Forecasting World Crude Oil Production Using Multicyclic Hubbert Model
Abstract
The year 2008 has witnessed unprecedented fluctuations in the oil prices. During the first three-quarters, the oil price abruptly increased to $140/bbl, a level that has never been reached before; then because of the global economic crisis, the price dramatically plunged to less than $50/bbl by the end of the year losing more than 64% of the maximum price in less than three months period. The supply of crude oil to the international market oscillated to follow suite according to the law of supply and demand. This behavior affected oil production in all exporting countries. Nonetheless, the demand for crude oil in some developing countries, such as China and India, has increased in the past few years because of the rapid growth in the transportation sector in addition to the absence of viable economic alternatives for fossil fuel. The rapid growth in fuel demand has forced the policy makers worldwide to include uninterrupted crude oil supply as a vital priority in their economic and strategic planning. Even though forecasting should be handled with extreme caution, it is always desirable to look ahead as far as possible to make an intellectual judgment on the future supplies of crude oil. Over the years, accurate prediction of oil production was confronted by fluctuating ecological, economical, and political factors, which imposed many restrictions on its exploration, transportation, and supply and demand. The objective of this study is to develop a forecasting model to predict world crude oil supply with better accuracy than the existing models. Even though our approach originates from Hubbert model, it overcomes the limitations and restrictions associated with the original Hubbert model. As opposed to Hubbert single-cycle model, our model has more than one cycle depending on the historical oil production trend and known oil reserves. The presented method is a viable tool to predict the peak oil production rate and time. The model is simple, accurate, and totally data driven, which allows a continuous updating once new data are available. The analysis of 47 major oil producing countries estimates the world’s ultimate crude oil reserve by 2140 BSTB and the remaining recoverable oil by 1161 BSTB. The world production is estimated to peak in 2014 at a rate of 79 MMSTB/D. OPEC has remaining reserve of 909 BSTB, which is about 78% of the world reserves. OPEC production is expected to peak in 2026 at a rate of 53 MMSTB/D. On the basis of 2005 world crude oil production and current recovery techniques, the world oil reserves are being depleted at an annual rate of 2.1%.
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Peak oil will be reached as early as 2014.
“Nashawi et al. (2010) predicted that peak oil will be reached as early as 2014.”
From Renewable energy from Cyanobacteria: energy production optimization by metabolic pathway engineering (2011) · cites this paper as Nashawi et al. (2010)
Cites
Campbell, C. J., & Laherrère, J. H. (1998) · Scientific American · doi:10.1038/scientificamerican0398-78 · Cited by 1,036 · see citing works
Stretched exponential distributions in nature and economy: “fat tails” with characteristic scales
Laherrère, J., & Sornette, D. (1998) · The European Physical Journal B · doi:10.1007/s100510050276 · Cited by 698 · see citing works
Organization of the Petroleum Exporting Countries (OPEC)
Kurian, G. T. (2011) · The Encyclopedia of Political Science · doi:10.4135/9781608712434.n1108 · Cited by 125 · see citing works
An Analysis of U.S. and World Oil Production Patterns Using Hubbert-Style Curves
Bartlett, A. A. (2000) · Mathematical Geology · doi:10.1023/a:1007587132700 · Cited by 122 · see citing works
Degree of Advancement of Petroleum Exploration in United States
Hubbert, M. K. (1967) · AAPG Bulletin · doi:10.1306/5d25c269-16c1-11d7-8645000102c1865d · Cited by 102 · see citing works
