United States is one of the largest crude oil producers in the world, but the consumption rate is higher than production. Hence, United States imports oil from varies parts of the world depending on different criteria.
The efficiency curve model is modified to compare crude oil supply chain among Indonesia, Russia, and Colombia based on oil transportation distances and associated cost, refinery costs, and the costs associated with refinery sustainability and pipeline quality shown in Modeling the Supply Chain (Author: Shapiro). However, this model was originally used to determine the optimal locations of distribution centers (DCs) based on transportation cost and the capacity of the DCs, and was modified to allow the use of different costs associated with the quality condition of the pipeline and the costs of sustaining an environmentally friendly facility. This case used to optimize the total cost of oil supply chain for Indonesia, Russia, and Colombia. We seek to extend our previous supply chain model, which represent the outbound oil supply chain for Indonesia. The outputs of this chapter are efficiency curves that show how the costs of pipeline quality and facility sustainability affect the overall costs of the oil industry of Indonesia, Russia, and Colombia.
The United States import oil from different countries, which is essential to sustain American people’s necessity based on current situation. The United States imported about 7.7 MMbd of crude oil, and 2.1 MMbd of petroleum liquids and refined products in 2013. The United States also exported 3.6 MMbd of crude oil and petroleum products (very little was crude oil), which made the United States a net exporter of petroleum liquids and refined products. Net imports of crude oil and petroleum products (imports minus exports) averaged 6.2 MMbd and accounted for 33% of U.S. total petroleum consumption in 2013, the lowest level since 1986. U.S. dependence on imported petroleum has declined since peaking in 2005.
This trend is the result of a variety of factors including a decline in consumption and shifts in supply patterns. The economic downturn following the financial crisis of 2008, efficiency improvements, changes in consumer behavior, and patterns of economic growth all contributed to the decline in petroleum consumption. Additionally, the increased use of domestic biofuels (ethanol and biodiesel), and strong gains in domestic production of crude oil and natural gas plant liquids expanded domestic supplies and reduced the need for imports.
The current U.S. sources for oil are not limited to politically stable countries, but it majorly relies on Canada & OPEC member Saudi Arabia. There is a concern about the impact to the U.S. economy if Canada or Saudi Arabia decides to manipulate demand and possibly stops exporting oil to the United States. The dependence on foreign oil does not present strategic challenges to the United States and that it does not negatively affect the nation’s economy and national security. This dependency has had a large impact on the U.S. foreign policy and continues to influence international relationships. Today, the consideration is more in regards as to which foreign oil sources are the most challenging and what steps could be taken by the U.S. government to help alleviate these challenges.
Figure 3.1 U.S. petroleum and other liquid production, estimated consumption, and net imports from 1995 to 2013. (Preliminary Data U.S. EIA October 2014.)
Figure 3.2 U.S. net imports of crude oil and petroleum products from Saudi Arabia, Canada, Russia, and Colombia in 2013. (Preliminary Data: U.S. EIA, October 2014.)
The U.S. EIA stated that the United States consumed an estimated 18.96 million barrels per day (MMbd) of petroleum products and produced 12.31 MMbd of crude oil and petroleum products during 2013. Therefore, the U.S. net imports of crude oil and petroleum products equaled 6.57 MMbd, making the United States dependent on foreign oil—see Figure 3.1 [U.S. EIA].
Most of the imports came from the western hemisphere. The western hemisphere including North, South, and Central America, the Caribbean, and the U.S. territories; and the Persian Gulf countries such as Iraq, Kuwait, Qatar, Saudi Arabia, and United Arab Emirates exported 55.8% and 31.8%, respectively, of crude oil and petroleum products to the United States in 2013. Oil from Canada and Saudi Arabia accounted for 42% and 21%, respectively, of the U.S. crude oil and petroleum products imports, resulting in those countries representing the top two foreign oil sources for the United States in 2013—see Figure 3.2.
This is problematic due to the fact that 21% of the U.S. net crude oil and petroleum products imports come from one country, Saudi Arabia, which threatens U.S. homeland security by leaving the United States susceptible to Middle Eastern manipulation. While the United States does import a larger percentage of crude oil and petroleum products from Canada, Canada is considered an ally due to treaties signed during World War II and during the Cold War.
According to U.S. EIA, oil from Russia and Colombia is approximately 7% and 4% of the U.S. crude oil and petroleum product, respectively (see Figure 1.2).
The significance of this research is to seek impacts of the U.S. dependency on foreign oil problems by introducing a mixed-integer programming (MIP) model that identifies how other nations such as Indonesia, Russia, and Colombia can be more efficient in their crude oil supply chain and produce more crude oil products for export. This model was built with respect to the trade-off between crude oil supply chain quality, sustainable environmental incentives, and supply chain costs. Furthermore, the broader impact is how investments into other countries crude oil supply chains can be quantified and optimized and how countries such as Indonesia can be identified as possible candidates for investment for future global crude oil needs. This chapter hypothesizes that the crude oil supply chain quality will impact the crude oil supply chain costs. Additionally, the environmental sustainability will have an impact on crude oil supply chain costs and suggests that the crude oil supply chains of each of these countries will dictate their ability to produce crude oil for export. The overall objective is to investigate a MIP model that supports decisions about providing economic and environmental incentives to improve the supply chain quality of crude oil so that it becomes more cost-effective for the United States to import crude oil from other nations as opposed to other global sources.
The U.S. government, crude oil refining companies, and other stake holders find it necessary to invest infrastructure and to buy crude oil from other nation to accomplish the requirement of the United States. Therefore, this dissertation attempt to answer the following global question: “When is it economically benefit to invest in supply chain of crude oil for given nation?” This question hypothesizes that the pipeline quality and sustainability will impact the supply chain cost and suggest that the crude oil supply chain for given nation will dictate their ability to be an ideal candidate for investment.
The goal of the most of companies is to maximize profit and shareholder value. In the oil industry, to maximize of shareholder value, the value of oil resources should be maximized through managing production, exploration, and development activities to assure a functioning market (Pirog, 2007). Reserve replacement and ability to expand production and sales to meet demand are important activities to ensure the long-term feasibility of company. Technical efficiency is required to minimize cost and to improve performance and environmental integrity.
The management of the company organizing production to accomplish goal helps to make profit in current as well as future time. Management makes investment decision to raise company’s rate of return and to increase the profitability.
A majority of government operate their national oil companies, so these companies do not follow stakeholder value maximization model. They have to compete with governmentally mandated objectives to maximize the value of the company. These companies have pressure to maximize the flow of fund to national treasuries.
There are several examples of unsuccessful deals between national oil companies in which the outcome was not able to meet expectations like “China and Iran” and “China and Saudi Arabia”.
Furthermore, the broader impact is how investments into other countries crude oil supply chains can be quantified and optimized, and how countries such as Russia/Colombia can be identified as possible candidates for investment for future global crude oil needs. This chapter hypothesizes that the crude oil supply chain quality will impact the crude oil supply chain costs. Additionally, the environmental sustainability will have an impact on crude oil supply chain costs and suggests that the crude oil supply chains of each of these countries will dictate their ability to produce crude oil for export. The overall objective is to investigate a MIP model that supports decisions about providing economic and environmental incentives to improve the supply chain quality of crude oil, specifically in Russia/Colombia so that it becomes more cost-effective for the United States to import crude oil from Russia/Colombia as opposed to other global sources.
Crude oil, commonly known as petroleum, was formed from the remains of animals and plants (called biomass) that lived many years ago. Over many years, the biomass was covered by layers of mud, silt, and sand that formed into sedimentary rock. Geologic heat and the pressure of the overlying rock turned the biomass into a hydrocarbon-rich liquid that we call crude oil, and eventually forced it into porous rock strata called reservoirs. Oil reserves cannot be reproduced because it needs millions of years to form. That’s why crude oil is called non-renewable energy source. There are also formations or deposits of hydrocarbon-saturated sands and shale where geologic conditions have not been sufficient to turn the hydrocarbons into liquid.
Crude oil is a liquid found within the Earth comprised of hydrocarbons, organic compounds, and small amounts of metal. While hydrocarbons are usually the primary component of crude oil, their composition can vary from 50% to 97% depending on the type of crude oil and how it is extracted. Organic compounds such as nitrogen, oxygen, and sulfur typically make up between 6% and 10% of crude oil, while metals such as copper, nickel, vanadium, and iron account for less than 1% of the total composition.
Petroleum has been used since ancient time. Geologists observe rock structure and its characteristics to determine the oil reservoir. According to E-tech international, oil exploration and production processes consist of five main processes (Figure 3.3).
Oil and gas exploration is the discovery for hydrocarbon deposits (oil and gas) underneath the Earth’s surface by petroleum geologists and geophysicists. It contains locating oil and gas reservoirs using primarily seismic surveys and drilling wells.
Exploration is an expensive, high-risk operation because it costs millions of dollars and every one out of three wells, on average, contains hydrocarbons. Therefore, companies have to drill multiple wells in one area before finding an oil or gas, which can take several years.
During exploration drilling, information about the rocks and fluids (water, gas, and oil) and samples are collected from the well which leads to following information:
Figure 3.3 Crude oil exploration process.
Exploration activities can also be risky because of
If a company is successful with their exploration drilling and makes an oil or gas discovery, then they move into the appraisal phase of the lifecycle. The purpose of this phase is to reduce the uncertainty about the size of the oil or gas field and its properties.
During appraisal, more wells are drilled to collect information and samples from the reservoir. Another seismic survey might also be acquired in order to better image the reservoir. These activities can take several more years and cost tens to hundreds of millions of dollars.
More seismic surveys and wells help petroleum geologists; geophysicists and reservoir engineers understand the reservoir better. For example, they try to find out whether rock or fluid properties change away from the discovery well, how much oil or gas might be in the reservoir, and how fast oil or gas will move through the reservoir.
The appraisal stage is successful if a company decides that the oil or gas field can be developed. One risk that companies face is even after investing time and money in the appraisal stage, they might not find a way to develop the field safely, profitably, and responsibly (in terms of communities and the environment).
The development stage takes place after successful appraisal and before full-scale production. The main activities (and people involved) are
Executing the development plan involves drilling engineers who drill the first phase of production wells and project engineers who build the planned facilities. Many thousands of people can be involved in building production facilities, and safety is a top priority. The risk of accidents is highest in this phase because of the number of people involved at construction sites.
It costs hundreds of millions, sometimes billions of dollars and typically 5–10 years to develop an oil or gas field, depending on the location, size and complexity of the facilities, and the number of wells needed. Onshore developments are typically much cheaper than offshore developments.
