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Record W2060973179 · doi:10.3390/su3112080

The EROI of Conventional Canadian Natural Gas Production

2011· article· en· W2060973179 on OpenAlexaboutno aff
Jon Freise

Bibliographic record

VenueSustainability · 2011
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)Natural gasNatural (archaeology)Environmental scienceNatural resource economicsBusinessWaste managementEngineeringEconomicsGeographyMicroeconomicsArchaeology

Abstract

fetched live from OpenAlex

Canada was the world’s third largest natural gas producer in 2008, with 98% of its gas being produced by conventional, tight gas, and coal bed methane wells in Western Canada. Natural gas production in Western Canada peaked in 2001 and remained nearly flat until 2006 despite more than quadrupling the drilling rate. Canada seems to be one of many counter examples to the idea that oil and gas production can rise with sufficient investment. This study calculated the Energy Return on Energy Invested and Net Energy of conventional natural gas and oil production in Western Canada by a variety of methods to explore the energy dynamics of the peaking process. All these methods show a downward trend in EROI during the last decade. Natural gas EROI fell from 38:1 in 1993 to 15:1 at the peak of drilling in 2005. The drilling intensity for natural gas was so high that net energy delivered to society peaked in 2000–2002, while production did not peak until 2006. The industry consumed all the extra energy it delivered to maintain the high drilling effort. The inability of a region to increase net energy may be the best definition of peak production. This increase in energy consumption reduces the total energy provided to society and acts as a contracting pressure on the overall economy as the industry consumes greater quantities of labor, steel, concrete and fuel. It appears that energy production from conventional oil and gas in Western Canada has peaked and entered permanent decline.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.255
Teacher spread0.242 · 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 designTheoretical or conceptual
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

Citations34
Published2011
Admission routes1
Has abstractyes

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