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Oil supply disruptions and modelling methodologies
Oil supply disruptions and modelling methodologies The role of LP models
T. Randall Curlee, Anthony F. Turhollow and Sujit Das
This paper has three main objectives. First, an argument is made that oil vulnerability is not a problem of the past, but remains a sig@ant concern for all oil-consuming countries, especially beyond 1990. Second, it is suggested that the severity of past disruptions can be attributed, in part, to physical and institutional constraints that prevented the oil market from reacting quickly to what were relatively minor supply disruptions. The currently changing structure of the world oil market, in particular the evolving sales agreements under which an increasing percentage of world oil is traded and the vertical integration of major OPEC members into areas such as refining, could decrease the ability of the market to adjust to future disruptions. Third, it is suggested that linear programming (LP) models oger unique capabilities in assessing the degree to which the world and domestic oil markets could adjust to short-term supply disruptions, given constraints on transport, trade, and refining possibilities imposed by the physical structures of those market sectors or by control of those sectors by increasingly powerful producing countries. The assessment of this flexibility will help pinpoint areas needing attention and also contribute indirectly to the evaluation of short-run demand elasticities for world oil. The US Department of Energy’s Petroleum Allocation (PAL) Model is used as an example of one LP model that can address such issues. Keywords: Oil security;
Oil vulnerability;
The purpose of this paper is to discuss the role of linear programming (LP) models in addressing the potential costs of, and appropriate responses to, oil The authors are with the Energy and Economic Analysis Section, Energy Division, Oak Ridge National Laboratory, PO Box X, Oak Ridge, Tennessee 37831, USA. Oak Ridge National Laboratory is operated by Martin Marietta Energy Systems Inc for the US Department ol Energy under contract No DE-ACOW340R21400. The submitted manuscript has been authored by a contractor of the US Government under contract No DE-ACOW340R21400. Accordingly, the US Government retains a non-exclusive, royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for US Government purposes. Final manuscript
received
0140-9883/88/020147-08
10 September
1987.
$03.00 0 1988 Butterworth
Oil modelling
supply disruptions. It is argued that while world oil prices have decreased sharply in recent months, the threat of oil supply disruptions and accompanying oil price jumps remain a major concern of all oil importing countries, especially beyond 1990. It is suggested that the current lull offers an opportune time to evaluate and respond to the inevitable resurgence of oil vulnerability. It is further suggested that linear programming models are a unique tool in the analysis of certain aspects of the vulnerability problem. In particular, LP models are important in assessing the degree to which the world and domestic oil markets could adjust to short-term supply disruptions, given constraints on transport and refining possibilities imposed by the physical structures of those market
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sectors, or by control of those sectors by increasingly powerful producing countries. The assessment of this flexibility will help pinpoint areas needing attention and also indirectly contribute to the evaluation of short-run demand elasticities for world oil. The Petroleum Allocation (PAL) Model is used as an example of an LP model that can address such issues.’ By examining this particular model’s strengths and weaknesses in addressing questions related to oil vulnerability, the general applicability of LP models is assessed.
The recent inability of the Organization of Petroleum Exporting Countries (OPEC) to control oil production effectively, and thus prevent the collapse of world oil prices, has led many to conclude that concern about oil supply disruptions and sudden and drastic oil price increases is a thing of the past. Crude spot prices have decreased from their 1980 high of over $38/bbl to as low as SlO/bbl. And long-term contract prices are decreasing from their 1981 high of more than $34/bbl in response to spot market trends. Further, the oil importing countries have seen their dependence on OPEC crude reduced drastically. World oil demand is down by about 8 % from its 1978 peak, while non-OPEC oil production has increased by 9 million bbl/day and OPEC production decreased by approximately 14 million bbl/day. In the USA, oil imports currently represent only about 5-6 million bbl/day of the total US consumption of 16 million bbl/day, and only about 50% of those imports are from OPEC countries. Oil from the Arab OPEC members represents less than 10% of total US oil imports. Finally, significant excess production capacity exists in the world market. The Central Intelligence Agency [4] estimates that the OPEC countries have a maximum sustainable production capacity of about 34.4 million bbl/day, while recent OPEC production was only 17-l 7.5 million bbl/day. Saudi Arabia alone has excess capacity of about 5 million bbl/day. There is, however, significant evidence to point to the contrary position that the threat of oil supply disruptions remains a serious problem, especially in the 1990s and beyond. First, the drastic reductions in world oil prices that have occurred recently will have the effect of increasing world oil consumption and reducing non-OPEC oil production. Production will decrease in the short term as wells are capped and
decrease further in the intermediate term as prices discourage exploration for new reserves. It has been argued that the production costs of as much as 3 million bbl/day of current world output are in excess of Sl2/bbl. In some cases stripper wells have been capped, and because the flow rates are typically low from such wells, many believe these stripper wells will never produce again. In fact, crude oil production in the USA has fallen from 9.0 million bbliday in 1985 to 8.4 million bbl/day in early 1987. Further, oil prices in the $15 to $20 range could increase world oil consumption by 4 to 5 million bbl/day by 1990 (see Rowen [29]). These trends will most likely result in the level of excess production capacity in the world market decreasing by 1990 to a point where any of a number of potential oil supply disruptions could result in large jumps in oil prices. In fact, the consensus among oil price forecasters is that real oil prices will begin to increase in about 1990 as the combined forces of production reductions in non-OPEC countries and consumption increases in all consuming countries give back to OPEC - and, in particular, the Persian Gulf producers - much of their market control lost during recent months.’ Second, it has been argued (see Curlee [l 11) that the current economic and political pressures being placed on the OPEC countries by the drastic reductions in oil prices, and thus reductions in oil revenues, increase the probability of internal turmoil within the member nations of OPEC. This problem is particularly pronounced in the more populous producing countries because of their relatively greater needs for revenues. Revolutions within major producing countries or military conflicts between OPEC producers could reduce the level of excess production quickly and drastically. Saudi Arabia, Kuwait, and the United Arab Emirates currently maintain about 6.9 million bbl/day of excess capacity. A disturbance in the Persian Gulf area affecting these countries could eliminate about 50% of OPEC’s current excess capacity and thereby cause panic on the entire world market. Third, the structure of the world oil market is continually evolving, often in ways that could make the impacts of oil supply disruption potentially more damaging. Curlee [12] has argued that the huge oil price jumps that followed the 1978 Iranian Revolution were due in part to structural changes in the world oil market. In particular, the major international oil companies lost a degree of their control over the distribution of crude and in so doing lost some ability
1The PAL Model was developed and is maintained by the Energy Information Administration within the US Department of Energy. The authors recently completed a draft documentation of that model. See Turhollow, Curlee and Das [35].