No oil or gas field will be developed unless the company believes that they will make enough money to pay back their exploration, appraisal and development costs, as well as profit from selling the hydrocarbons. Even more importantly, developments will only happen if the communities or ecosystems affected can be protected.
Production is the phase during which hydrocarbons are extracted from an oil or gas field and the first money (or revenue) comes from selling the oil or gas. After a number of years, the revenue exceeds the company’s investment, and they begin to make a profit.
Production can last several years up to 40 years, depending on the size of the oil or gas field and how expensive it is to keep the wells and production facilities running. Every year, millions of dollars will be spent on operating and maintaining the field. Safe production operations are critical; otherwise, companies risk harming people or the damaging the environment, e.g., through an oil spill or explosion.
Operators work in shifts to keep production going. Engineers will usually be located full time at the production facilities in order to operate and maintain them. Reservoir engineers will check on the health and performance of the field to plan how best to maintain production. Additional wells might need to be drilled or the production facilities improved to maximize recovery of the oil or gas.
Decommissioning is the term used for removing the production facilities and restoring oil and gas sites that are no longer profitable. The term is usually used to refer to offshore facilities. Offshore oil and gas platforms can be vast structures requiring large amounts of materials in their construction. By bringing the facilities onshore for dismantling and disposal, these materials can be reclaimed.
Decommissioning involves removing not only the main platform but also pipelines and cables. The aim is to reduce the risk to the marine environment and to reuse or recycle materials. In the majority of cases, all equipment is removed, and the site returned to its condition before development began. Some installations can be reused as oil and gas facilities at another location or reused in place for another purpose (e.g., as a wind farm or aid to navigation). Occasionally, part of the platform may be left in place because they benefit the marine environment, e.g., steel legs of tension leg platforms that are used to create artificial reefs in the Gulf of Mexico.
Project, logistics, and environmental engineers will be involved in decommissioning a production facility. This vital step takes several years and many millions of dollars. Government requirements and community views will be taken on board during decommissioning.
Extracting oil and natural gas from oil field isn’t as simple as just drilling and completing a well. Crude oil extraction process consists of three recovery process (see Figure 3.4).
Figure 3.4 Crude oil extraction process.
When an oil field is first produced, the oil typically is recovered as a result of expansion of reservoir fluids which are naturally pressured within the producing formation. The only natural force present to move the oil through the reservoir rock to the well bore is the pressure differential between the higher pressure in the rock formation and the lower pressure in the producing well bore. Various types of pumps are often used to reduce pressure in the well bore, thereby increasing the pressure differential. At the same time, there are many factors that act to impede the flow of oil, depending on the nature of the formation and fluid properties, such as pressure, permeability, viscosity, and water saturation. This stage of production, referred to as “primary recovery”, recovers only a small fraction of the oil originally in place in a producing formation, typically ranging from 10% to 25%.
Primary recovery first relies on underground pressure to drive fluids to the surface. When the pressure falls, artificial lift technologies, such as pumps, are used help bring more fluids to the surface. In some situations, natural gas is pumped back down the well underneath the oil. The gas expands, pushing the oil to the surface. Gas lift technology is often used in offshore facilities. Primary recovery often taps up to 15% of the oil in a deposit.
After the primary recovery phase, many, but not all, oil fields respond positively to “secondary recovery” techniques in which external fluids are injected into a reservoir to increase reservoir pressure and to displace oil toward the well bore. Secondary recovery techniques often result in increases in production and reserves the abovementioned primary recovery. Waterflooding, a form of secondary recovery, works by repressuring a reservoir through water injection and “sweeping” or pushing oil to producing well bores. Through waterflooding, water injection replaces the loss of reservoir pressure caused by the primary production of oil and gas, which is often referred to as “pressure depletion” or “reservoir voidage”. The degree to which reservoir voidage has been replaced through water injection is known as “reservoir fill up” or simply as “fill up”. A reservoir which has had all of the produced fluids replaced by injection is at 100% fill up. In general, peak oil production from a waterflood typically occurs at 100% fill up. Estimating the percentage of fill up which has occurred, or when a reservoir is 100% filled up, is subject to a wide variety of engineering and geologic uncertainties. As a result of the water used in a waterflood, produced fluids contain both water and oil, with the relative amount of water increasing over time. Surface equipment is used to separate the oil from the water, with the oil going to pipelines or holding tanks for sale and the water being recycled to the injection facilities. In general, in the Mid-Continent Region, a secondary recovery process may produce an additional 10%–20% of the oil originally in place in a reservoir.
A third stage of oil recovery is called “tertiary recovery”. In addition to maintaining reservoir pressure, this type of recovery seeks to alter the properties of the oil in ways that facilitate additional production. The three major types of tertiary recovery are chemical flooding, thermal recovery (such as a steam flood), and miscible displacement involving carbon dioxide (CO2), hydrocarbon, or nitrogen injection.
Thermal recovery entails injecting steam into the formation. The heat from the steam makes the oil flow more easily, and the increased pressure forces it to the surface.
Gas injection uses either miscible or immiscible gases. Miscible gasses dissolve CO2, propane, methane, or other gasses in the oil to lower its viscosity and increase flow. Immiscible gasses do not mix with the oil, but increase pressure in the “gas cap” in a reservoir to drive additional oil to the well bore.
Chemical flooding involves mixing dense, water-soluble polymers with water and injecting the mixture into the field. The water pushes the oil out of the formation and into the well bore.
We are currently field testing new technologies in chemical flooding on some of our properties. If successful, this testing may lead to reserve and production increases in the future. Any future tertiary development programs and subsequent capital expenditures would be contingent upon commercial viability established by successful pilot testing. At this time, there are no estimated reserves or production associated with tertiary recovery projects assigned to our properties. We will continue to review future opportunities for growth through the use of various tertiary recovery techniques.
A crude oil refinery is a group of industrial facilities that turns crude oil and other inputs into finished petroleum products. A refinery’s capacity refers to the maximum amount of crude oil designed to flow into the distillation unit of a refinery, also known as the crude unit.
Crude oil is unprocessed oil, which comes out of a ground. Refineries process crude oil into many different petroleum products. These products include gasoline, diesel fuel, jet fuel, and asphalt. The most basic refining process separates crude oil into its various components. The various components of crude oil have different sizes, weights, and boiling temperatures. The process is very complex and involves both chemical reactions and physical separations. Crude oil is composed of thousands of different molecules. It would be nearly impossible to isolate every molecule and make finished products from each molecule. Chemists and engineers deal with this problem by isolating mixtures of molecules according to the mixture’s boiling point range. Crude oil is heated and put into a distillation tower (a still) where different hydrocarbon components are boiled off and recovered as they condense at different temperatures (see Figure 3.5).
The major products of crude oil according to its specific temperature are as follows (Table 3.1).
Oil transportation is a major industry in and of itself, with a range of transportation options available, depending on the situation at hand. The most important methods include pipeline, rail, barge, and truck. Transportation and storage in the oil and gas industry concern to the movement of crude oil from the oil fields (where oil has been discovered) to petroleum refineries (where the oil is further processed) to storage areas, where the petroleum products are stored for distribution and emergency reserves.
Figure 3.5 Crude oil distillation process.
Product Name |
Boiling Range (°C) |
State |
Uses |
---|---|---|---|
Petroleum gas |
40 |
Gas |
Used for heating, cooking |
Naphtha |
60–100 |
Gas |
Intermediate that will be processed more to make gasoline |
Gasoline |
40–205 |
Liquid |
Motor fuel |
Kerosene |
175–325 |
Liquid |
Fuel for jet engine and tractors |
Diesel oil |
250–350 |
Liquid |
Used for diesel fuel and heating oil |
Lubricating oil |
300–370 |
Liquid |
Used for motor oil, grease, and other lubricant |
Fuel oil |
370–600 |
Liquid |
Used for industrial fuel |
Residuals |
Above 600 |
Solid |
Coke, asphalt, tar, waxes, etc. |
Advances in exploration and production have helped to locate and recover a supply of oil and natural gas from major reserves across the globe. At the same time, demand for petroleum-based products has grown in every corner of the world. But supply and demand are rarely concentrated in the same place. Transportation therefore is vital to ensuring the reliable and affordable flow of petroleum we all count on to fuel our cars, heat our homes, and improve the quality of our lives.
There are four modes of transportation associated with crude oil.
Oil tankers ships are used for oil transport overseas or from sea to shore. Tankers can carry huge amounts of oil, and they have the flexibility of being able to transport to a variety of locations, whereas pipelines have fixed networks and limited ranges. As the name implies, tankers store large quantities of oil in enormous tanks on the ship.
Unlike oil tankers ship, barges are used to transport oil in barrels. This allows for easy loading and unloading of measured units of oil.
Advantage of ship and barge:
Disadvantage of ship and barge:
Oil pipelines are the most efficient means of transporting oil. They can handle enormous amounts of oil day in and day out with very little human interaction, and they can cover enormous distances.
Advantages of pipelines:
Disadvantages of pipeline
Trains are useful for transporting large amounts of oil over land and can generally reach a wider network of locations than oil pipelines can.
Advantages of rail:
Disadvantage of rail:
Trucks are the most limited oil transportation method in terms of storage capacity, but they have the greatest flexibility in potential destinations. This means trucks are often the last step in the transport process, delivering oil, and refined petroleum products to their intended storage destinations.
Advantage of truck:
Disadvantage of truck:
The United States Environmental Protection Agency (EPA) classifies crude oil waste into following two categories: (1) exempt and (2) non-exempt wastes.
The EPA defines exempt wastes as follows:
“Wastes that are generated before the end point of primary field operations are exempt. The term end point of initial product separation means the point at which crude oil leaves the last vessel in the tank battery associated with the wells. This tank battery separates crude oil from the produced water and/or gas”.
With respect to crude oil, primary field operations include activities occurring at or near the wellhead and before the point where the oil is transferred from an individual field facility or a centrally located facility to a carrier for transport to a refinery or a refiner.
Primary field operations include exploration, development, and the primary, secondary, and tertiary production of oil or gas. Crude oil processing, such as water separation, de-emulsifying, degassing, and storage at tank batteries associated with a specific well or wells, are examples of primary field operations. Furthermore, because natural gas often requires processing to remove water and other impurities prior to entering the sales line, gas plants are considered to be part of production operations regardless of their location with respect to the wellhead.
List of exempt and non-exempt for crude oil E&P
Exempt waste
Non-exempt waste
Pipelines are not part of primary field operations; thus, oil wastes that are generated by pipelines are non-exempt. Failure of a pipeline segment caused by accidental excavation damage is an example of non-exempt wastes, which will result in oil companies paying fines to the EPA as well as settlements to clean the surrounding environment. This pipeline segment failure is chosen as the sampling plan of supply chain quality-level performance.
