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Record W2623572142 · doi:10.2118/0517-0012-jpt

Comments: Peak Demand or Too Much Oil?

2017· article· en· W2623572142 on OpenAlexaboutno aff
John Donnelly

Bibliographic record

VenueJournal of Petroleum Technology · 2017
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
Fundersnot available
KeywordsPosition (finance)Renewable energyConsumption (sociology)PortfolioNatural resource economicsEconomyEconomicsBusinessEngineeringFinance

Abstract

fetched live from OpenAlex

Editor's column Momentum is building for what is being called the “peak demand” theory—that before too long global oil demand will begin to fall as transportation efficiency, innovations such as electric cars, and government climate change policies will quell the rising consumption of hydrocarbons that has marked the past several decades. What is getting attention is that this sentiment is no longer coming from what could be termed anti-oil interests but is coming from the likes of Shell’s chief executive officer (CEO) and such organizations as the World Energy Council (WEC). Speaking at an energy conference in Houston in March, Shell CEO Ben van Beurden predicted that world oil demand could peak in the late 2020s because of the growth of renewable energy sources and natural gas. He noted that his company is moving toward a lower-carbon, long-term strategy. Shell recently divested most of its Canadian oil sands position and is increasing its position in natural gas. Last year, it bought the BG Group, which built up its natural gas portfolio. Van Beurden emphasized that the industry must reduce carbon dioxide emissions to help countries meet the recent Paris climate change accord goals. The WEC has predicted that global energy consumption will begin declining in a little over a decade, and its eighth annual survey of energy executives around the world showed that growth in renewables and energy efficiency is requiring firms to revise their medium- and long-term outlooks. The peak demand theory undercuts the prevailing industry notion that a rising middle class in developing countries will propel oil demand much higher. Just a few years ago, the industry and many economists were fretting about a shortage of energy supplies to meet this growing consumption. At the same conference where Shell’s CEO spoke, the head of the International Energy Agency (IEA), Fatih Birol, said that global demand is not peaking and in fact will grow by 7.3 million B/D through 2022. He pleaded with oil companies to invest more, otherwise the world would face an oil shortage in the future and the prospect of huge price spikes. He noted that even though sales of electric cars had risen to a record number of more than 1 million, this was still less than 1% of total global auto sales. The trucking, airline, and chemical sectors will continue to drive oil growth, he said. In general, the oil industry is not good at predicting the future. The oil price decline in the late 1990s, the huge run-up in prices led by surging Chinese and Indian demand in the early 2000s, the strength of the price collapse of the past 2 years, and the resilience of the US shale sector all seemed to catch much of the industry flat-footed. The growth in unconventional production has only made supply/demand forecasts tougher. The argument might not be so much about peak demand, but about timing. The industry as well as organizations such as the IEA have predicted that global hydrocarbon use would decline this century and that natural gas would be the “bridge to the future” of economies built more around renewable energy sources. The question is whether that will come in 15 years, 30 years, or even longer.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.885
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.313
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2017
Admission routes1
Has abstractyes

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