‘See, for example, Adelman [I], Curlee [IO], Erickson [ 151, Kouris 1241 or Saunders [30]. Curlee [12] reviews and summarizes numerous oil forecasts by both public and private institutions, as well as the modelling methodologies used to make those forecasts.
The continuing threat of supply disruptions
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to smooth out short-term and relatively minor supply disruptions. Two structural changes currently taking place that have received little attention, but could play significant roles in determining the impacts of future supply disruptions, are first the transition from an oil market dominated by long-term contracts to one dominated by spot market sales and second the additional control of the world oil market being gained by OPEC countries through vertical integration and evolving sales agreements. During the 1970s and early 1980s the overwhelming majority of oil was traded by long-term contracts. However, since the mid-1980s oil trade has been dominated by the spot market and contracts of much shorter duration than in the past. On the one hand, the additional flexibility offered by the spot market, in terms of allowing the redistribution of crude on the world market to occur more quickly, could serve to calm the market during a supply disruption. On the other hand, however, the changes in the way oil is traded would allow the price of a much larger percentage of oil traded on the world market to fluctuate in response to a supply disruption than during previous disruptions. The price impacts of a supply disruption would therefore be felt by the consuming countries more quickly.3 A possibly more disturbing development, however, is the growing control that the major OPEC producers have over the downstream processing and distribution of oil. In addition to having more control over oil distribution with measures such as ‘netback’ deals, major producing countries are increasingly involved in refining. OPEC members are not only building refineries in their own countries, but are also purchasing US refineries at a rapid rate. It is estimated that foreign oil producers will soon control about one million bbl/day of refinery capacity in the USA at a time when the capacity of domestically owned refineries is decreasing (see Frazier and Tanner [17]). The vertical integration of the oil exporting countries into downstream sectors could give those producers more control over domestic markets during supply disruptions. And, as has been argued elsewhere, the more control the producing countries have over refining and distribution, the less flexible the oil market becomes jThe impacts of spot prices on the overall price of world oil is controversial. Verleger [37] argues that spot prices determine all oil prices, because crude traded on the spot market represents the marginal source of supply. Bohi 127. however, argues that spot prices have historically had little impact on the overall price structure. For a more recent assessment of the relationship between spot and long-term contract prices, see Hubbard 1211. Hubbard argues that the relationship between the two is not trivial and depends on a complicated interaction of several parameters, including the fraction of trade carried out by long-term contracts and expectations of market members given past price changes.
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and therefore the greater the potential damage of supply disruptions to consuming countries. Finally, too much solace has been taken in the reduction of oil imports to consuming countries, especially in the USA. The costs of oil supply disruptions have not historically, and will not likely in the future, manifest themselves as crude shortages but rather as oil price increases. In the absence of price controls - which, of course, can only make the problems of supply disruptions worse - domestic oil prices are set by world prices. As was demonstrated during the two major disruptions of the past decade, the quantity of crude imported will have little impact on the severity of future disruptions.4 The dislocations occur because it is very difficult for both consumers and producers to adjust to severe price increases in the short term. The resurgence of oil vulnerability is inevitable. And the more we know about how that vulnerability will manifest itself and take actions to respond to the threat, the more secure our energy future will be.
Oil vulnerability and modelling methodologies In this section we discuss how different modelling methodologies can be used to address particular questions relevant to the evaluation of, and the appropriate policy responses to, supply disruptions. Particular emphasis is given to LP models. It is convenient if we think of the assessment of supply disruptions on three different levels, which are appropriately addressed with three different categories of models. The first we term a microeconomic level in which we are concerned with how firms and consumers within the oil industry respond to the price increases that accompany supply disruptions. This level is also concerned with how firms and consumers may respond to particular vulnerability-reducing measures, such as stockpiles, oil tariffs, or the like. Little attention is given to how the disaggregated components of the oil industry, such as the physical capabilities of the transport and refining sectors, may constrain the short-run response of suppliers and demanders. Neither is attention directed to how the disruptions or the vulnerability-reducing measures may result in macroeconomic gains or losses. Several models within this first category of models were reviewed in a 1982 report by the Energy Modeling Forum [ 143. That study divided these models into two main types - recursive simulation and intertemporal optimization. Recursive simulation models 4See Curlee [9] for details of the historical impacts of supply disruptions on the import of crude and products into the USA.