Table 3.2 shows summary of various causes for pipeline failure.
Pipeline quality affects the transportation cost for crude oil. Cause-and-effect diagram for pipeline loss is shown in Figure 3.6.
Globalization has resulted in pressure on multinational firms to improve environmental performance. In order to achieve improvement in environmental performance, a company must integrate its environmental management strategies, while maintaining production quality and cost goals, into the supply chain, which includes all of the operational lifecycle stages such as unique partnerships with suppliers. Environmental sustainability has been defined as “meeting the needs of the present without compromising the ability of the future generations to meet their needs” [UN Document].
Type of Failure |
Causes |
---|---|
Mechanical failure |
Construction, material, and structural |
Corrosion |
Internal, external |
Operational failure |
System, human |
Third-party activity |
Accidental, malicious, incidental |
Natural hazard |
Subsidence, flooding, earthquake, etc. |
Figure 3.6 Cause-and-effect diagram for pipeline loss.
For oil companies, the concept of sustainability is most appropriately used when evaluating their business strategies. Sustainability concerns are to the degree of which they will not only reduce negative impacts on the natural environment through their operations but also invest in business practices that promote policies to make wide-reaching progress toward sustainable development. In the industry, the operations of oil companies are examined for their impact on the surrounding environment annually. To distinguish from the above definition of sustainability, environmentally conscious operations are referred to as green operations. However, green operations are not necessarily sustainable in the long run, but minimizing the negative impact of operational processes is still environmentally conscious. Company operations deal with energy usage necessary for operating refineries, emissions, and waste. Meanwhile, sustainability of the products deals with oil, natural gas, and possible alternatives to fossil fuels.
In the oil industry exploration and production processes, sustainability involves the products, and as such, the petroleum industry itself is environmentally unsustainable because like all fossil fuels, oil is a limited resource. Some risks of accidental spills of oil have the potential to pollute water, contaminate soil, harm species, and affect livelihoods.
Oil companies need to plan all major operations in advance and manage their costs during the supply chain to improve the profit margin. Sustainability that associated with oil companies’ processes or products will have positive and negative impacts on the supply chain costs. An example of the negative impact is certainly the tragic British Petroleum (BP) drill explosion and oil spill in 2010, which impacted nature and animals in the Gulf of Mexico. This accident resulted in damaging the environment as well as costing BP a settlement of billions of dollars. On contrary, an example of the positive impact is the ability to be capable of reserving the productivity of oil itself as a natural resource asset, which leads to supply chain costs savings.
Unlike the quality metrics, which focused on pipelines performance, this research considers refining process as a good candidate to determine its sustainability metrics. Refinery is a complex process. Oil refineries essentially serve as the second stage in the production process following the actual extraction by oil rigs. The first step in the refining process is distillation where crude oil is heated at extreme temperatures to separate the different hydrocarbons. The refining sector of the oil industry has significantly affected the crude oil global marketplace due to the demand growth of petroleum products. As the petroleum products demand increases, the demand for conversion capacity increases. Refineries affect supply chain profit margins such that refineries’ variable costs vary on the petroleum products demand.
There are two sustainability factors that are considered for refineries performance. The first factor is the refining operations, which deal with energy usage necessary for operating refineries, emissions, and waste. The second factor is the refining products, which deal with oil to fossil fuels. Refining processes that deal with energy usage are chosen as environmental sustainability according to the performance-sampling plan.
The petroleum industry in Russia is one of the largest industries in the world. Russia was the third-largest producer of liquid fuels in 2012, following the United States and Saudi Arabia. Russia’s proven oil reserves were 80 billion barrels as of January 2013, according to the Oil and Gas Journal. In 2012, Russia produced an estimated 10.4 MMbd of total liquids (of which 9.9 MMbd was crude oil), and it consumed roughly 3.2 MMbd. Russia exported over 7 MMbd in 2012, including roughly 5 MMbd of crude oil and the remainder in products.
Most of Russia’s oil production continues to originate in West Siberia, notably from the Priobskoye and Samotlor fields. Approximately 62% of oil produced from West Siberia region, while nearly 22% oil produced from the Urals-Volga region. The use of more advanced technologies and the application of improved recovery techniques are resulting in increased oil output from existing oil deposits. Fields in the Western Siberian Basin produce the majority of Russia’s oil, with developments at the Samotlor (TNK-BP) and Priobskoye (Rosneft) fields extracting more than 750,000 and 800,000 bd, respectively. Russian firms govern the region, although foreign companies, notably Shell, have secured access to production in Western Siberia as well.
West Siberia is Russia’s main oil-producing region, accounting for around 6.4 MMbd of liquids production, nearly two-thirds of Russia’s total production. While this region is mature, West Siberian production potential is still significant but will depend on improving production economics at fields that are more complex and that contain a significant portion of remaining reserves. The two largest oil fields in West Siberia are North Priobskoye and Samotlor, which account for about 20% of West Siberian production. Urengoy is the largest gas field in the region.
Urals-Volga was the largest producing region of the Soviet Union until the late 1970s, when it was surpassed by Western Siberia. Today, this region is a distant-second producing region, accounting for about 22% of Russia’s total output. The giant Romashkinskoye field (discovered in 1948) is the largest in the region. Tatneft operates it. While the field reached its peak production level sometime in the late 1970s, it likely will continue to produce until at least 2030, according to Wood Mackenzie.
The potential oil reserves of Eastern Siberia, the Russian Arctic, the northern Caspian Sea, and Sakhalin Island are attracting attention.
Russian companies are also expanding into the Arctic and Eastern Siberian regions, prompted on by tax holidays and lower oil export tariffs. While several new fields have come online since 2009, bringing additional fields into production will take time and may require an improved oil tax system from the government.
Russia has 40 oil refineries with a total crude oil distillation capacity of 5.5 MMbd, according to Oil and Gas Journal. Rosneft, the largest refinery operator, has a crude distillation capacity of 1.3 MMbd and operates Russia’s largest refinery, the Angarsk facility. LUKoil is the second-largest operator of refineries in Russia with a crude distillation capacity of 1 MMbd.
In 2012, Russia exported approximately 7.4 MMbd of total liquid fuels, with 5 MMbd of crude oil and 2.4 MMbd of petroleum products. The majority (79%) of Russia’s crude oil exports went to European countries (including Eastern Europe), particularly Germany, the Netherlands, and Poland. Around 18% of Russia’s crude oil exports were destined for Asia, while the remainder went mostly to the Americas. Russia’s crude oil exports to North America and South America have been largely displaced by increases in crude oil production in the United States, Canada, and, to a lesser extent, Brazil, Colombia, and other countries on the continent. More than 80% of Russia’s oil is exported via the Transneft pipeline system, and the remainder is shipped via rail and on vessels that load at independently owned terminals.
Russia has an extensive domestic distribution and export pipeline network. Russia’s pipeline network is nearly completely owned and run by the state-run Transneft, which transports about 88% of all crude oil and about 27% of oil products produced in Russia. These pipelines include a number of domestic pipeline networks, pipelines that transport oil to export terminals such as Novorossiysk on the Black Sea and Primorsk on the Baltic Sea, as well as a number of export pipelines that deliver oil to western European markets. Russian export pipelines include Druzhba, Baltic Pipeline System, North-West Pipeline System, Tengiz-Novorossiysk, and Baku-Novorossiysk. All of these pipelines, with the exception of the Tengiz-Novorossiysk, are Transneft-controlled.
Colombia produced 969,000 barrels per day (bd) of oil in 2012, up 61% from the 604,000 bd produced in 2008. EIA estimates that oil production in 2013 to be just over 1 MMbd and expects this rising trend to continue. The Ministry of Mines and Energy reported that Colombian production is expected to reach 1.3 MMbd by 2020. Colombia consumed 287,000 bd in 2012, allowing the country to export most of its oil production.
Colombia’s oil production has increased since 2008 because of increased exploration and development. New exploration and development were spurred by regulatory reform.
Much of Colombia’s crude oil production occurs in the Andes foothills and the eastern Amazonian jungles. Meta department, in central Colombia, is also an important production area, predominately of heavy crude oil. Its Llanos basin contains the Rubiales oilfield, the largest producing oil field in the country.
The largest producing oil field in the country is the Rubiales heavy oil field, located in Meta department, and operated by partners Pacific Rubiales and Ecopetrol. Low levels of production began at Rubiales in the late 1980s, but increasing investment and the completion of a new pipeline have allowed production rates to rise in recent years. Gross production at Rubiales exceeded 177,000 bd in 2012, up from 37,000 bd in 2008. Other large oil fields include Cano Limon, Castilla, and Cupiagua.
Colombia has six major oil pipelines, four of which connect production fields to the Caribbean export terminal at Covenas. These include the 500-mile Ocensa pipeline, which has the capacity to transport 650,000 bd from the Cusiana/Cupiagua area; the 460-mile, 220,000 bd-capacity Cano Limon pipeline; and the smaller Alto Magdalena and Colombia Oil pipelines. The Llanos Orientales pipeline came online in late 2009, linking the Rubiales field to the Ocensa pipeline, with a capacity of 340,000 bd. The sixth pipeline, the TransAndino, has a capacity of 190,000 bd and transports crude from Colombia’s Orito field in the Putumayo basin to Colombia’s Pacific port at Tumaco linking to Ecuador.
This research generates MIP baseline models and a proficient frontier curve, which include sampling plans for both pipeline quality and refinery sustainability performance, to evaluate the quality and sustainability for Russia and Colombia. This research utilizes Microsoft Excel Solver to solve for optimal solutions.
There are two primary research questions that we have to achieve in this section:
This chapter evaluates whether or not the crude oil sustainability and pipeline quality impact the crude oil supply chain cost. To evaluate the impact, we introduce two sets of hypothesis, which help to answer the research question. In statistical hypothesis testing, two hypotheses are compared. These are called the null hypothesis and the alternative hypothesis. The null hypothesis is the hypothesis that states that there is no relation between the phenomena whose relation is under investigation, or at least not of the form given by the alternative hypothesis. The alternative hypothesis, as the name suggests, is the alternative to the null hypothesis: it states that there is some kind of relation. The alternative hypothesis may take several forms, depending on the nature of the hypothesized relation; in particular, it can be two-sided (e.g., there is some effect, in a yet unknown direction) or one-sided (the direction of the hypothesized relation, positive or negative, is fixed in advance).
