profitability ratio is 1.5, the fractional increase in capacity is 18 per cent per year. At even higher profitability the function levels off at a fractional increase of 25 per cent per year, which is assumed to be the maximum rate of capacity expansion achievable in the industry.

8.3.4. Oil Price and Demand

It is common to think that market forces simultaneously determine price and demand. But in dynamical models it is important to capture the separate processes that adjust price and demand and the information on which they depend. Figure 8.8 shows demand for oil as a stock that accumulates change in demand. Similarly market oil price is a stock that accumulates change in price. The influences on these two processes of change were the focus of attention in conversations with the project team.

Change in demand responds to market oil price, the effect of the global economy and environment, and to the level of demand itself. In the short to medium term, the basic rationale behind demand changes is straightforward. When price goes up, demand goes down and vice versa. In reality, there are more subtle dynamics of demand. For example, if there is a shock price increase, the resulting reduction in demand will be greater than if the same price increase were spread over a few years. Consumers modify demand quickly in the short run by conservation and easy substitution. But they can also continue adjusting in the long run by making improvements in energy efficiency – with more fuel efficient cars, or more heat efficient homes.

Price sensitivity combines short- and medium-term dynamic effects. A numerical example illustrates the idea. Suppose price is steady at $20 per barrel, then rises suddenly to $30 per barrel and settles at this new and higher value. The model assumes that consumers faced with this 50 per cent price hike set out with the intention of reducing demand by 20 per cent. Yet, radical cuts in consumption are slow to implement. It takes years for people to switch to more fuel-efficient cars or better insulated homes. In the meantime, they get used to a higher oil price and the pressure to reduce consumption declines. What began as an intention to reduce demand by 20 per cent is much diluted as time passes to 5 per cent or less. Effectively, people are hooked on oil, and consumption depends not on the absolute oil price but on the difference between the current oil price and the price people are used to.

In the long term, there are broad societal and global pressures on demand, captured in the effect of the economy and environment. This effect is formulated as a bias so that indicated future demand for oil is either magnified or diminished relative to current demand. For example, if the global economy continues to grow over the next decade, led by China and India, then there will be steady upward pressure on demand for oil. On the other hand, if, in response to global warming, society curbs its use of fossil fuels, then there will be steady downward pressure on demand for oil. These long-term pressures are superimposed on the price effect.

In the lower half of Figure 8.8 the change in market oil price responds to differences between demand and total production. If demand exceeds total production then there is persistent pressure for price to rise. A fractional formulation is used in which the change in price is a fraction of the current market oil price. Therefore, as long as a demand surplus persists, price will move steadily upwards. Conversely, if production exceeds demand, there is persistent pressure for price to fall. Note there is no pre-defined ceiling or floor on oil price and the development cost of oil does not directly influence change in price. Only when demand and production are exactly equal does the change in price become zero. Hence, oil price can drift across a wide range of values, far removed from the underlying development cost incurred by commercial producers. A numerical example reveals the sensitivity of the modelled oil price to production and demand imbalances. When there is a shortfall of 2 million barrels per day, price is assumed to increase at a rate of 4 per cent per month. The rate of increase rises to 7.5 per cent per month if the shortfall reaches 4 million barrels per day. There are corresponding rates of price decline resulting from a glut of production. These numbers produce plausible price profiles in the simulator.

8.3.5. The Swing Producer

The role of the swing producer is to supply just enough oil to defend OPEC's intended price, known in the industry as the 'marker price'. A producer taking on this role must have both the physical and economic capacity to increase or decrease production quickly, by as much as 2 million barrels per day or more in a matter of weeks or months, in order to absorb unexpected variations in demand (due say to an unusually mild winter) or to compensate for cuts in the output of other producers. The model makes the important assumption that the swing producer always has adequate capacity to meet any call. The project team felt this assumption was reasonable given the large capacity surplus of Saudi Arabia, estimated at 5 million barrels per day under normal supply conditions. As long as Saudi maintains this huge surplus then there is no need to model explicitly the capacity expansion policy of the swing producer, since capacity is never a constraint on output. Instead, the focus switches to the rationale for changes in crude oil production.