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are structured so that decisions by suppliers and demanders of oil are assumed to depend on information about past and current events, or on extrapolation of past events. A simplistic methodology is often applied to determine oil prices, such as the percent of capacity utilization in the OPEC countries. And future capacity of OPEC is usually an exogenous input of the models. Models of this type include, for example, those by Braden [3], Gately [18], Levy [25], and the US Department of Energy’s Oil Market Simulation (OMS) Model [36]. In the intertemporal optimization models it is assumed that at least some of the actors - ie certain subsets of suppliers and/or demanders of oil - have perfect foresight and act to maximize the discounted sum of current and future benefits of their actions. Some models assume that OPEC or a core of the organization restricts production and thus sets the price of world oil to maximize discounted profits. Models in this category include those by Cremer and Weitzman [6], Gately, Kyle and Fischer [19], Kalymon [22], Pindyck [28], and Singer [31]. Variations of this basic approach include those by Eckbo [13] and Hnyilicza and Pindyck [20] in which game theory is used to address questions of how different producers within the core allocate production levels. Other variations assume that the producing countries optimize oil revenues rather than profits or make production decisions based on profit maximization subject to constraints on the producing countries’ abilities to absorb revenues. Examples of such models include those by Cremer and Salehi-Isfahani [7], Ezzati [16], Mead [26], and Teece [32]. Short-run and long-run supply and demand elasticities are crucial parameters in such models, but are normally input exogenously - ie are taken from sources outside the model. This microeconomic-based category also includes optimal stockpiling and tariff models, such as those by Chao and Manne [S], Curlee [8], Nordhaus [27], Teisberg [33], and Tolley and Wilman [34]. These models estimate the expected costs imposed by hypothetical future disruptions and select the stockpiling and tariff strategies that maximize the total expected net benefits to be received from these policy instruments. Usually the benefits of the policy tools are measured and optimized in terms of the avoided losses of consumer and producer surplus before, during, and after the supply disruption. Short-run and long-run supply and demand elasticities and the speed at which market adjustments take place are key parameters of the models. However, in the above models these parameters are exogenous inputs. On a second level, we may be interested in estimating the macroeconomic costs of supply disruptions and
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the impacts of various policy instruments on macroeconomic variables. Questions about, for example, the inflationary and employment impacts of disruptions and the recycling of oil tax revenues are appropriately addressed at this level. Large-scale econometric models, such as the Wharton Model or the Data Resources Model, are usually employed for these types of assessments. Given their econometric foundations, these models predict future events based on estimated historic relationships among various market parameters. On a third level, we may be interested in very specific and detailed questions about how the oil market may respond to the loss of particular types of crude in particular locations, given anticipated distribution and refining constraints. For example, given a disruption in the Persian Gulf, how would the refining of crude and the distribution of crude and product change on the world market? Would significant shifts be required, or would only minor dislocations result? If a major transport passage, such as the Straits of Hormuz, is no longer available, how must the distribution and refining of oil be changed to satisfy regional oil demands? Or if a decision is made to draw down strategic stocks, such as the US Strategic Petroleum Reserve, how do the distribution and refining of oil change, and how sensitive are those changes to the types of crude drawn down? Obviously, if one type of crude is replaced with a very dissimilar crude, problems may arise. Can refineries use a different crude to make the same product stream, or will a drastic redistribution of crude and product be required to match particular refining capabilities to particular crude types? Will the agreements of the International Energy Agency to share oil during a supply disruption be triggered by a given disruption, and, if so, what is the likely redistribution of oil?5 It is suggested that the flexibility of the oil market to adapt to supply disruptions has been and will continue to be severely limited by the distribution and refining infrastructure. That flexibility will, in turn, suggest the short-run price elasticity of world oil demand. Obviously, the short-run price jump will be a function of the difficulty of redistributing crudes and products. And the degree to which the short-run elasticity differs from the long-run elasticity will be a major determinant of the severity of future supply disruptions.
‘The agreements of the International Energy Agency are rather complicated in the way they might bc triggered or applied. See Krapels [23] or Turhollow, Curlee and Das [35] [or a discussion of the specifics. in short, the agreements are triggered when one or more of the member countries experiences a loss of crude above a given percentage of their historic consumption.
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It is further suggested that the modelling approaches on the first or second levels do not have the conceptual or empirical capabilities to address these issues. Models based on historical relationships among market parameters are of little use because of a lack of data. And even if there were many disruptions from which data could be drawn, the continually changing oil market structure would negate their benefits in assessing current or future problems. Models based on well defined maximizing objectives, such as OPEC profit maximization, are also of limited value in assessing the short-term response to supply disruptions. The market mechanism will obviously try to satisfy world demand during a disruption by minimizing the cost of crude, transport and refining. However, that minimization may be severely constrained by the available physical capital in the market place and complicated and inflexible institutional arrangements - problems not easily identified with the first two modelling approaches. To address these very detailed, but important, questions, a linear-programming approach is warranted. Linear programming allows a large number of technical, institutional, and other constraints to be imposed on the system. Given these numerous constraints, the LP framework is amenable to addressing the questions posed on this third level. Care must be taken, however, to not overuse or misuse the LP approach. The next section addresses the appropriate and inappropriate use of LP models in studying oil supply disruptions - with an emphasis on the Energy Information Administration’s Petroleum Allocation (PAL) Model.6
Linear programming
models and supply
disruptions The main advantage of LP models in studying oil supply disruptions is their ability to model in a very detailed way the physical, economic and institutional activities associated with the petroleum market. These activities can be conveniently divided into the following sets: (i) crude oil production, (ii) transport and trade of crude oil from production site to refinery site; (iii) crude oil refining; 6Other
LP models with similar capabilities include the International Petroleum Model (IPM) developed by Williams Brothers Engineering Company, the Contingency Planning Model (CPM) developed at Stanford University, and the Queen Mary College World Energy Model. The Oil Trade Model (OTM) has also been developed at Stanford University, which uses a non-linear programming methodology and supersedes the CPM.
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(iv) distribution of refined products to end markets; and (v) consumption of refined products.’ By constraining the options available to an LP model - eg allowing Alaska North Slope crude to only be exported to the lower 48 states even though the least cost solution to the LP would send that oil to Japan - complicated institutional and real-world physical constraints can be addressed. Other examples of such constraints include the drawdown of the US Strategic Petroleum Reserves, the International Energy Agency sharing agreements, and possible restrictions on the use of selected refining and distribution capacity because of institutional barriers. Unlike other modelling approaches, LP models can address the implications of such detailed constraints during both normal and disruption conditions. And as is argued earlier, these types of constraints can be the key in determining the implications of a supply disruption. The structure and level of aggregation of the LP model depend upon the particular market sector or sectors that are of greatest concern, with the recognition that the model can quickly become very large. How many crudes should be included? How detailed should the crude and product transport network be? How many refinery districts and refined products should be included? At what level of detail should the refinery sector be modelled? How should known institutional factors affecting the trade of crudes and products be depicted? Obviously, there are an enormous number of world crudes; transport varies by mode, size and potential routes, thus presenting thousands of possibilities; refinery activities can be modelled with great precision and complexity; and products can be disaggregated from a basic set of four to six to as many as 25 or more. It is easy to see that when one considers the possible number of crudes, refined products, transport alternatives, and refinery configurations, the LP model can quickly become unwieldy in size, expensive to run, and difficult to maintain in an up-to-date state - ie major disadvantages in using an LP framework. A simple outline of a typical LP model - in this case the PAL Model - may aid in understanding how an LP model can be specified to help analyse the problems discussed in the previous section, while maintaining a size and level of complexity that is manageable. In the case of the PAL Model, the world oil market is divided into regions for refining and demand purposes. In other words, a ‘typical’ regional refinery is modelled _ which in the case of PAL is the aggregate regional ‘One may also want to model natural gas liquids because a close substitute for some crude-oil-based products.