These two hypotheses statement are stated as follows:
In this research, the DC model shown in Shapiro’s book is utilized to show optimal locations to place DCs based on transportation distances and the size of the DCs. The model was worked in Microsoft Excel and used GRG nonlinear engine in Solver to solve the objective function. To achieve research objective, we introduce three specific objectives:
To satisfy these three specific objectives, we approach several steps.
In this phase, we introduce steps to achieve Specific Objective 1. “Evaluate the supply chain factors that determine pipeline quality of crude oil production”.
In this phase, we introduce steps to achieve Specific Objective 2. “Evaluate the supply chain factors that determine Sustainability of crude oil production”.
In this phase, we introduce steps to achieve Specific Objective 3. Evaluate the economic impacts of quality and sustainability on operational strategies in supplier network.
Figure 3.7 Pipeline survey form.
Quality Level |
Pipeline Quality Description |
---|---|
1 |
Damaged and causing non-exempt waste |
2 (base) |
Good condition and causing little non-exempt waste |
3 |
New and not causing non-exempt waste |
Sustainability Level |
Refinery Sustainability Description |
---|---|
1 |
High energy usage consumption |
2 (base) |
Medium energy usage consumption |
3 |
Low energy usage consumption |
Objective Function
where
i |
Russia |
Colombia |
---|---|---|
1 |
Samotlor—large |
Rubiales—large |
2 |
Samotlor—small |
Rubiales—small |
3 |
Priobskoye—large |
Cano Limon—large |
4 |
Priobskoye—small |
Cano Limon—small |
j |
Russia |
Colombia |
---|---|---|
1 |
Angarsk |
Barrancabermeja |
2 |
Achinsk |
Cartagena |
3 |
Tuapse |
Apiay |
4 |
Syzran |
Orito |
5 |
Kuibyshev |
Tibu |
6 |
Novokuibyshevsk |
- |
Country |
Oil Field Location |
Sampling Plan |
Performance Level |
Scenario |
---|---|---|---|---|
Russia |
Samotlor |
Pipeline quality |
1 |
1 |
|
|
|
2 (base) |
2 |
|
|
|
3 |
3 |
|
|
Refinery sustainability |
1 |
4 |
|
|
|
2 (base) |
5 |
|
|
|
3 |
6 |
|
Priobskoye |
Pipeline quality |
1 |
7 |
|
|
|
2 (base) |
8 |
|
|
|
3 |
9 |
|
|
Refinery sustainability |
1 |
10 |
|
|
|
2 (base) |
11 |
|
|
|
3 |
12 |
Colombia |
Rubiales |
Pipeline quality |
1 |
13 |
|
|
|
2 (base) |
14 |
|
|
|
3 |
15 |
|
|
Refinery sustainability |
1 |
16 |
|
|
|
2 (base) |
17 |
|
|
|
3 |
18 |
|
Cano Limon |
Pipeline quality |
1 |
19 |
|
|
|
2 (base) |
20 |
|
|
|
3 |
21 |
|
|
Refinery sustainability |
1 |
22 |
|
|
|
2 (base) |
23 |
|
|
|
3 |
24 |
Constraints
To get the optimum solution, we have to run the model with all 24 scenarios. Following are the results for each scenario. After getting the result for all 24 scenarios, we will do hypothesis testing to achieve research objective.
Scenario 1 describes the pipeline quality level 1 for Samotlor oil field in Russia.
If pipeline quality level is 1 (damaged and causing non-exempt waste), its transportation cost increases.
Table 3.8 shows the distance (km) and unit cost (ruble per hundred barrel) from Samotlor oil field to refineries.
Table 3.9 shows the fixed cost and sustainability cost associated with refinery for Scenario 1.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 9.11117E + 11.
Scenario 2 describes the pipeline quality level 2 for Samotlor oil field in Russia.
If pipeline quality level is 2 (good condition and causing little non-exempt waste), its transportation cost remains standard. We considered this model as a base model.
From/To |
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor |
Distance |
1,175 |
596 |
1,916 |
1,171 |
384 |
1,127 |
|
Cost |
2.53 |
3.18 |
2.41 |
2.57 |
3.49 |
2.78 |
Priobskoye |
Distance |
876 |
312 |
2,058 |
1,382 |
178 |
1,326 |
|
Cost |
2.69 |
4.12 |
1.96 |
2.41 |
4.69 |
2.48 |
|
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor—large |
Fixed cost |
189,000 |
123,000 |
132,000 |
151,000 |
143,000 |
149,000 |
|
Sustainability cost |
139 |
111 |
128 |
119 |
102 |
99 |
Samotlor—small |
Fixed cost |
129,000 |
 97,000 |
101,000 |
139,000 |
136,000 |
142,000 |
|
Sustainability cost |
113 |
99 |
119 |
107 |
97 |
94 |
Priobskoye—large |
Fixed cost |
176,000 |
104,000 |
128,000 |
147,000 |
141,000 |
145,000 |
|
Sustainability cost |
127 |
102 |
121 |
127 |
111 |
98 |
Priobskoye—small |
Fixed cost |
103,000 |
 89,000 |
 99,000 |
136,000 |
133,000 |
136,000 |
|
Sustainability cost |
103 |
95 |
111 |
114 |
92 |
95 |
From/To |
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor |
Distance |
1,175 |
596 |
1,916 |
1,171 |
384 |
1,127 |
|
Cost |
2.13 |
2.78 |
2.01 |
2.17 |
309 |
2.38 |
Priobskoye |
Distance |
876 |
312 |
2,058 |
1,382 |
178 |
1,326 |
|
Cost |
2.69 |
4.12 |
1.96 |
2.41 |
4.69 |
2.48 |
Table 3.10 shows the distance (km) and unit cost (ruble per hundred barrel) from Samotlor oil field to refineries.
Table 3.11 shows the fixed cost and sustainability cost associated with refinery for Scenario 2.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 5.84768E + 11.
Scenario 3 describes the pipeline quality level 3 for Samotlor oil field in Russia.
If pipeline quality level is 3 (new condition and not causing non-exempt waste), its transportation cost remains lower than base model.
Table 3.12 shows the distance (km) and unit cost (ruble per hundred barrel) from Samotlor oil field to refineries.
Table 3.13 shows the fixed cost and sustainability cost associated with refinery for Scenario 3.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 7.84129E + 11.
Scenario 4 describes the sustainability level 1 from Samotlor oil field in Russia.
If refinery sustainability level is 1 (high energy usage consumption), its sustainability cost increases.
Table 3.14 shows the distance (km) and unit cost (ruble per hundred barrel) from Samotlor oil field to refineries.
|
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor—large |
Fixed cost |
189,000 |
123,000 |
132,000 |
151,000 |
143,000 |
149,000 |
|
Sustainability cost |
139 |
111 |
128 |
119 |
102 |
99 |
Samotlor—small |
Fixed cost |
129,000 |
97,000 |
101,000 |
139,000 |
136,000 |
142,000 |
|
Sustainability cost |
113 |
99 |
119 |
107 |
97 |
94 |
Priobskoye—large |
Fixed cost |
176,000 |
104,000 |
128,000 |
147,000 |
141,000 |
145,000 |
|
Sustainability cost |
127 |
102 |
121 |
127 |
111 |
98 |
Priobskoye—small |
Fixed cost |
103,000 |
89,000 |
99,000 |
136,000 |
133,000 |
136,000 |
|
Sustainability cost |
103 |
95 |
111 |
114 |
92 |
95 |
From/To |
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor |
Distance |
1,175 |
596 |
1,916 |
1,171 |
384 |
1,127 |
|
Cost |
1.73 |
2.38 |
1.61 |
1.77 |
2.69 |
1.98 |
Priobskoye |
Distance |
876 |
312 |
2,058 |
1,382 |
178 |
1,326 |
|
Cost |
2.69 |
4.12 |
1.96 |
2.41 |
4.69 |
2.48 |
|
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor—large |
Fixed cost |
189,000 |
123,000 |
132,000 |
151,000 |
143,000 |
149,000 |
|
Sustainability cost |
139 |
111 |
128 |
119 |
102 |
99 |
Samotlor—small |
Fixed cost |
129,000 |
97,000 |
101,000 |
139,000 |
136,000 |
142,000 |
|
Sustainability cost |
113 |
99 |
119 |
107 |
97 |
94 |
Priobskoye—large |
Fixed cost |
176,000 |
104,000 |
128,000 |
147,000 |
141,000 |
145,000 |
|
Sustainability cost |
127 |
102 |
121 |
127 |
111 |
98 |
Priobskoye—small |
Fixed cost |
103,000 |
89,000 |
99,000 |
136,000 |
133,000 |
136,000 |
|
Sustainability cost |
103 |
95 |
111 |
114 |
92 |
95 |
From/To |
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor |
Distance |
1,175 |
596 |
1,916 |
1,171 |
384 |
1,127 |
|
Cost |
2.13 |
2.78 |
2.01 |
2.14 |
3.09 |
2.38 |
Priobskoye |
Distance |
876 |
312 |
2,058 |
1,382 |
178 |
1,326 |
|
Cost |
2.69 |
4.12 |
1.96 |
2.41 |
4.69 |
2.48 |
|
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor—large |
Fixed cost |
189,000 |
123,000 |
132,000 |
151,000 |
143,000 |
149,000 |
|
Sustainability cost |
159 |
131 |
148 |
139 |
122 |
119 |
Samotlor—small |
Fixed cost |
129,000 |
97,000 |
101,000 |
139,000 |
136,000 |
142,000 |
|
Sustainability cost |
133 |
119 |
139 |
127 |
117 |
114 |
Priobskoye—large |
Fixed cost |
176,000 |
104,000 |
128,000 |
147,000 |
141,000 |
145,000 |
|
Sustainability cost |
127 |
102 |
121 |
127 |
111 |
98 |
Priobskoye—small |
Fixed cost |
103,000 |
89,000 |
99,000 |
136,000 |
133,000 |
136,000 |
|
Sustainability cost |
103 |
95 |
111 |
114 |
92 |
95 |
Table 3.15 shows the fixed cost and sustainability cost associated with oil field for scenario 4.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 8.3641E + 11.
Scenario 5 describes the sustainability level 2 from Samotlor oil field in Russia.
If refinery sustainability level is 2 (medium energy usage consumption), its sustainability cost remains normal. We considered this model as a base model.
Table 3.16 shows the distance (km) and unit cost (ruble per hundred barrel) from Samotlor oil field to refineries.
Table 3.17 shows the fixed cost and sustainability cost associated with oil field for Scenario 4.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 5.84768E + 11.
