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Record W2895988612 · doi:10.2118/191482-ms

Contribution of Oil and Gas Production in The US to The Climate Change

2018· article· en· W2895988612 on OpenAlexaboutno aff
Olivier Lançon, Berna Hasçakir

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
FundersTexas A and M University
KeywordsGreenhouse gasPetroleum industryFugitive emissionsFossil fuelEnvironmental scienceAssociated petroleum gasProduction (economics)Natural resource economicsPetroleumClimate changeEnvironmental protectionNatural gasWaste managementEnvironmental engineeringEngineeringEconomicsChemistry

Abstract

fetched live from OpenAlex

Abstract The oil and gas industry has often been blamed for its major contribution to greenhouse gas releases and designated as a target to knock down by media, activists, and environmentalists. It is true to say that without Oil and Gas Industry, anthropogenic emissions of CO2 and CH4 would be much lower. Similarly, it is also true to state that without this industry and petroleum products, our life standards would be much different than the current standards. One should not confuse an activity which generates greenhouse gases, and the effect of product consumption. Evaluating the real routine emissions of the oil and gas industry on the same mode than every other industry is possible and constitutes the objective of this work. As a preliminary result, however, data coming from the Environmental Protection Agency (EPA) clearly highlight that oil and gas production accounts for at least less than 10% of the greenhouse gas emissions from the energy sector in the United States. To more precisely evaluate these emissions, this study relied on environmental impact reports in terms of greenhouse gas emissions, which are available for every production site in the U.S, as well as the oil and gas consumption in the US over the year 2015. Emissions happen during three different stages of the hydrocarbon production; extraction, flaring and venting, and fugitive emissions. The importance of each stage in terms of emissions is extremely variable, depending on the quality of the oil, the field location, and the existence of an outlet for the produced gas. The greenhouse gas emissions contribution from the Oil and Gas industry is 3% for extraction, and about 0% for flaring and venting, and 0% of fugitive emissions in the US. The remaining U.S greenhouse gas emissions while processing petroleum products are due to refining at 88%, and transportation at 9%. However, these results are extremely different for Canadian oil sands, Venezuela heavy oil, Arabian light oil, or Indonesian gas condensate. Worldwide, greenhouse emission source for petroleum industry are 10% for extraction, 19% for flaring and venting, 6% of fugitive emissions, 4% of transport, and 61% of the refinery. As a result, 3.5% of greenhouse gases emitted while processing petroleum products are due to Oil and Gas industry. Based on these results, an extrapolation to the worldwide Oil and Gas production enable to assess the participation of this industry to total emissions. Results show that less than 3 % of worldwide greenhouse emissions comes actually from Oil and Gas industry.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.239
Teacher spread0.225 · 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 designObservational
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

Citations16
Published2018
Admission routes1
Has abstractyes

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