they are
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refinery capacity divided by the number of regional refineries - rather than attempting to model each refinery or refinery type. Likewise, end-product demand is estimated at a fairly aggregated level for each region - using an econometric approach outside the PAL LP framework - and then disaggregated into individual products, again using econometric models to share down the end-product demand estimates from the more aggregated model. The supply of crude oil is provided by region and by specific crude type as an exogenous model input. In the case of the PAL Model, crude supply is estimated using a relatively simple econometric model - the same model used to estimate regional oil demands. The production of crude oil in individual regions is shared down to specific crude types according to the historic production of crudes from that region. A crude may either be refined in the region in which it is produced or exported to another region using transport activities. Crudes are transformed into products by refining activities, and the products may be used to satisfy end-product demands either within the region in which they are refined, or, using transport activities, exported to other regions. The objective function of the system is to minimize the cost of satisfying end-product demands for refined products, given the costs depicted in the model for crude oil, transport, and refining, and given the numerous constraints imposed on the model that supposedly reflect real-world physical and institutional barriers. This brief overview of one model shows how an LP framework can be appropriately formulated to represent some of the key real-world barriers faced during a supply disruption. Model complexity, size, and detail can be limited, while at the same time the model can provide a useful, if not necessarily the most accurate, representation of the barriers imposed by the infrastructure of the oil market. Unfortunately, this brief overview also points to some additional disadvantages in using an LP approach. First, as with other modelling types, the results of the model must be interpreted in accordance with the sophistication and detail of the various model components. Interpreting estimates of movements in crude and product distribution, given a supply disruption, as reliable forecasts of how the market will actually respond can be dangerous. The more appropriate approach is to interpret the outputs of the LP in a qualitative way. The outputs do suggest directional movements and therefore suggest the degree to which the distribution of crudes and products will be ‘encouraged’ to change to minimize the LP objective function. Second, LP models have a tendency to overoptimize. Implicit in an LP framework is that the refining and distribution systems act in concert to minimize costs.
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Thus small changes in relative costs can lead to large changes in the optimal solution. For example, a regional refinery may, according to the model, alter its refined product slate, given a slight change in the quality of crude availability. While this type of product shift may be consistent with cost minimization, it most likely does not reflect the institutional barriers that must be overcome for such a product shift to occur. Another example is that a small change in the cost of transport on one route can result in a drastic reallocation of all world oil trade. If the model is not constrained to recognize that deviations from historical trade patterns are in themselves costly, large and unrealistic changes in oil trade may minimize total costs and thus become an expected outcome of the LP framework. The PAL Model addresses this problem of overoptimization by imposing a penalty cost on any world oil trade that does not follow historical patterns. In other words, in order for the model to select a distribution of crudes and products that differs from historical trade patterns, the redistributed oil must incur a penalty cost that supposedly reflects the cost of breaking historical institutional arrangements. The modeller can vary these penalty costs according to his or her own perceptions of the rigidity of historical trade patterns.8 By observing that a redistribution of crudes and products occurs with one penalty cost, but does not occur with another, the model results suggest the degree to which the redistribution is attractive on a cost minimizing basis. While this is not a perfect way to depict institutional barriers, it does let us address those barriers and at the same time limit the size and complexity of the model to a manageable level.
Conclusions This paper makes three major arguments. First, oil vulnerability is not a thing of the past. We as oil importing countries are, at best, in a grace period during which we have the option to either evaluate and prepare for the next severe disturbance or ignore the problem in the false hope that the turmoil of the past two decades will never recur. Second, an argument can be made that major contributors to the severity of past disruptions were physical and institutional constraints on the market system that hindered the market’s rapid response to what were relatively minor supply disruptions. It is suggested that future disruptions may be made worse by current and anticipated changes in the structure of ’ Unfortunately, a major disadvantage ol’using these penalty costs is that they distort shadow prices, making them difficult, if not impossible, to interpret in any meaningful way.
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the world oil market, particularly in the ways oil is traded and the vertical integration of the OPEC countries into downstream activities, such as refining. Third, while microeconomic and macroeconomic approaches are appropriate for addressing many issues relevant to supply disruptions, they are not appropriate tools when studying detailed physical and institutional market constraints. LP models can, however, be appropriately used to address how the world oil market may respond to supply disruptions, given real-world physical and institutional barriers. Directional shifts suggested by LP models indicate the degree to which the market flows of crudes and products will be encouraged, if not required, to change given a supply disruption within a particular region or a transport constraint at a certain location. These directional shifts in turn suggest the turmoil the market would undergo and thus help assess the degree to which panic may exacerbate the market’s problems in shifting crudes and products. Panic buying for hoarding purposes will, of course, imply a more inelastic short-run demand curve for oil and thus drive shortrun prices higher than they otherwise would be. LP models are not, however, perfect tools to address these types of problems. The models by their nature are large and often require compromises in market detail for operational feasibility. Further, the models, because of their linearity and aggregation methods, are prone to overoptimization and large jumps in model solutions. Outputs must be interpreted carefully and only infrequently can be labelled as reliable forecasts. This does not, however, negate their potential benefits in assessing the real-world physical and institutional barriers that have historically, and may very well in the future, turn a relatively minor supply disruption into another oil crisis.