Scenario 6 describes the sustainability level 3 from Samotlor oil field in Russia.
If refinery sustainability level is 3 (low energy usage consumption), its sustainability cost decreases.
Table 3.18 shows the distance (km) and unit cost (ruble per hundred barrel) from Samotlor oil field to refineries.
Table 3.19 shows the fixed cost and sustainability cost associated with oil field for Scenario 6.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 8.29875E + 11.
Scenario 7 describes the pipeline quality level 1 for Priobskoye oil field in Russia.
If pipeline quality level is 1 (damaged and causing non-exempt waste), its transportation cost increases.
From/To |
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor |
Distance |
1,175 |
596 |
1,916 |
1,171 |
384 |
1,127 |
|
Cost |
2.13 |
2.78 |
2.01 |
2.14 |
3.09 |
2.38 |
Priobskoye |
Distance |
876 |
312 |
2,058 |
1,382 |
178 |
1,326 |
|
Cost |
2.69 |
4.12 |
1.96 |
2.41 |
4.69 |
2.48 |
|
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor—large |
Fixed cost |
189,000 |
123,000 |
132,000 |
151,000 |
143,000 |
149,000 |
|
Sustainability cost |
139 |
111 |
128 |
119 |
102 |
99 |
Samotlor—small |
Fixed cost |
129,000 |
97,000 |
101,000 |
139,000 |
136,000 |
142,000 |
|
Sustainability cost |
113 |
99 |
119 |
107 |
97 |
94 |
Priobskoye—large |
Fixed cost |
176,000 |
104,000 |
128,000 |
147,000 |
141,000 |
145,000 |
|
Sustainability cost |
127 |
102 |
121 |
127 |
111 |
98 |
Priobskoye—small |
Fixed cost |
103,000 |
89,000 |
99,000 |
136,000 |
133,000 |
136,000 |
|
Sustainability cost |
103 |
95 |
111 |
114 |
92 |
95 |
From/To |
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor |
Distance |
1,175 |
596 |
1,916 |
1,171 |
384 |
1,127 |
|
Cost |
2.13 |
2.78 |
2.01 |
2.14 |
3.09 |
2.38 |
Priobskoye |
Distance |
876 |
312 |
2,058 |
1,382 |
178 |
1,326 |
|
Cost |
2.69 |
4.12 |
1.96 |
2.41 |
4.69 |
2.48 |
|
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor—large |
Fixed cost |
189,000 |
123,000 |
132,000 |
151,000 |
143,000 |
149,000 |
|
Sustainability cost |
119 |
91 |
108 |
99 |
82 |
79 |
Samotlor—small |
Fixed cost |
129,000 |
97,000 |
101,000 |
139,000 |
136,000 |
142,000 |
|
Sustainability cost |
93 |
79 |
99 |
87 |
77 |
74 |
Priobskoye—large |
Fixed cost |
176,000 |
104,000 |
128,000 |
147,000 |
141,000 |
145,000 |
|
Sustainability cost |
127 |
102 |
121 |
127 |
111 |
98 |
Priobskoye—small |
Fixed cost |
103,000 |
89,000 |
99,000 |
136,000 |
133,000 |
136,000 |
|
Sustainability cost |
103 |
95 |
111 |
114 |
92 |
95 |
Table 3.20 shows the distance (km) and unit cost (ruble per hundred barrel) from Priobskoye oil field to refineries.
Table 3.21 shows the fixed cost and sustainability cost associated with refinery for Scenario 7.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 9.17049E + 11.
Scenario 8 describes the pipeline quality level 2 for Priobskoye oil field in Russia.
If pipeline quality level is 2 (good condition and causing little non-exempt waste), its transportation cost remains standard. We considered this model as a base model.
Table 3.22 shows the distance (km) and unit cost (ruble per hundred barrel) from Priobskoye oil field to refineries.
Table 3.23 shows the fixed cost and sustainability cost associated with refinery for Scenario 8.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 5.84768E + 11.
Scenario 9 describes the pipeline quality level 3 for Priobskoye oil field in Russia.
If pipeline quality level is 3 (new condition and not causing non-exempt waste), its transportation cost remains lower than base model.
From/To |
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor |
Distance |
1,175 |
596 |
1,916 |
1,171 |
384 |
1,127 |
|
Cost |
2.13 |
2.78 |
2.01 |
2.17 |
3.09 |
2.38 |
Priobskoye |
Distance |
876 |
312 |
2,058 |
1,382 |
178 |
1,326 |
|
Cost |
3.09 |
4.52 |
2.36 |
2.81 |
5.09 |
2.88 |
|
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor—large |
Fixed cost |
189,000 |
123,000 |
132,000 |
151,000 |
143,000 |
149,000 |
|
Sustainability cost |
139 |
111 |
128 |
119 |
102 |
99 |
Samotlor—small |
Fixed cost |
129,000 |
97,000 |
101,000 |
139,000 |
136,000 |
142,000 |
|
Sustainability cost |
113 |
99 |
119 |
107 |
97 |
94 |
Priobskoye—large |
Fixed cost |
176,000 |
104,000 |
128,000 |
147,000 |
141,000 |
145,000 |
|
Sustainability cost |
127 |
102 |
121 |
127 |
111 |
98 |
Priobskoye—small |
Fixed cost |
103,000 |
89,000 |
99,000 |
136,000 |
133,000 |
136,000 |
|
Sustainability cost |
103 |
95 |
111 |
114 |
92 |
95 |
From/To |
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor |
Distance |
1,175 |
596 |
1,916 |
1,171 |
384 |
1,127 |
|
Cost |
2.13 |
2.78 |
2.01 |
2.17 |
309 |
2.38 |
Priobskoye |
Distance |
876 |
312 |
2,058 |
1,382 |
178 |
1,326 |
|
Cost |
2.69 |
4.12 |
1.96 |
2.41 |
4.69 |
2.48 |
Table 3.24 shows the distance (km) and unit cost (ruble per hundred barrel) from Priobskoye oil field to refineries.
Table 3.25 shows the fixed cost and sustainability cost associated with refinery for Scenario 9.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 7.49348E + 11.
Scenario 10 describes the sustainability level 1 from Priobskoye oil field in Russia.
If refinery sustainability level is 1 (high energy usage consumption), its sustainability cost increases.
Table 3.26 shows the distance (km) and unit cost (ruble per hundred barrel) from Priobskoye oil field to refineries.
Table 3.27 shows the fixed cost and sustainability cost associated with oil field for Scenario 10.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 8.36077E + 11.
Scenario 11 describes the sustainability level 2 from Priobskoye oil field in Russia.
|
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor—large |
Fixed cost |
189,000 |
123,000 |
132,000 |
151,000 |
143,000 |
149,000 |
|
Sustainability cost |
139 |
111 |
128 |
119 |
102 |
99 |
Samotlor—small |
Fixed cost |
129,000 |
97,000 |
101,000 |
139,000 |
136,000 |
142,000 |
|
Sustainability cost |
113 |
99 |
119 |
107 |
97 |
94 |
Priobskoye—large |
Fixed cost |
176,000 |
104,000 |
128,000 |
147,000 |
141,000 |
145,000 |
|
Sustainability cost |
127 |
102 |
121 |
127 |
111 |
98 |
Priobskoye—small |
Fixed cost |
103,000 |
89,000 |
99,000 |
136,000 |
133,000 |
136,000 |
|
Sustainability cost |
103 |
95 |
111 |
114 |
92 |
95 |
From/To |
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor |
Distance |
1,175 |
596 |
1,916 |
1,171 |
384 |
1,127 |
|
Cost |
2.13 |
2.78 |
2.01 |
2.17 |
3.09 |
2.38 |
Priobskoye |
Distance |
876 |
312 |
2,058 |
1,382 |
178 |
1,326 |
|
Cost |
2.29 |
3.72 |
1.56 |
2.01 |
4.29 |
2.08 |
|
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor—large |
Fixed cost |
189,000 |
123,000 |
132,000 |
151,000 |
143,000 |
149,000 |
|
Sustainability cost |
139 |
111 |
128 |
119 |
102 |
99 |
Samotlor—small |
Fixed cost |
129,000 |
97,000 |
101,000 |
139,000 |
136,000 |
142,000 |
|
Sustainability cost |
113 |
99 |
119 |
107 |
97 |
94 |
Priobskoye—large |
Fixed cost |
176,000 |
104,000 |
128,000 |
147,000 |
141,000 |
145,000 |
|
Sustainability cost |
127 |
102 |
121 |
127 |
111 |
98 |
Priobskoye—small |
Fixed cost |
103,000 |
89,000 |
99,000 |
136,000 |
133,000 |
136,000 |
|
Sustainability cost |
103 |
95 |
111 |
114 |
92 |
95 |
If refinery sustainability level is 2 (medium energy usage consumption), its sustainability cost remains normal. We considered this model as a base model.
Table 3.28 shows the distance (km) and unit cost (ruble per hundred barrel) from Priobskoye oil field to refineries.
Table 3.29 shows the fixed cost and sustainability cost associated with oil field for Scenario 11.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 5.84768E + 11.
From/To |
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor |
Distance |
1,175 |
596 |
1,916 |
1,171 |
384 |
1,127 |
|
Cost |
2.13 |
2.78 |
2.01 |
2.14 |
3.09 |
2.38 |
Priobskoye |
Distance |
876 |
312 |
2,058 |
1,382 |
178 |
1,326 |
|
Cost |
2.69 |
4.12 |
1.96 |
2.41 |
4.69 |
2.48 |
|
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor—large |
Fixed cost |
189,000 |
123,000 |
132,000 |
151,000 |
143,000 |
149,000 |
|
Sustainability cost |
139 |
111 |
128 |
119 |
102 |
99 |
Samotlor—small |
Fixed cost |
129,000 |
97,000 |
101,000 |
139,000 |
136,000 |
142,000 |
|
Sustainability cost |
113 |
99 |
119 |
107 |
97 |
94 |
Priobskoye—large |
Fixed cost |
176,000 |
104,000 |
128,000 |
147,000 |
141,000 |
145,000 |
|
Sustainability cost |
147 |
122 |
141 |
147 |
131 |
118 |
Priobskoye—small |
Fixed cost |
103,000 |
89,000 |
99,000 |
136,000 |
133,000 |
136,000 |
|
Sustainability cost |
123 |
115 |
131 |
134 |
112 |
115 |
From/To |
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor |
Distance |
1,175 |
596 |
1,916 |
1,171 |
384 |
1,127 |
|
Cost |
2.13 |
2.78 |
2.01 |
2.14 |
3.09 |
2.38 |
Priobskoye |
Distance |
876 |
312 |
2,058 |
1,382 |
178 |
1,326 |
|
Cost |
2.69 |
4.12 |
1.96 |
2.41 |
4.69 |
2.48 |
|
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor—large |
Fixed cost |
189,000 |
123,000 |
132,000 |
151,000 |
143,000 |
149,000 |
|
Sustainability cost |
139 |
111 |
128 |
119 |
102 |
99 |
Samotlor—small |
Fixed cost |
129,000 |
97,000 |
101,000 |
139,000 |
136,000 |
142,000 |
|
Sustainability cost |
113 |
99 |
119 |
107 |
97 |
94 |
Priobskoye—large |
Fixed cost |
176,000 |
104,000 |
128,000 |
147,000 |
141,000 |
145,000 |
|
Sustainability cost |
127 |
102 |
121 |
127 |
111 |
98 |
Priobskoye—small |
Fixed cost |
103,000 |
89,000 |
99,000 |
136,000 |
133,000 |
136,000 |
|
Sustainability cost |
103 |
95 |
111 |
114 |
92 |
95 |
Scenario 12 describes the sustainability level 3 from Priobskoye oil field in Russia.