The swing producer (Saudi Arabia) operates in either swing mode or punitive mode. Most of the time Saudi is in swing mode, abiding by and supporting the production quotas set by OPEC. Occasionally, Saudi switches into punitive mode, by abandoning agreed quotas and rapidly cranking up production in order to discipline the other producers.

Figure 8.9 shows the factors influencing Saudi production policy when operating in normal swing mode. Production responds to pressure from both quota and oil price. There are two stock adjustment processes operating simultaneously. Saudi ministers change production in order to meet the swing producer's quota, but they also take corrective action whenever the market oil price deviates from the intended price that OPEC members collectively wish to achieve. When the price is too low, Saudi production is reduced below quota thereby undersupplying the market and pushing up the market price. Similarly, when the price is too high, Saudi production is increased above quota to oversupply the market and reduce price to the level OPEC is trying to defend. Such willingness to adjust production in the short term is in sharp contrast to the independent producers and is a defining characteristic of any swing producer.

In punitive mode, Saudi oil ministers feel that production is inadequate and they are not getting a fair share of the market. They decide to re-establish a strong position by increasing production regardless of the price consequences, thereby also punishing the other producers. The resulting punitive production policy is shown in Figure 8.10. The swing producer sets a minimum threshold for share of global demand (estimated to be 8 per cent) and will not tolerate anything less. Whenever market share falls below the threshold the volume of production is increased rapidly in order to flood the market with oil and quickly lower the price.

The team spent some time discussing the detail of punitive behaviour. For example, how does the swing producer decide on the volume of punitive production, and when do policymakers switch back to swing mode? The team's proposal was to include a punitive price, a very low target price, for teaching a lesson to the other producers. Punitive production continues to expand until market oil price reaches the punitive price, or until the swing producer regains an acceptable market share (which is the signal to return to swing mode). The switch to punitive mode can send a powerful price signal to discipline the other producers. It is an act of last resort, however, because in this mode the swing producer has abandoned the role of price regulator – essentially the market is no longer managed.

8.3.6. Quota Setting

Quota setting takes place in two stages. First, OPEC members agree on a quota for the cartel as a whole. Then, member states negotiate individual quotas by allocating the total quota among themselves.

How much should OPEC produce? The main influences are shown in Figure 8.11. The members need to form a view of the likely 'call on OPEC' over the time period covered by the quota agreement. To do this, they estimate global oil demand and the independents' production. The difference is the estimated call on OPEC. If you think about it, the estimate is just a best guess of the volume of OPEC oil required to balance supply and demand, but the estimate need not be spot-on. In practice, it could differ from the actual call by as much as 1 or 2 million barrels per day. The swing producer will compensate for any mis-estimation by OPEC through swing changes to production. More important than spot-on estimation of the call is for OPEC members to agree on whether to set an overall quota that is deliberately less than the estimated call, or deliberately more. By setting a quota that is less than the call, the member states are pursuing a policy aimed at increasing market prices. Their decision to over- or under-produce is politically and economically motivated and is represented by the scenario parameter 'cartel quota bias'.

Quota negotiation, shown in Figure 8.12, allocates OPEC's agreed quota among members. In reality, the negotiation is a highly political process, though a benchmark allocation is established based on objective criteria that include member states' oil reserves, production capacity and population. In the model, quota is allocated in proportion to each member's share of OPEC's total operating capacity. Although this formulation is a simplification, it does capture the flavour of political bargaining by making the members' bargaining strength proportional to capacity share.

8.3.7. The Opportunists

The opportunists are all the other members of OPEC besides the swing producer. Some of the opportunists are known to adhere strictly to quota, so their production policy is straightforward – it is simply equal to negotiated quota. Other countries, however, have a huge appetite for oil revenue to support their growing populations and developing economies. This need for revenue, coupled with underutilised production capacity, provides opportunists the motivation to exceed quota and to strengthen their quota negotiating position by deliberately over-expanding capacity.