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T. Randall Curlee, Anthony F. Turhollow and Sujit Das
This paper has three main objectives. First, an argument is made that oil vulnerability is not a problem of the past, but remains a sig@ant concern for all oil-consuming countries, especially beyond 1990. Second, it is suggested that the severity of past disruptions can be attributed, in part, to physical and institutional constraints that prevented the oil market from reacting quickly to what were relatively minor supply disruptions. The currently changing structure of the world oil market, in particular the evolving sales agreements under which an increasing percentage of world oil is traded and the vertical integration of major OPEC members into areas such as refining, could decrease the ability of the market to adjust to future disruptions. Third, it is suggested that linear programming (LP) models oger unique capabilities in assessing the degree to which the world and domestic oil markets could adjust to short-term supply disruptions, given constraints on transport, trade, and refining possibilities imposed by the physical structures of those market sectors or by control of those sectors by increasingly powerful producing countries. The assessment of this flexibility will help pinpoint areas needing attention and also contribute indirectly to the evaluation of short-run demand elasticities for world oil. The US Department of Energy’s Petroleum Allocation (PAL) Model is used as an example of one LP model that can address such issues. Keywords: Oil security;
Oil vulnerability;
The purpose of this paper is to discuss the role of linear programming (LP) models in addressing the potential costs of, and appropriate responses to, oil The authors are with the Energy and Economic Analysis Section, Energy Division, Oak Ridge National Laboratory, PO Box X, Oak Ridge, Tennessee 37831, USA. Oak Ridge National Laboratory is operated by Martin Marietta Energy Systems Inc for the US Department ol Energy under contract No DE-ACOW340R21400. The submitted manuscript has been authored by a contractor of the US Government under contract No DE-ACOW340R21400. Accordingly, the US Government retains a non-exclusive, royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for US Government purposes. Final manuscript
received
0140-9883/88/020147-08
10 September
1987.
$03.00 0 1988 Butterworth
Oil modelling
supply disruptions. It is argued that while world oil prices have decreased sharply in recent months, the threat of oil supply disruptions and accompanying oil price jumps remain a major concern of all oil importing countries, especially beyond 1990. It is suggested that the current lull offers an opportune time to evaluate and respond to the inevitable resurgence of oil vulnerability. It is further suggested that linear programming models are a unique tool in the analysis of certain aspects of the vulnerability problem. In particular, LP models are important in assessing the degree to which the world and domestic oil markets could adjust to short-term supply disruptions, given constraints on transport and refining possibilities imposed by the physical structures of those market
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sectors, or by control of those sectors by increasingly powerful producing countries. The assessment of this flexibility will help pinpoint areas needing attention and also indirectly contribute to the evaluation of short-run demand elasticities for world oil. The Petroleum Allocation (PAL) Model is used as an example of an LP model that can address such issues.’ By examining this particular model’s strengths and weaknesses in addressing questions related to oil vulnerability, the general applicability of LP models is assessed.
The recent inability of the Organization of Petroleum Exporting Countries (OPEC) to control oil production effectively, and thus prevent the collapse of world oil prices, has led many to conclude that concern about oil supply disruptions and sudden and drastic oil price increases is a thing of the past. Crude spot prices have decreased from their 1980 high of over $38/bbl to as low as SlO/bbl. And long-term contract prices are decreasing from their 1981 high of more than $34/bbl in response to spot market trends. Further, the oil importing countries have seen their dependence on OPEC crude reduced drastically. World oil demand is down by about 8 % from its 1978 peak, while non-OPEC oil production has increased by 9 million bbl/day and OPEC production decreased by approximately 14 million bbl/day. In the USA, oil imports currently represent only about 5-6 million bbl/day of the total US consumption of 16 million bbl/day, and only about 50% of those imports are from OPEC countries. Oil from the Arab OPEC members represents less than 10% of total US oil imports. Finally, significant excess production capacity exists in the world market. The Central Intelligence Agency [4] estimates that the OPEC countries have a maximum sustainable production capacity of about 34.4 million bbl/day, while recent OPEC production was only 17-l 7.5 million bbl/day. Saudi Arabia alone has excess capacity of about 5 million bbl/day. There is, however, significant evidence to point to the contrary position that the threat of oil supply disruptions remains a serious problem, especially in the 1990s and beyond. First, the drastic reductions in world oil prices that have occurred recently will have the effect of increasing world oil consumption and reducing non-OPEC oil production. Production will decrease in the short term as wells are capped and
decrease further in the intermediate term as prices discourage exploration for new reserves. It has been argued that the production costs of as much as 3 million bbl/day of current world output are in excess of Sl2/bbl. In some cases stripper wells have been capped, and because the flow rates are typically low from such wells, many believe these stripper wells will never produce again. In fact, crude oil production in the USA has fallen from 9.0 million bbliday in 1985 to 8.4 million bbl/day in early 1987. Further, oil prices in the $15 to $20 range could increase world oil consumption by 4 to 5 million bbl/day by 1990 (see Rowen [29]). These trends will most likely result in the level of excess production capacity in the world market decreasing by 1990 to a point where any of a number of potential oil supply disruptions could result in large jumps in oil prices. In fact, the consensus among oil price forecasters is that real oil prices will begin to increase in about 1990 as the combined forces of production reductions in non-OPEC countries and consumption increases in all consuming countries give back to OPEC - and, in particular, the Persian Gulf producers - much of their market control lost during recent months.’ Second, it has been argued (see Curlee [l 11) that the current economic and political pressures being placed on the OPEC countries by the drastic reductions in oil prices, and thus reductions in oil revenues, increase the probability of internal turmoil within the member nations of OPEC. This problem is particularly pronounced in the more populous producing countries because of their relatively greater needs for revenues. Revolutions within major producing countries or military conflicts between OPEC producers could reduce the level of excess production quickly and drastically. Saudi Arabia, Kuwait, and the United Arab Emirates currently maintain about 6.9 million bbl/day of excess capacity. A disturbance in the Persian Gulf area affecting these countries could eliminate about 50% of OPEC’s current excess capacity and thereby cause panic on the entire world market. Third, the structure of the world oil market is continually evolving, often in ways that could make the impacts of oil supply disruption potentially more damaging. Curlee [12] has argued that the huge oil price jumps that followed the 1978 Iranian Revolution were due in part to structural changes in the world oil market. In particular, the major international oil companies lost a degree of their control over the distribution of crude and in so doing lost some ability
1The PAL Model was developed and is maintained by the Energy Information Administration within the US Department of Energy. The authors recently completed a draft documentation of that model. See Turhollow, Curlee and Das [35].