If refinery sustainability level is 3 (low energy usage consumption), its sustainability cost decreases.
Table 3.30 shows the distance (km) and unit cost (ruble per hundred barrel) from Priobskoye oil field to refineries.
Table 3.31 shows the fixed cost and sustainability cost associated with oil field for Scenario 12.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 8.30213E + 11.
Scenario 13 describes the pipeline quality level 1 for Rubiales oil field in Colombia.
If pipeline quality level is 1 (damaged and causing non-exempt waste), its transportation cost increases.
Table 3.32 shows the distance (km) and unit cost (peso per barrel) from Rubiales oil field to refineries.
Table 3.33 shows the fixed cost and sustainability cost associated with refinery for Scenario 13.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 3.6274E + 8.
Scenario 14 describes the pipeline quality level 2 for Rubiales oil field in Colombia.
If pipeline quality level is 2 (good condition and causing little non-exempt waste), its transportation cost remains standard. We considered this model as a base model.
From/To |
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor |
Distance |
1,175 |
596 |
1,916 |
1,171 |
384 |
1,127 |
|
Cost |
2.13 |
2.78 |
2.01 |
2.14 |
3.09 |
2.38 |
Priobskoye |
Distance |
876 |
312 |
2,058 |
1,382 |
178 |
1,326 |
|
Cost |
2.69 |
4.12 |
1.96 |
2.41 |
4.69 |
2.48 |
|
|
Angarsk |
Achinsk |
Tuapse |
Syzran |
Kuibyshev |
Novokuibyshevsk |
---|---|---|---|---|---|---|---|
Samotlor—large |
Fixed cost |
189,000 |
123,000 |
132,000 |
151,000 |
143,000 |
149,000 |
|
Sustainability cost |
139 |
111 |
128 |
119 |
102 |
99 |
Samotlor—small |
Fixed cost |
129,000 |
97,000 |
101,000 |
139,000 |
136,000 |
142,000 |
|
Sustainability cost |
113 |
99 |
119 |
107 |
97 |
94 |
Priobskoye—large |
Fixed Cost |
176,000 |
104,000 |
128,000 |
147,000 |
141,000 |
145,000 |
|
Sustainability cost |
107 |
82 |
101 |
107 |
91 |
78 |
Priobskoye—small |
Fixed cost |
103,000 |
89,000 |
99,000 |
136,000 |
133,000 |
136,000 |
|
Sustainability cost |
83 |
75 |
91 |
94 |
72 |
75 |
From/To |
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales |
Distance |
248 |
507 |
86 |
380 |
335 |
|
Cost |
3.32 |
2.65 |
4.95 |
2.76 |
2.91 |
Cano Limon |
Distance |
300 |
556 |
98 |
315 |
401 |
|
Cost |
2.12 |
1.94 |
3.28 |
2.14 |
2.43 |
Table 3.34 shows the distance (km) and unit cost (peso per barrel) from Rubiales oil field to refineries.
Table 3.35 shows the fixed cost and sustainability cost associated with refinery for Scenario 14.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 3.4201E + 8.
Scenario 15 describes the pipeline quality level 3 for Rubiales oil field in Colombia.
If pipeline quality level is 3 (new condition and not causing non-exempt waste), its transportation cost remains lower than base model.
Table 3.36 shows the distance (km) and unit cost (peso per barrel) from Rubiales oil field to refineries.
Table 3.37 shows the fixed cost and sustainability cost associated with refinery for Scenario 15.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 3.2398E + 8.
Scenario 16 describes the sustainability level 1 from Rubiales oil field in Colombia.
If refinery sustainability level is 1 (high energy usage consumption), its sustainability cost increases.
|
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales—large |
Fixed cost |
183,000 |
188,000 |
149,000 |
120,000 |
131,000 |
|
Sustainability cost |
127 |
114 |
91 |
101 |
106 |
Rubiales—small |
Fixed cost |
178,000 |
185,000 |
143,000 |
114,000 |
129,000 |
|
Sustainability cost |
113 |
109 |
88 |
97 |
97 |
Cano Limon—large |
Fixed cost |
165,000 |
173,000 |
143,000 |
116,000 |
129,000 |
|
Sustainability cost |
138 |
125 |
86 |
98 |
102 |
Cano Limon—small |
Fixed cost |
158,000 |
166,000 |
136,000 |
111,000 |
125,000 |
|
Sustainability cost |
124 |
119 |
79 |
95 |
92 |
From/To |
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales |
Distance |
248 |
507 |
86 |
380 |
335 |
|
Cost |
3.14 |
2.42 |
4.78 |
2.59 |
2.79 |
Cano Limon |
Distance |
300 |
556 |
98 |
315 |
401 |
|
Cost |
2.12 |
1.94 |
3.28 |
2.14 |
2.43 |
|
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales—large |
Fixed cost |
183,000 |
188,000 |
149,000 |
120,000 |
131,000 |
|
Sustainability cost |
127 |
114 |
91 |
101 |
106 |
Rubiales—small |
Fixed cost |
178,000 |
185,000 |
143,000 |
114,000 |
129,000 |
|
Sustainability cost |
113 |
109 |
88 |
97 |
97 |
Cano Limon—large |
Fixed cost |
165,000 |
173,000 |
143,000 |
116,000 |
129,000 |
|
Sustainability cost |
138 |
125 |
86 |
98 |
102 |
Cano Limon—small |
Fixed cost |
158,000 |
166,000 |
136,000 |
111,000 |
125,000 |
|
Sustainability cost |
124 |
119 |
79 |
95 |
92 |
From/To |
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales |
Distance |
248 |
507 |
86 |
380 |
335 |
|
Cost |
2.99 |
2.21 |
4.53 |
2.46 |
2.63 |
Cano Limon |
Distance |
300 |
556 |
98 |
315 |
401 |
|
Cost |
2.12 |
1.94 |
3.28 |
2.14 |
2.43 |
|
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales—large |
Fixed cost |
183,000 |
188,000 |
149,000 |
120,000 |
131,000 |
|
Sustainability cost |
127 |
114 |
91 |
101 |
106 |
Rubiales—small |
Fixed cost |
178,000 |
185,000 |
143,000 |
114,000 |
129,000 |
|
Sustainability cost |
113 |
109 |
88 |
97 |
97 |
Cano Limon—large |
Fixed cost |
165,000 |
173,000 |
143,000 |
116,000 |
129,000 |
|
Sustainability cost |
138 |
125 |
86 |
98 |
102 |
Cano Limon—small |
Fixed cost |
158,000 |
166,000 |
136,000 |
111,000 |
125,000 |
|
Sustainability cost |
124 |
119 |
79 |
95 |
92 |
From/To |
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales |
Distance |
248 |
507 |
86 |
380 |
335 |
|
Cost |
3.14 |
2.42 |
4.78 |
2.59 |
2.79 |
Cano Limon |
Distance |
300 |
556 |
98 |
315 |
401 |
|
Cost |
2.12 |
1.94 |
3.28 |
2.14 |
2.43 |
|
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales—large |
Fixed cost |
183,000 |
188,000 |
149,000 |
120,000 |
131,000 |
|
Sustainability cost |
145 |
131 |
105 |
113 |
117 |
Rubiales—small |
Fixed cost |
178,000 |
185,000 |
143,000 |
114,000 |
129,000 |
|
Sustainability cost |
139 |
124 |
96 |
101 |
104 |
Cano Limon—large |
Fixed cost |
165,000 |
173,000 |
143,000 |
116,000 |
129,000 |
|
Sustainability cost |
138 |
125 |
86 |
98 |
102 |
Cano Limon—small |
Fixed cost |
158,000 |
166,000 |
136,000 |
111,000 |
125,000 |
|
Sustainability cost |
124 |
119 |
79 |
95 |
92 |
Table 3.38 shows the distance (km) and unit cost (peso per barrel) from Rubiales oil field to refineries.
Table 3.39 shows the fixed cost and sustainability cost associated with refinery for Scenario 16.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 3.4796E + 8.
Scenario 17 describes the sustainability level 2 from Rubiales oil field in Colombia.
If refinery sustainability level is 2 (medium energy usage consumption), its sustainability cost remains normal. We considered this model as a base model.
Table 3.40 shows the distance (km) and unit cost (peso per barrel) from Rubiales oil field to refineries.
Table 3.41 shows the fixed cost and sustainability cost associated with refinery for Scenario 17.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 3.4201E + 8.
Scenario 18 describes the sustainability level 3 from Rubiales oil field in Colombia.
If refinery sustainability level is 3 (low energy usage consumption), its sustainability cost decreases.
Table 3.42 shows the distance (km) and unit cost (peso per barrel) from Rubiales oil field to refineries.
Table 3.43 shows the fixed cost and sustainability cost associated with refinery for Scenario 18.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 3.3942E + 8.
Scenario 19 describes the pipeline quality level 1 for Cano Limon oil field in Colombia.
If pipeline quality level is 1 (damaged and causing non-exempt waste), its transportation cost increases.
Table 3.44 shows the distance (km) and unit cost (peso per barrel) from Cano Limon oil field to refineries.
