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Record W2585173041 · doi:10.2118/0816-0012-jpt

Gas Producers Look for Opening

2016· article· en· W2585173041 on OpenAlexaboutno aff
John Donnelly

Bibliographic record

VenueJournal of Petroleum Technology · 2016
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCartelNatural gasLiquefied natural gasFossil fuelBusinessMarket shareInternational tradeEconomyEconomicsAgricultural economicsMarket economyEngineeringFinanceIncentive

Abstract

fetched live from OpenAlex

Editor's column While the Organization of Petroleum Exporting Countries (OPEC) has shifted strategy over the past couple of years, losing some of its clout to control oil prices, major natural gas producers are working to create their own cartel that they hope could bring some stability to international gas prices. OPEC, led by Saudi Arabia, decided in late 2014 to stop shoring up oil prices by tweaking global oil supply, leaving it to market dynamics to determine the price of oil. The thinking was to keep market share away from higher-cost producers, such as those in the North American shale. The strategy has basically worked, leaving lots of carnage in its wake. The world’s largest gas producers have a different motive. Because gas is not as tradable as oil, with prices often locked into long-term contracts, gas producers have less ability to influence prices as oil producers do. But the emergence of liquefied natural gas (LNG) trade may provide a potential opening for the gas producers group. Twelve country members and nine observer states met in Iran recently to further develop the strategy of the Gas Exporting Countries Forum (GECF). Participants included Iran, Iraq, Russia, Qatar, Venezuela, Bolivia, Equatorial Guinea, Nigeria, Algeria, Trinidad and Tobago, Egypt, and Libya, among others. It was the largest gathering of the 14-year-old organization, whose members account for almost two-thirds of the world’s gas reserves. Participants discussed the latest trends, developments, and policies affecting natural gas and reaffirmed their support for the objectives of the GECF, which is to support the “collective interests” of its members and encourage cooperation. During the forum, Iran’s president called on gas producers to coordinate policies to increase the share of natural gas in the global energy picture. The GECF lobbied the recent United Nations climate change summit in Paris, noting that gas is a much cleaner-burning energy source than some alternatives. Gas producers are aware that renewables are growing faster than some expected and could undermine gas’ assumed role as the fuel that will bridge oil to future energy supplies. One of the biggest concerns among producers is the pricing mechanism used for gas worldwide. Most of the world’s gas supply is locked in long-term contracts, affecting the seller’s ability to take advantage of market conditions. Although LNG is shipped by tankers and can be priced in short-term contracts, compressed natural gas is shipped via pipeline, making it dependent on long-term deals. Gas producers want what oil producers want—security of demand to fund their economies into the future. But an international gas cartel would face hurdles. Even as LNG trade continues to grow, some of the major LNG exporters—the US, Australia, and Canada—are unlikely to join a cartel. And the volume of global LNG trade still would not approach that of oil, leaving a less transparent market. In addition, the cost of liquefaction infrastructure would likely see players looking for long-term contracts. JPT

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.075
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0060.005
Open science0.0010.002
Research integrity0.0090.011
Insufficient payload (model declined to judge)0.0750.026

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 head0.011
GPT teacher head0.255
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations0
Published2016
Admission routes1
Has abstractyes

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