‘See, for example, Adelman [I], Curlee [IO], Erickson [ 151, Kouris 1241 or Saunders [30]. Curlee [12] reviews and summarizes numerous oil forecasts by both public and private institutions, as well as the modelling methodologies used to make those forecasts.
The continuing threat of supply disruptions
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to smooth out short-term and relatively minor supply disruptions. Two structural changes currently taking place that have received little attention, but could play significant roles in determining the impacts of future supply disruptions, are first the transition from an oil market dominated by long-term contracts to one dominated by spot market sales and second the additional control of the world oil market being gained by OPEC countries through vertical integration and evolving sales agreements. During the 1970s and early 1980s the overwhelming majority of oil was traded by long-term contracts. However, since the mid-1980s oil trade has been dominated by the spot market and contracts of much shorter duration than in the past. On the one hand, the additional flexibility offered by the spot market, in terms of allowing the redistribution of crude on the world market to occur more quickly, could serve to calm the market during a supply disruption. On the other hand, however, the changes in the way oil is traded would allow the price of a much larger percentage of oil traded on the world market to fluctuate in response to a supply disruption than during previous disruptions. The price impacts of a supply disruption would therefore be felt by the consuming countries more quickly.3 A possibly more disturbing development, however, is the growing control that the major OPEC producers have over the downstream processing and distribution of oil. In addition to having more control over oil distribution with measures such as ‘netback’ deals, major producing countries are increasingly involved in refining. OPEC members are not only building refineries in their own countries, but are also purchasing US refineries at a rapid rate. It is estimated that foreign oil producers will soon control about one million bbl/day of refinery capacity in the USA at a time when the capacity of domestically owned refineries is decreasing (see Frazier and Tanner [17]). The vertical integration of the oil exporting countries into downstream sectors could give those producers more control over domestic markets during supply disruptions. And, as has been argued elsewhere, the more control the producing countries have over refining and distribution, the less flexible the oil market becomes jThe impacts of spot prices on the overall price of world oil is controversial. Verleger [37] argues that spot prices determine all oil prices, because crude traded on the spot market represents the marginal source of supply. Bohi 127. however, argues that spot prices have historically had little impact on the overall price structure. For a more recent assessment of the relationship between spot and long-term contract prices, see Hubbard 1211. Hubbard argues that the relationship between the two is not trivial and depends on a complicated interaction of several parameters, including the fraction of trade carried out by long-term contracts and expectations of market members given past price changes.
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and therefore the greater the potential damage of supply disruptions to consuming countries. Finally, too much solace has been taken in the reduction of oil imports to consuming countries, especially in the USA. The costs of oil supply disruptions have not historically, and will not likely in the future, manifest themselves as crude shortages but rather as oil price increases. In the absence of price controls - which, of course, can only make the problems of supply disruptions worse - domestic oil prices are set by world prices. As was demonstrated during the two major disruptions of the past decade, the quantity of crude imported will have little impact on the severity of future disruptions.4 The dislocations occur because it is very difficult for both consumers and producers to adjust to severe price increases in the short term. The resurgence of oil vulnerability is inevitable. And the more we know about how that vulnerability will manifest itself and take actions to respond to the threat, the more secure our energy future will be.
Oil vulnerability and modelling methodologies In this section we discuss how different modelling methodologies can be used to address particular questions relevant to the evaluation of, and the appropriate policy responses to, supply disruptions. Particular emphasis is given to LP models. It is convenient if we think of the assessment of supply disruptions on three different levels, which are appropriately addressed with three different categories of models. The first we term a microeconomic level in which we are concerned with how firms and consumers within the oil industry respond to the price increases that accompany supply disruptions. This level is also concerned with how firms and consumers may respond to particular vulnerability-reducing measures, such as stockpiles, oil tariffs, or the like. Little attention is given to how the disaggregated components of the oil industry, such as the physical capabilities of the transport and refining sectors, may constrain the short-run response of suppliers and demanders. Neither is attention directed to how the disruptions or the vulnerability-reducing measures may result in macroeconomic gains or losses. Several models within this first category of models were reviewed in a 1982 report by the Energy Modeling Forum [ 143. That study divided these models into two main types - recursive simulation and intertemporal optimization. Recursive simulation models 4See Curlee [9] for details of the historical impacts of supply disruptions on the import of crude and products into the USA.
