1. © SAP Training and Change Management Oil Complexity Faisal BaDughaish The Export-Import Community Supervised by Prof. Ronaldo Menezes

2. © SAP Training and Change Management Outline Background The need of studying oil as a complex network The Model: Oil World as a Network Constructing the Data Building the Network Results Conclusion Future Work

3. © SAP Training and Change Management Background: Oil Nearly everything in our lives is  made from oil,  made by machinery and systems dependent on oil,  and transported by oil as either gas or diesel fuel. I mean everything!!!

4. © SAP Training and Change Management Ammonia, Anesthetics, Antihistamines, Artificial limbs, Artificial Turf, Antiseptics, Aspirin, Auto Parts, Awnings, Balloons, Ballpoint pens, Bandages, Beach Umbrellas, Boats, Cameras, Candles, Car Battery Cases, Carpets, Caulking, Combs, Cortisones, Cosmetics, Crayons, Credit Cards, Curtains, Deodorants, Detergents, Dice, Disposable Diapers, Dolls, Dyes, Eye Glasses, Electrical Wiring Insulation, Faucet Washers, Fishing Rods, Fishing Line, Fishing Lures, Food Preservatives, Food Packaging, Garden Hose, Glue, Hair Coloring, Hair Curlers, Hand Lotion, Hearing Aids, Heart Valves, Ink, Insect Repellant, Insecticides, Linoleum, Lip Stick, Milk Jugs, Nail Polish, Oil Filters, Panty Hose, Perfume, Petroleum Jelly, Rubber Cement, Rubbing Alcohol, Shampoo, Shaving Cream, Shoes, Toothpaste, Trash Bags, Upholstery, Vitamin Capsules, Water Pipes, Yarn

5. © SAP Training and Change Management Background: Microeconomics 101 The price of any commodity heavily depends on its supply and demand. Supply & Demand Maintaining the equilibrium

6. © SAP Training and Change Management Background: Oil SupplyDemand ProducerConsumer ExporterImporter Saudi ArabiaUnited States Major Exporters: OPEC, Russia, Norway Major Importers: United States, Japan, China OPEC: the Organization of the Petroleum Exporting Countries consists of: Algeria, Angola, Ecuador, Iran, Iraq, Kuwait, Libya, Nigeria, Qatar, Saudi Arabia, the United Arab Emirates, and Venezuela.

7. © SAP Training and Change Management Why Oil? Why Supply & Demand? Oil is the most basic global commodities and the oscillation of its price has both direct and indirect impact on the global economy prices of oil are analyzed, tracked and studied very closely by investors, scientists and politics worldwide What’s drive the price? S & D… Therefore, we need to analyze them!

8. © SAP Training and Change Management How Could Complex Network Help? Global Energy Outlook  http://www.youtube.com/watch?v=WahloApfLmI http://www.youtube.com/watch?v=WahloApfLmI  6:00-7:00, 8:55-10:00, 26:45-29:30 The oil world is a network! Analyzing the network would certainly help!

9. © SAP Training and Change Management The Model: Oil World as a Network country A supplies country B with X amount of oil or edge(A,B)=X B A X = 20 K bbl/d

10. © SAP Training and Change Management Constructing the Data lack of one centralized official representative of global oil needs and supplies Collecting data is not a direct process Solution? 3 main sources over 22 years:  OPEC  Non-OPEC Top Exporters  The Rest

11. © SAP Training and Change Management Data from OPEC found all the crude oil exports from those countries by continent of destination and some of the major importer countries fill the rest of the other countries in each continent  total imports of each country provided by EIA divided by total imports of the whole continent  how much each OPEC member would export to that continent

12. © SAP Training and Change Management Saudi (Top) and Venezuela (bottom) export to all continents Percentage of Imports of each country in Europe

13. © SAP Training and Change Management Constructing the Data Non-OPEC top exporters  Russia, Norway, Kazakhstan and Canada  Doesn’t vary, neighbors The rest  20.5%  Their total

14. © SAP Training and Change Management Building Networks 1986, 1990, 1995, 2000, 2002 and 2006 threshold highlights the countries that import more than 50000 bbl/d

15. © SAP Training and Change Management Building the Network 1986 1990 1995 2000

16. © SAP Training and Change Management Building Networks (left 2002, 2006)

17. © SAP Training and Change Management 1986 1990 1995 2000

18. © SAP Training and Change Management Building Networks (left 2002, 2006)

19. © SAP Training and Change Management Results Average clustering coefficient 0.945 (high) Average path length 0.058 (very small) Log-log plot (follows the signature of a power law)

20. © SAP Training and Change Management Results with time many more countries increased their importation or exportation to more than the fifty thousand barrels per day. As a result more were shown progressively. Studying China’s behavior Highlighting China’s import in 6 different years

21. © SAP Training and Change Management 1986

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27. © SAP Training and Change Management Conclusion The network is a small-world and a scale-free which confirm our hypotheses stating that the oil market is recognized as a complex network. How major importers evolve, change and develop over time Trends could be monitored and predicted

28. © SAP Training and Change Management Future Work That was just the beginning! More experiments (dynamic) Patterns can be obtained and could be used to foresee future prices according to the expected changes in supply and demand 3 rd attribute to our current model. Currently, we have the weight represented as the amount of oil exported and the year, the price would be added respectively to the model

29. © SAP Training and Change Management References OPEC's Annual Statistical Bulletin and World Oil Outlook, 44 th edition, July 8, 2009 Annual Energy Outlook 2010, United States Energy Information Administration (EIA), December 14, 2009. International Energy Statistics, United States Energy Information Administration (EIA). S. H. Strogatz, Exploring Complex Networks, (2001) Tore Opsahl and Pietro Panzarasa, Clustering in Weighted Networks (2009). R. Albert and A.-L. Barabási, Statistical mechanics of complex networks, (2002) M. E. J. Newman, The structure and function of complex networks, (2003)