Cleveland, C. J., & Kaufmann, R. K. (1991) · The Energy Journal · doi:10.5547/issn0195-6574-ej-vol12-no2-3 · Cited by 88 · see citing works
Oil production in the lower 48 states
Kaufmann, R. K. (1991) · Resources and Energy · doi:10.1016/0165-0572(91)90022-u · Cited by 76 · see citing works
Peak Oil: Testing Hubbert’s Curve via Theoretical Modeling
Mohr, S. H., & Evans, G. M. (2008) · Natural Resources Research · doi:10.1007/s11053-008-9059-8 · Cited by 39 · see citing works
Relationship Between Proved Reserves And Exploratory Effort
Arps, J. J., Mortada, M., & Smith, A. (1971) · Journal of Petroleum Technology · doi:10.2118/2995-pa · Cited by 35 · see citing works
Forecasting World Natural Gas Supply
Al-Fattah, S. M., & Startzman, R. A. (2000) · Journal of Petroleum Technology · doi:10.2118/62580-jpt · Cited by 34 · see citing works
Worldwide Petroleum-Liquid Supply and Demand (includes associated papers 52597 and 52598 )
Al-Jarri, A. S., & Startzman, R. A. (1997) · Journal of Petroleum Technology · doi:10.2118/38782-jpt · Cited by 32 · see citing works
Future oil production in Brazil—Estimates based on a Hubbert model
Szklo, A. S., Machado, G. V., & Schaeffer, R. (2006) · Energy Policy · doi:10.1016/j.enpol.2006.08.014 · Cited by 29 · see citing works
Optimizing Tax Strategies to Reduce Greenhouse Gases Without Curtailing Growth
Brinner, R. E., Shelby, M., Yanchar, J., et al. (1991) · The Energy Journal · doi:10.5547/issn0195-6574-ej-vol12-no4-1 · Cited by 25 · see citing works
Neural Network Approach Predicts U.S. Natural Gas Production
Al-Fattah, S. M., & Startzman, R. A. (2003) · SPE Production & Facilities · doi:10.2118/82411-pa · Cited by 24 · see citing works
An Empirical Method to Make Oil Production Models Tolerant to Anomalies
Mohr, S. H., & Evans, G. M. (2008) · Natural Resources Research · doi:10.1007/s11053-008-9083-8 · Cited by 6 · see citing works
Modeling the U.S. Oil Industry: How Much Oil Is Left? (includes associated papers 52599 and 52600 )
Taylor, P. J. (1997) · Journal of Petroleum Technology · doi:10.2118/37311-jpt · Cited by 5 · see citing works
Book Review: The Coming Oil Crisis
Everest, D. A. (1997) · Energy & Environment · doi:10.1177/0958305x9700800411 · Cited by 1 · see citing works
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Renewable energy from Cyanobacteria: energy production optimization by metabolic pathway engineering
Quintana, N., Van der Kooy, F., Van de Rhee, M. D., Voshol, G. P., & Verpoorte, R. (2011) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-011-3394-0 · Cited by 338 · see citing works
Peak oil and the low-carbon energy transition: A net-energy perspective
Delannoy, L., Longaretti, P.-Y., Murphy, D. J., & Prados, E. (2021) · Applied Energy · doi:10.1016/j.apenergy.2021.117843 · Cited by 116 · see citing works
- Authors
- Nashawi, I. S., Malallah, A., & Al-Bisharah, M.
- Affiliations
- Kuwait University (KW)
- Kuwait Oil Company (Kuwait) (KW)
- Corresponding author
- Nashawi, Ibrahim Sami
- ORCID
- Malallah, Adel
- Venue
- Energy & Fuels
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-02-04
- Volume
- 24
- Issue
- 3
- Pages
- 1788-1800
- ISSN
- 0887-0624 (ISSN-L)
- 1520-5029
- OpenAlex
- W2006004497
- Cited by
- 224
- References
- 17
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 8 · 2023: 7 · 2022: 11 · 2021: 9 · 2020: 17 · 2019: 13 · 2018: 8 · 2017: 13 · 2016: 12 · 2015: 14 · 2014: 20 · 2013: 23 · 2012: 22
- FWCI
- 12.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Energy & Fuels (publishedVersion)
- Topics
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Global Energy and Sustainability Research
- Social Sciences › Decision Sciences › Management Science and Operations Research › Innovation Diffusion and Forecasting
- Physical Sciences › Engineering › Ocean Engineering › Reservoir Engineering and Simulation Methods
- Keywords
- Hubbert curve, peak oil, oil supply, oil price fluctuations, oil demand growth, oil production increase
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