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are structured so that decisions by suppliers and demanders of oil are assumed to depend on information about past and current events, or on extrapolation of past events. A simplistic methodology is often applied to determine oil prices, such as the percent of capacity utilization in the OPEC countries. And future capacity of OPEC is usually an exogenous input of the models. Models of this type include, for example, those by Braden [3], Gately [18], Levy [25], and the US Department of Energy’s Oil Market Simulation (OMS) Model [36]. In the intertemporal optimization models it is assumed that at least some of the actors - ie certain subsets of suppliers and/or demanders of oil - have perfect foresight and act to maximize the discounted sum of current and future benefits of their actions. Some models assume that OPEC or a core of the organization restricts production and thus sets the price of world oil to maximize discounted profits. Models in this category include those by Cremer and Weitzman [6], Gately, Kyle and Fischer [19], Kalymon [22], Pindyck [28], and Singer [31]. Variations of this basic approach include those by Eckbo [13] and Hnyilicza and Pindyck [20] in which game theory is used to address questions of how different producers within the core allocate production levels. Other variations assume that the producing countries optimize oil revenues rather than profits or make production decisions based on profit maximization subject to constraints on the producing countries’ abilities to absorb revenues. Examples of such models include those by Cremer and Salehi-Isfahani [7], Ezzati [16], Mead [26], and Teece [32]. Short-run and long-run supply and demand elasticities are crucial parameters in such models, but are normally input exogenously - ie are taken from sources outside the model. This microeconomic-based category also includes optimal stockpiling and tariff models, such as those by Chao and Manne [S], Curlee [8], Nordhaus [27], Teisberg [33], and Tolley and Wilman [34]. These models estimate the expected costs imposed by hypothetical future disruptions and select the stockpiling and tariff strategies that maximize the total expected net benefits to be received from these policy instruments. Usually the benefits of the policy tools are measured and optimized in terms of the avoided losses of consumer and producer surplus before, during, and after the supply disruption. Short-run and long-run supply and demand elasticities and the speed at which market adjustments take place are key parameters of the models. However, in the above models these parameters are exogenous inputs. On a second level, we may be interested in estimating the macroeconomic costs of supply disruptions and
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the impacts of various policy instruments on macroeconomic variables. Questions about, for example, the inflationary and employment impacts of disruptions and the recycling of oil tax revenues are appropriately addressed at this level. Large-scale econometric models, such as the Wharton Model or the Data Resources Model, are usually employed for these types of assessments. Given their econometric foundations, these models predict future events based on estimated historic relationships among various market parameters. On a third level, we may be interested in very specific and detailed questions about how the oil market may respond to the loss of particular types of crude in particular locations, given anticipated distribution and refining constraints. For example, given a disruption in the Persian Gulf, how would the refining of crude and the distribution of crude and product change on the world market? Would significant shifts be required, or would only minor dislocations result? If a major transport passage, such as the Straits of Hormuz, is no longer available, how must the distribution and refining of oil be changed to satisfy regional oil demands? Or if a decision is made to draw down strategic stocks, such as the US Strategic Petroleum Reserve, how do the distribution and refining of oil change, and how sensitive are those changes to the types of crude drawn down? Obviously, if one type of crude is replaced with a very dissimilar crude, problems may arise. Can refineries use a different crude to make the same product stream, or will a drastic redistribution of crude and product be required to match particular refining capabilities to particular crude types? Will the agreements of the International Energy Agency to share oil during a supply disruption be triggered by a given disruption, and, if so, what is the likely redistribution of oil?5 It is suggested that the flexibility of the oil market to adapt to supply disruptions has been and will continue to be severely limited by the distribution and refining infrastructure. That flexibility will, in turn, suggest the short-run price elasticity of world oil demand. Obviously, the short-run price jump will be a function of the difficulty of redistributing crudes and products. And the degree to which the short-run elasticity differs from the long-run elasticity will be a major determinant of the severity of future supply disruptions.
‘The agreements of the International Energy Agency are rather complicated in the way they might bc triggered or applied. See Krapels [23] or Turhollow, Curlee and Das [35] [or a discussion of the specifics. in short, the agreements are triggered when one or more of the member countries experiences a loss of crude above a given percentage of their historic consumption.
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It is further suggested that the modelling approaches on the first or second levels do not have the conceptual or empirical capabilities to address these issues. Models based on historical relationships among market parameters are of little use because of a lack of data. And even if there were many disruptions from which data could be drawn, the continually changing oil market structure would negate their benefits in assessing current or future problems. Models based on well defined maximizing objectives, such as OPEC profit maximization, are also of limited value in assessing the short-term response to supply disruptions. The market mechanism will obviously try to satisfy world demand during a disruption by minimizing the cost of crude, transport and refining. However, that minimization may be severely constrained by the available physical capital in the market place and complicated and inflexible institutional arrangements - problems not easily identified with the first two modelling approaches. To address these very detailed, but important, questions, a linear-programming approach is warranted. Linear programming allows a large number of technical, institutional, and other constraints to be imposed on the system. Given these numerous constraints, the LP framework is amenable to addressing the questions posed on this third level. Care must be taken, however, to not overuse or misuse the LP approach. The next section addresses the appropriate and inappropriate use of LP models in studying oil supply disruptions - with an emphasis on the Energy Information Administration’s Petroleum Allocation (PAL) Model.6
Linear programming
models and supply
disruptions The main advantage of LP models in studying oil supply disruptions is their ability to model in a very detailed way the physical, economic and institutional activities associated with the petroleum market. These activities can be conveniently divided into the following sets: (i) crude oil production, (ii) transport and trade of crude oil from production site to refinery site; (iii) crude oil refining; 6Other
LP models with similar capabilities include the International Petroleum Model (IPM) developed by Williams Brothers Engineering Company, the Contingency Planning Model (CPM) developed at Stanford University, and the Queen Mary College World Energy Model. The Oil Trade Model (OTM) has also been developed at Stanford University, which uses a non-linear programming methodology and supersedes the CPM.
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(iv) distribution of refined products to end markets; and (v) consumption of refined products.’ By constraining the options available to an LP model - eg allowing Alaska North Slope crude to only be exported to the lower 48 states even though the least cost solution to the LP would send that oil to Japan - complicated institutional and real-world physical constraints can be addressed. Other examples of such constraints include the drawdown of the US Strategic Petroleum Reserves, the International Energy Agency sharing agreements, and possible restrictions on the use of selected refining and distribution capacity because of institutional barriers. Unlike other modelling approaches, LP models can address the implications of such detailed constraints during both normal and disruption conditions. And as is argued earlier, these types of constraints can be the key in determining the implications of a supply disruption. The structure and level of aggregation of the LP model depend upon the particular market sector or sectors that are of greatest concern, with the recognition that the model can quickly become very large. How many crudes should be included? How detailed should the crude and product transport network be? How many refinery districts and refined products should be included? At what level of detail should the refinery sector be modelled? How should known institutional factors affecting the trade of crudes and products be depicted? Obviously, there are an enormous number of world crudes; transport varies by mode, size and potential routes, thus presenting thousands of possibilities; refinery activities can be modelled with great precision and complexity; and products can be disaggregated from a basic set of four to six to as many as 25 or more. It is easy to see that when one considers the possible number of crudes, refined products, transport alternatives, and refinery configurations, the LP model can quickly become unwieldy in size, expensive to run, and difficult to maintain in an up-to-date state - ie major disadvantages in using an LP framework. A simple outline of a typical LP model - in this case the PAL Model - may aid in understanding how an LP model can be specified to help analyse the problems discussed in the previous section, while maintaining a size and level of complexity that is manageable. In the case of the PAL Model, the world oil market is divided into regions for refining and demand purposes. In other words, a ‘typical’ regional refinery is modelled _ which in the case of PAL is the aggregate regional ‘One may also want to model natural gas liquids because a close substitute for some crude-oil-based products.
