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%.

Utilization of biodiesel-derived glycerol or xylose for increased growth and lipid production by indigenous microalgae

“…Today, the full consequences of an abrupt interruption in crude oil supplies are unimaginable, but the era of cheap and abundant oil is already gone. The ever growing demand, with ramped-up prices over the last few decades, and the perspective of a decline in oil production rates (peak oil) in the near future, indicate that we are reaching a critical point (Nashawi et al 2010). Moreover, the direct and indirect toll on the environment and health systems is beginning to change the cost-benefit calculus of using this black gold.…”

Homogeneous Catalyzed Reactions of Levulinic Acid: To γ‐Valerolactone and Beyond

“…LA could be converted to S-GVL in moderate yields of 66% and with 98.5% ee at 60 o C, 60 bar H 2 in EtOH using a catalyst system generated in situ from [Ru(Me-allyl) 2 (COD)], S-BINAP and HCl. [28] Higher yields and ee where however achieved when EL was used as substrate, achieving 95% yields and 99% ee for S-GVL (table 1, entries [32][33].…”

Establishment of a multi-cycle generalized Weng model and its application in forecasts of global oil supply

“…These include the Hubbert, Gaussian and Logistic models (Reynolds 2014;Saraiva et al 2014;Brandt 2007); system simulation methods, which are based on causal relationship of factors, such as the system dynamics method (Tao and Li 2007;Tang et al 2010;Hosseini and Shakouri 2016); and econometric models based on economic theory (Kaufmann 1991;Pindyk and Rubinfeld 1998). The most widely used method is the curve-fitting model (Gallagher 2011;Sorrell and Speirs 2010;Nashawi et al 2010;Ebrahimi and Ghasabani 2015).…”