From/To |
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales |
Distance |
248 |
507 |
86 |
380 |
335 |
|
Cost |
3.14 |
2.42 |
4.78 |
2.59 |
2.79 |
Cano Limon |
Distance |
300 |
556 |
98 |
315 |
401 |
|
Cost |
2.12 |
1.94 |
3.28 |
2.14 |
2.43 |
|
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales—large |
Fixed cost |
183,000 |
188,000 |
149,000 |
120,000 |
131,000 |
|
Sustainability cost |
127 |
114 |
91 |
101 |
106 |
Rubiales—small |
Fixed cost |
178,000 |
185,000 |
143,000 |
114,000 |
129,000 |
|
Sustainability cost |
113 |
109 |
88 |
97 |
97 |
Cano Limon—large |
Fixed cost |
165,000 |
173,000 |
143,000 |
116,000 |
129,000 |
|
Sustainability cost |
138 |
125 |
86 |
98 |
102 |
Cano Limon—small |
Fixed cost |
158,000 |
166,000 |
136,000 |
111,000 |
125,000 |
|
Sustainability cost |
124 |
119 |
79 |
95 |
92 |
From/To |
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales |
Distance |
248 |
507 |
86 |
380 |
335 |
|
Cost |
3.14 |
2.42 |
4.78 |
2.59 |
2.79 |
Cano Limon |
Distance |
300 |
556 |
98 |
315 |
401 |
|
Cost |
2.12 |
1.94 |
3.28 |
2.14 |
2.43 |
Table 3.45 shows the fixed cost and sustainability cost associated with refinery for Scenario 19.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 3.4213E + 8.
Scenario 20 describes the pipeline quality level 2 for Cano Limon oil field in Colombia.
If pipeline quality level is 2 (good condition and causing little non-exempt waste), its transportation cost remains standard. We considered this model as a base model.
Table 3.46 shows the distance (km) and unit cost (peso per barrel) from Cano Limon oil field to refineries.
|
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales—large |
Fixed cost |
183,000 |
188,000 |
149,000 |
120,000 |
131,000 |
|
Sustainability cost |
119 |
107 |
86 |
97 |
101 |
Rubiales—small |
Fixed cost |
178,000 |
185,000 |
143,000 |
114,000 |
129,000 |
|
Sustainability cost |
109 |
101 |
78 |
89 |
93 |
Cano Limon—large |
Fixed cost |
165,000 |
173,000 |
143,000 |
116,000 |
129,000 |
|
Sustainability cost |
138 |
125 |
86 |
98 |
102 |
Cano Limon—small |
Fixed cost |
158,000 |
166,000 |
136,000 |
111,000 |
125,000 |
|
Sustainability cost |
124 |
119 |
79 |
95 |
92 |
From/To |
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales |
Distance |
248 |
507 |
86 |
380 |
335 |
|
Cost |
3.14 |
2.42 |
4.78 |
2.59 |
2.79 |
Cano Limon |
Distance |
300 |
556 |
98 |
315 |
401 |
|
Cost |
2.31 |
2.11 |
3.46 |
2.43 |
2.59 |
|
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales—large |
Fixed cost |
183,000 |
188,000 |
149,000 |
120,000 |
131,000 |
|
Sustainability cost |
127 |
114 |
91 |
101 |
106 |
Rubiales—small |
Fixed cost |
178,000 |
185,000 |
143,000 |
114,000 |
129,000 |
|
Sustainability cost |
113 |
109 |
88 |
97 |
97 |
Cano Limon—large |
Fixed cost |
165,000 |
173,000 |
143,000 |
116,000 |
129,000 |
|
Sustainability cost |
138 |
125 |
86 |
98 |
102 |
Cano Limon—small |
Fixed cost |
158,000 |
166,000 |
136,000 |
111,000 |
125,000 |
|
Sustainability cost |
124 |
119 |
79 |
95 |
92 |
From/To |
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales |
Distance |
248 |
507 |
86 |
380 |
335 |
|
Cost |
3.14 |
2.42 |
4.78 |
2.59 |
2.79 |
Cano Limon |
Distance |
300 |
556 |
98 |
315 |
401 |
|
Cost |
2.12 |
1.94 |
3.28 |
2.14 |
2.43 |
Table 3.47 shows the fixed cost and sustainability cost associated with refinery for Scenario 20.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 3.4201E + 8.
Scenario 21 describes the pipeline quality level 3 for Cano Limon oil field in Colombia.
If pipeline quality level is 3 (new condition and not causing non-exempt waste), its transportation cost remains lower than base model.
Table 3.48 shows the distance (km) and unit cost (peso per barrel) from Cano Limon oil field to refineries.
Table 3.49 shows the fixed cost and sustainability cost associated with refinery for Scenario 21.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 3.4190E + 8.
Scenario 22 describes the sustainability level 1 from Cano Limon oil field in Colombia.
If refinery sustainability level is 1 (high energy usage consumption), its sustainability cost increases.
|
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales—large |
Fixed cost |
183,000 |
188,000 |
149,000 |
120,000 |
131,000 |
|
Sustainability cost |
127 |
114 |
91 |
101 |
106 |
Rubiales—small |
Fixed cost |
178,000 |
185,000 |
143,000 |
114,000 |
129,000 |
|
Sustainability cost |
113 |
109 |
88 |
97 |
97 |
Cano Limon—large |
Fixed cost |
165,000 |
173,000 |
143,000 |
116,000 |
129,000 |
|
Sustainability cost |
138 |
125 |
86 |
98 |
102 |
Cano Limon—small |
Fixed cost |
158,000 |
166,000 |
136,000 |
111,000 |
125,000 |
|
Sustainability cost |
124 |
119 |
79 |
95 |
92 |
From/To |
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales |
Distance |
248 |
507 |
86 |
380 |
335 |
|
Cost |
3.14 |
2.42 |
4.78 |
2.59 |
2.79 |
Cano Limon |
Distance |
300 |
556 |
98 |
315 |
401 |
|
Cost |
1.98 |
1.75 |
3.02 |
1.99 |
2.27 |
|
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales—large |
Fixed cost |
183,000 |
188,000 |
149,000 |
120,000 |
131,000 |
|
Sustainability cost |
127 |
114 |
91 |
101 |
106 |
Rubiales—small |
Fixed cost |
178,000 |
185,000 |
143,000 |
114,000 |
129,000 |
|
Sustainability cost |
113 |
109 |
88 |
97 |
97 |
Cano Limon—large |
Fixed cost |
165,000 |
173,000 |
143,000 |
116,000 |
129,000 |
|
Sustainability cost |
138 |
125 |
86 |
98 |
102 |
Cano Limon—small |
Fixed cost |
158,000 |
166,000 |
136,000 |
111,000 |
125,000 |
|
Sustainability cost |
124 |
119 |
79 |
95 |
92 |
Table 3.50 shows the distance (km) and unit cost (peso per barrel) from Cano Limon oil field to refineries.
Table 3.51 shows the fixed cost and sustainability cost associated with refinery for Scenario 22.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 3.4204E + 8.
Scenario 23 describes the sustainability level 2 from Cano Limon oil field in Colombia.
If refinery sustainability level is 2 (medium energy usage consumption), its sustainability cost remains normal. We considered this model as a base model.
Table 3.52 shows the distance (km) and unit cost (peso per barrel) from Cano Limon oil field to refineries.
Table 3.53 shows the fixed cost and sustainability cost associated with refinery for Scenario 23.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 3.4201E + 8.
Scenario 24 describes the sustainability level 3 from Cano Limon oil field in Colombia.
If refinery sustainability level is 3 (low energy usage consumption), its sustainability cost decreases.
Table 3.54 shows the distance (km) and unit cost (peso per barrel) from Cano Limon oil field to refineries.
Table 3.55 shows the fixed cost and sustainability cost associated with refinery for Scenario 24.
Run the scenario with Excel using GRG nonlinear, we obtain the total value is 3.4200E + 8.
From/To |
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales |
Distance |
248 |
507 |
86 |
380 |
335 |
|
Cost |
3.14 |
2.42 |
4.78 |
2.59 |
2.79 |
Cano Limon |
Distance |
300 |
556 |
98 |
315 |
401 |
|
Cost |
2.12 |
1.94 |
3.28 |
2.14 |
2.43 |
|
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales—large |
Fixed cost |
183,000 |
188,000 |
149,000 |
120,000 |
131,000 |
|
Sustainability cost |
127 |
114 |
91 |
101 |
106 |
Rubiales—small |
Fixed cost |
178,000 |
185,000 |
143,000 |
114,000 |
129,000 |
|
Sustainability cost |
113 |
109 |
88 |
97 |
97 |
Cano Limon—large |
Fixed cost |
165,000 |
173,000 |
143,000 |
116,000 |
129,000 |
|
Sustainability cost |
151 |
144 |
98 |
112 |
119 |
Cano Limon—small |
Fixed cost |
158,000 |
166,000 |
136,000 |
111,000 |
125,000 |
|
Sustainability cost |
146 |
135 |
91 |
101 |
105 |
From/To |
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales |
Distance |
248 |
507 |
86 |
380 |
335 |
|
Cost |
3.14 |
2.42 |
4.78 |
2.59 |
2.79 |
Cano Limon |
Distance |
300 |
556 |
98 |
315 |
401 |
|
Cost |
2.12 |
1.94 |
3.28 |
2.14 |
2.43 |
|
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales—large |
Fixed cost |
183,000 |
188,000 |
149,000 |
120,000 |
131,000 |
|
Sustainability cost |
127 |
114 |
91 |
101 |
106 |
Rubiales—small |
Fixed cost |
178,000 |
185,000 |
143,000 |
114,000 |
129,000 |
|
Sustainability cost |
113 |
109 |
88 |
97 |
97 |
Cano Limon—large |
Fixed cost |
165,000 |
173,000 |
143,000 |
116,000 |
129,000 |
|
Sustainability cost |
138 |
125 |
86 |
98 |
102 |
Cano Limon—small |
Fixed cost |
158,000 |
166,000 |
136,000 |
111,000 |
125,000 |
|
Sustainability cost |
124 |
119 |
79 |
95 |
92 |
From/To |
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales |
Distance |
248 |
507 |
86 |
380 |
335 |
|
Cost |
3.14 |
2.42 |
4.78 |
2.59 |
2.79 |
Cano Limon |
Distance |
300 |
556 |
98 |
315 |
401 |
|
Cost |
2.12 |
1.94 |
3.28 |
2.14 |
2.43 |
|
|
Barrancabermeja |
Cartagena |
Apjay |
Orito |
Tibu |
---|---|---|---|---|---|---|
Rubiales—large |
Fixed cost |
183,000 |
188,000 |
149,000 |
120,000 |
131,000 |
|
Sustainability cost |
127 |
114 |
91 |
101 |
106 |
Rubiales—small |
Fixed cost |
178,000 |
185,000 |
143,000 |
114,000 |
129,000 |
|
Sustainability cost |
113 |
109 |
88 |
97 |
97 |
Cano Limon—large |
Fixed cost |
165,000 |
173,000 |
143,000 |
116,000 |
129,000 |
|
Sustainability cost |
131 |
119 |
82 |
91 |
95 |
Cano Limon—small |
Fixed cost |
158,000 |
166,000 |
136,000 |
111,000 |
125,000 |
|
Sustainability cost |
119 |
107 |
69 |
82 |
83 |
There are three expected results from this research:
The optimum solution for all the 24 scenarios provides enough information for eight efficiency curves (Figures 3.8–3.15; Tables 3.56–3.64).