they are
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refinery capacity divided by the number of regional refineries - rather than attempting to model each refinery or refinery type. Likewise, end-product demand is estimated at a fairly aggregated level for each region - using an econometric approach outside the PAL LP framework - and then disaggregated into individual products, again using econometric models to share down the end-product demand estimates from the more aggregated model. The supply of crude oil is provided by region and by specific crude type as an exogenous model input. In the case of the PAL Model, crude supply is estimated using a relatively simple econometric model - the same model used to estimate regional oil demands. The production of crude oil in individual regions is shared down to specific crude types according to the historic production of crudes from that region. A crude may either be refined in the region in which it is produced or exported to another region using transport activities. Crudes are transformed into products by refining activities, and the products may be used to satisfy end-product demands either within the region in which they are refined, or, using transport activities, exported to other regions. The objective function of the system is to minimize the cost of satisfying end-product demands for refined products, given the costs depicted in the model for crude oil, transport, and refining, and given the numerous constraints imposed on the model that supposedly reflect real-world physical and institutional barriers. This brief overview of one model shows how an LP framework can be appropriately formulated to represent some of the key real-world barriers faced during a supply disruption. Model complexity, size, and detail can be limited, while at the same time the model can provide a useful, if not necessarily the most accurate, representation of the barriers imposed by the infrastructure of the oil market. Unfortunately, this brief overview also points to some additional disadvantages in using an LP approach. First, as with other modelling types, the results of the model must be interpreted in accordance with the sophistication and detail of the various model components. Interpreting estimates of movements in crude and product distribution, given a supply disruption, as reliable forecasts of how the market will actually respond can be dangerous. The more appropriate approach is to interpret the outputs of the LP in a qualitative way. The outputs do suggest directional movements and therefore suggest the degree to which the distribution of crudes and products will be ‘encouraged’ to change to minimize the LP objective function. Second, LP models have a tendency to overoptimize. Implicit in an LP framework is that the refining and distribution systems act in concert to minimize costs.
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Thus small changes in relative costs can lead to large changes in the optimal solution. For example, a regional refinery may, according to the model, alter its refined product slate, given a slight change in the quality of crude availability. While this type of product shift may be consistent with cost minimization, it most likely does not reflect the institutional barriers that must be overcome for such a product shift to occur. Another example is that a small change in the cost of transport on one route can result in a drastic reallocation of all world oil trade. If the model is not constrained to recognize that deviations from historical trade patterns are in themselves costly, large and unrealistic changes in oil trade may minimize total costs and thus become an expected outcome of the LP framework. The PAL Model addresses this problem of overoptimization by imposing a penalty cost on any world oil trade that does not follow historical patterns. In other words, in order for the model to select a distribution of crudes and products that differs from historical trade patterns, the redistributed oil must incur a penalty cost that supposedly reflects the cost of breaking historical institutional arrangements. The modeller can vary these penalty costs according to his or her own perceptions of the rigidity of historical trade patterns.8 By observing that a redistribution of crudes and products occurs with one penalty cost, but does not occur with another, the model results suggest the degree to which the redistribution is attractive on a cost minimizing basis. While this is not a perfect way to depict institutional barriers, it does let us address those barriers and at the same time limit the size and complexity of the model to a manageable level.
Conclusions This paper makes three major arguments. First, oil vulnerability is not a thing of the past. We as oil importing countries are, at best, in a grace period during which we have the option to either evaluate and prepare for the next severe disturbance or ignore the problem in the false hope that the turmoil of the past two decades will never recur. Second, an argument can be made that major contributors to the severity of past disruptions were physical and institutional constraints on the market system that hindered the market’s rapid response to what were relatively minor supply disruptions. It is suggested that future disruptions may be made worse by current and anticipated changes in the structure of ’ Unfortunately, a major disadvantage ol’using these penalty costs is that they distort shadow prices, making them difficult, if not impossible, to interpret in any meaningful way.
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the world oil market, particularly in the ways oil is traded and the vertical integration of the OPEC countries into downstream activities, such as refining. Third, while microeconomic and macroeconomic approaches are appropriate for addressing many issues relevant to supply disruptions, they are not appropriate tools when studying detailed physical and institutional market constraints. LP models can, however, be appropriately used to address how the world oil market may respond to supply disruptions, given real-world physical and institutional barriers. Directional shifts suggested by LP models indicate the degree to which the market flows of crudes and products will be encouraged, if not required, to change given a supply disruption within a particular region or a transport constraint at a certain location. These directional shifts in turn suggest the turmoil the market would undergo and thus help assess the degree to which panic may exacerbate the market’s problems in shifting crudes and products. Panic buying for hoarding purposes will, of course, imply a more inelastic short-run demand curve for oil and thus drive shortrun prices higher than they otherwise would be. LP models are not, however, perfect tools to address these types of problems. The models by their nature are large and often require compromises in market detail for operational feasibility. Further, the models, because of their linearity and aggregation methods, are prone to overoptimization and large jumps in model solutions. Outputs must be interpreted carefully and only infrequently can be labelled as reliable forecasts. This does not, however, negate their potential benefits in assessing the real-world physical and institutional barriers that have historically, and may very well in the future, turn a relatively minor supply disruption into another oil crisis.
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