Figure 8.13 shows the main influences on opportunists' production and capacity. First, focus on change in capacity shown in the lower half of the figure. Generally speaking, opportunists aim for surplus capacity, at least 2 or 3 per cent more than negotiated quota, partly to provide flexibility, but also to improve their bargaining position in future quota negotiations. The size of the surplus depends on a scenario parameter called capacity bias, which represents the tendency of opportunists to overbuild capacity. Opportunists' change in capacity is formulated as an asset stock adjustment process where the effective target for capacity is equal to negotiated quota multiplied by the capacity bias.

Now consider opportunists' production shown in the upper half of the figure. When opportunists are fully cooperating within the framework of the cartel they produce at a rate equal to the negotiated quota. But there is always the temptation for opportunists to exceed quota and fully utilise capacity – if only they can get away with it. How do opportunists know whether conditions are right for utilising surplus capacity and quota busting? The project team felt that the 'apparent cohesion' of the cartel would be an important factor. Cohesion is high when the market oil price is close to the intended marker price – in other words, when OPEC is successfully defending its intended price. Under these price conditions, quota busting may go unnoticed. Cohesion is low when the intended marker price is greater than the market price. Under these price conditions, quota busting is likely to be visible and to incur the wrath of the other member states, especially the swing producer. Figure 8.13 shows that both the intended marker price and oil price influence opportunists' production, and the inset on the upper right shows the assumed shape of the relationship between the price gap and surplus utilisation. When the price gap is in the range minus $4 to minus $5 per barrel surplus utilisation is zero. As the price gap diminishes surplus utilisation rises, slowly at first and then more rapidly. When the price gap is zero then opportunists fully utilise surplus capacity.

8.3.8. Russian Oil – Incorporating the Unforeseen

No scenario planning exercise has perfect foresight and the oil producers' project was no exception. The model was originally built in 1988 and then updated some years later to fit the global oil industry of the mid-to-late 1990s. The most significant political change during the interval was the break up of the Soviet Union. Before the Soviet break-up, oil companies and scenario planners ignored oil production from communist areas. This assumption was justified on the grounds that little if any such oil was traded outside the communist block. However, President Gorbachev's perestroika and peaceful revolution eventually brought Russian oil to world markets. Moreover, Russian reserves are huge – about 225 billion barrels, almost six per cent of proven global reserves and more than 50 per cent of non-OPEC reserves. Freely-traded Russian oil can therefore have a big impact on the global balance of supply and demand.

A member of the original scenario modelling team helped revise the model to include Russian oil. A key issue was how to classify Russian reserves – do they fall within the influence of OPEC, or are they best viewed as purely commercial reserves? After careful thought, the industry expert recommended that all Russian oil should be added to independents reserves. In other words, in his view, the oligarchs controlling Russian oil have commercial rather than political instincts. They prefer to develop reserves in response to market forces rather than OPEC political pressure. Profit matters. However, he also recognised that Russian reserves are not instantly available for commercial exploitation, even if the economics look favourable. There is still a political dimension to Russian oil representing the time it takes to build the trust required for long-term commercial contracts and to agree rights in the key Russian oil regions.

When viewed in this quasi-commercial way, Russian oil adds two new stock accumulations and six new concepts to the original model – only a small increase in complexity price for such an important structural change in the oil world.

Figure 8.14 shows the change exactly as it appears in the revised oil producers' model. A huge pool of risky Russian reserves, approximately 225 billion barrels, is available to commercial producers. Gradually, over time, these reserves come to be viewed by investors as secure. Secure Russian reserves are then adopted by commercial producers into the pool of independents' undeveloped reserves. The pace of adoption depends on the time to agree rights, which is set at 3 years.

The crucial limiting process for commercialisation is the rate at which investors reclassify risky reserves. This rate depends on a vital scenario parameter called 'time to build trust in Russia', which can be anywhere in the range 5–40 years. If the time is short (say 10 years), then Russian oil fields are commercialised quickly. If the time to build trust is very long (say 40 years), then Russian oil, though economically attractive, is commercialised slowly.

Two versions of the oil producers' model are available in the CD folder for Chapter 8: Oil World 1988 and Oil World 1995. Simulations of these two models reveal the impact on the industry of Russia's massive 225 billion barrel oil legacy which, up to 1989, nobody ever expected the free world to access.