Scenario |
Quality Level |
Total Cost |
---|---|---|
1 |
1 |
9.11117E + 11 |
2 |
2 (base) |
5.84768E + 11 |
3 |
3 |
7.84129E + 11 |
Figure 3.8 Samotlor—pipeline quality.
Scenario |
Sustainability Level |
Total Cost |
---|---|---|
4 |
1 |
8.3641E + 11 |
5 |
2 (base) |
5.84768E + 11 |
6 |
3 |
8.29875E + 11 |
Figure 3.9 Samotlor—refinery sustainability.
Scenario |
Quality Level |
Total Cost |
---|---|---|
7 |
1 |
9.17049E + 11 |
8 |
2 (base) |
5.84768E + 11 |
9 |
3 |
7.49348E + 11 |
Figure 3.10 Priobskoye—pipeline quality.
Scenario |
Sustainability Level |
Total Cost |
---|---|---|
10 |
1 |
8.36077E + 11 |
11 |
2 (base) |
5.84768E + 11 |
12 |
3 |
8.30213E + 11 |
Figure 3.11 Priobskoye—refinery sustainability.
Scenario |
Quality Level |
Total Cost |
---|---|---|
13 |
1 |
3.6274E + 8 |
14 |
2 (base) |
3.4201E + 11 |
15 |
3 |
3.2398E + 11 |
Figure 3.12 Rubiales—pipeline quality.
Scenario |
Sustainability Level |
Total Cost |
---|---|---|
16 |
1 |
3.4796E + 8 |
17 |
2 (base) |
3.4201E + 8 |
18 |
3 |
3.3942E + 8 |
Figure 3.13 Rubiales—refinery sustainability.
Scenario |
Quality Level |
Total Cost |
---|---|---|
19 |
1 |
3.4212E + 8 |
20 |
2 (base) |
3.4201E + 8 |
21 |
3 |
3.4190E + 8 |
Figure 3.14 Cano Limon—pipeline quality.
Scenario |
Sustainability Level |
Total Cost |
---|---|---|
22 |
1 |
3.4204E + 8 |
23 |
2 (base) |
3.4201E + 8 |
24 |
3 |
3.4199E + 8 |
Figure 3.15 Cano Limon—refinery sustainability.
Russia |
Colombia |
|||
---|---|---|---|---|
Samotlor |
Priobskoye |
Rubiales |
Cano Limon |
|
Pipeline quality |
34% |
28% |
6% |
4% |
Refinery sustainability |
42% |
42% |
2% |
1% |
From the above efficiency curves, we have to find cost variation for each case and perform hypothesis testing. In order to reject each hypothesis, the model needed to show that both the pipeline quality and refinery sustainability changed the total supply chain cost by 15%.
Table 3.64 shows cost variation by percentage for Russia and Colombia with respect to pipeline quality and refinery sustainability level.
For Russia, cost variation is more than 15% in both the cases, so we have to reject null hypothesis. In other world, pipeline quality and refinery sustainability will impact the supply chain cost.
For Colombia, cost variation is less than 15% in both the cases, so we fail to reject null hypothesis. In other world, pipeline quality and refinery sustainability will not impact the supply chain cost.
There are some expected limitations for this research such as the availability of data and scope of the research. The U.S. EIA provides copious amounts of useful data for the U.S. oil industry. There are certain limitations for the data collection of the Russia and Indonesian oil industry due to lack of information.
The importance of the proposed research is a comparison of pipeline quality and environmental sustainability on supply chain cost for Russia and Colombia. The broader impacts of the proposed research are how investments into other countries’ crude oil supply chains can be quantified and optimized; exporting countries such as Russia and Colombia can be considered as possible candidates for investment for future global needs.
The scope of this research is to extend the research for Indonesia Oil Supply Chain and use the methodology for Russia and Colombia. This scope is already broad enough considering the nature of supply chain activities on both countries. Future work can be conducted as the continuation of this research, which uses the proposed model that includes other countries and adds more variables as type of oil transportation and some other add-on value factors.
Year |
Production |
Estimated Consumption |
Net Imports |
---|---|---|---|
1995 |
9.39989315 |
17.72458904 |
8.32469589 |
1996 |
9.44454918 |
18.3089071 |
8.86435792 |
1997 |
9.46093973 |
18.62030411 |
9.15936438 |
1998 |
9.27800548 |
18.91714521 |
9.63913973 |
1999 |
8.9934137 |
19.51933973 |
10.52592603 |
2000 |
9.05777596 |
19.70107923 |
10.64330327 |
2001 |
8.95700822 |
19.64870685 |
10.69169863 |
2002 |
8.99843288 |
19.76130685 |
10.76287397 |
2003 |
8.76583288 |
20.03350685 |
11.26767397 |
2004 |
8.72242077 |
20.73115574 |
12.00873497 |
2005 |
8.32468767 |
20.80215616 |
12.47746849 |
2006 |
8.31616438 |
20.68741918 |
12.3712548 |
2007 |
8.46932055 |
20.68038082 |
12.21106027 |
2008 |
8.56359563 |
19.49796721 |
10.93437158 |
2009 |
9.13379726 |
18.77139726 |
9.6376 |
2010 |
9.68453151 |
19.18012877 |
9.49559726 |
2011 |
10.13620821 |
18.88207397 |
8.74586576 |
2012 |
11.11735507 |
18.49021585 |
7.37286078 |
2013 |
12.31197483 |
18.88679944 |
6.57482461 |
Source: Preliminary Data U.S. EIA October 2014, web.
Year |
Net Imports |
Saudi Arabia |
Canada |
Russia |
Colombia |
---|---|---|---|---|---|
2004 |
12,097 |
1,557 |
1,980 |
298 |
173 |
2005 |
12,549 |
1,536 |
2,001 |
410 |
188 |
2006 |
12,390 |
1,462 |
2,194 |
368 |
149 |
2007 |
12,036 |
1,483 |
2,266 |
413 |
148 |
2008 |
11,114 |
1,529 |
2,229 |
464 |
181 |
2009 |
9,667 |
1,003 |
2,257 |
562 |
240 |
2010 |
9,441 |
1,096 |
2,302 |
612 |
300 |
2011 |
8,450 |
1,193 |
2,377 |
624 |
371 |
2012 |
7,393 |
1,364 |
2,530 |
477 |
358 |
2013 |
6,237 |
1,326 |
2,593 |
460 |
273 |
2014 |
5,041 |
1,162 |
2,586 |
327 |
174 |
Source: Preliminary Data U.S. EIA October 2014, web.
Year |
Crude Oil Production |
Consumption |
Estimated Net Export |
---|---|---|---|
1992 |
7,631.929 |
4,423.1588 |
3,395.5581 |
1993 |
6,730 |
3,750.4598 |
3,200.5467 |
1994 |
6,135 |
3,178.9824 |
3,127.8767 |
1995 |
5,995 |
2,976.1331 |
3,196.3559 |
1996 |
5,850 |
2,619.4548 |
3,397.1023 |
1997 |
5,920 |
2,562.4824 |
3,538.608 |
1998 |
5,854 |
2,488.6083 |
3,581.0568 |
1999 |
6,078.948 |
2,537.6239 |
3,774.6924 |
2000 |
6,479.202 |
2,578.4981 |
4,145.1408 |
2001 |
6,917 |
2,590.2318 |
4,569.503 |
2002 |
7,408.173 |
2,636.4088 |
5,022.4824 |
2003 |
8,132.1988 |
2,681.8629 |
5,852.9157 |
2004 |
8,804.7077 |
2,750.8139 |
6,522.9565 |
2005 |
9,043.0822 |
2,785.1365 |
6,726.1051 |
2006 |
9,247.2055 |
2,803.4681 |
6,928.8821 |
2007 |
9,437.0634 |
2,885.101 |
7,053.0811 |
2008 |
9,356.7836 |
2,981.919 |
6,893.1139 |
2009 |
9,495.3649 |
2,888.534 |
7,161.0184 |
2010 |
9,694.1145 |
3,134.8999 |
7,158.9405 |
2011 |
9,773.5178 |
3,352.108 |
7,057.955 |
2012 |
9,921.6093 |
3,395.109 |
7,199.6916 |
2013 |
10,053.8438 |
3,515.143 |
7,248.5994 |
Source: U.S. Energy Information Administration.
Year |
Crude Oil Production |
Consumption |
Estimated Net Export |
---|---|---|---|
1990 |
440 |
208.9058 |
245.0924 |
1991 |
419 |
209.8785 |
219.8971 |
1992 |
433 |
232.5302 |
212.2805 |
1993 |
456 |
240.2192 |
227.1003 |
1994 |
450 |
244.4073 |
218.0097 |
1995 |
585 |
250.6331 |
346.421 |
1996 |
622.9645 |
278.1295 |
363.924 |
1997 |
652 |
286.5139 |
378.8357 |
1998 |
732.518 |
289.02 |
456.9996 |
1999 |
816 |
282 |
548.194 |
2000 |
690.5765 |
277.4874 |
426.6286 |
2001 |
625 |
271.1817 |
365.6424 |
2002 |
576.9397 |
256.1985 |
332.0776 |
2003 |
540.733 |
265.3557 |
289.3206 |
2004 |
528.7613 |
267.5158 |
274.4406 |
2005 |
525.7931 |
270.7081 |
269.9784 |
2006 |
531.0385 |
276.9701 |
271.3819 |
2007 |
531.1352 |
270.1889 |
275.9195 |
2008 |
588.3567 |
265.2192 |
338.4548 |
2009 |
670.6457 |
259.6515 |
430.6252 |
2010 |
785.5262 |
269.883 |
536.0068 |
2011 |
914.2544 |
294.2727 |
644.2705 |
2012 |
944.2186 |
304 |
665.0549 |
2013 |
1,003.2463 |
306 |
722.4737 |
Source: U.S. Energy Information Administration.