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Record W2537493208 · doi:10.2118/1115-0023-jpt

What Is All This Talk About Emissions?

2015· article· en· W2537493208 on OpenAlexaff
Audrey Mascarenhas, John Sutherland

Bibliographic record

VenueJournal of Petroleum Technology · 2015
Typearticle
Languageen
FieldEnergy
TopicOil, Gas, and Environmental Issues
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsGreenhouse gasClean Air ActLegislationMajor stationary sourceAir quality indexAir pollutionAgency (philosophy)Natural resource economicsBusinessEnvironmental protectionEnvironmental scienceClimate changeEnvironmental planningGlobal warmingHazardous wasteWaste managementEngineeringLawPolitical scienceEconomicsMeteorology

Abstract

fetched live from OpenAlex

Beyond the Headlines Emissions are in the air and in the headlines every day. Whether the discussion is on human health impacts of pollution, greenhouse gas (GHG) emissions and their impact on climate change, or the misleading performance of a diesel engine, the bottom line is there is a global focus on emissions. Emission discussions are also in the forefront of the oil and gas industry. In 2012, the US Environmental Protection Agency (EPA) mandated new emission rules for our industry dealing with volatile organic hydrocarbons (VOCs), hazardous air pollutants (HAPs), and, most recently, methane. On 18 August, the agency proposed additional measures (EPA 2015) that supplement the earlier regulations and that “together will help combat climate change, reduce air pollution that harms public health, and provide greater certainty about Clean Air Act permitting requirements for the oil and natural gas industry.” The rules have set limits on emissions. If they cannot be captured, the emissions must be combusted at a 95% destruction efficiency at a minimum. Destruction efficiency is not as extensive a measure of performance as combustion efficiency; however, the move to performance-based legislation is a positive one and will most certainly lead to improved air quality and a healthier relationship with communities in close proximity to oil and gas development. Within the US, various states have or are in the process of enacting legislation specific to their local situation, on the proviso that their requirements are not weaker than the federal rules. In Colorado, for example, much of the industry activity occurs in the vicinity of communities. The state regulator is moving toward mandating de vices that not only combust efficiently, but also fully enclose the combustion to eliminate the visibility of the flare. It is also spot inspecting facilities with special cameras that detect uncombusted hydrocarbons, which are a clear indicator of poor performance. Companies that are emitting uncombusted hydrocarbons will be subject to considerable fines. North Dakota has put a rule in place that the industry must find an acceptable method of using a significant, measurable portion of a well’s associated gas, or oil production from that well will be capped. There are other situations in which the new EPA requirements, combined with state rules, will result in improved operations. The existing 2012 EPA legislation covered natural gas wellsites, production gathering and boosting stations, natural gas processing plants, and natural gas compressor stations. The proposed EPA legislation requires the reductions of methane and VOC emissions from hydraulically fractured oil wells and extends the emission reduction targets downstream covering equipment in the natural gas transmission segment. In view of this regulation, two questions are central to the emissions issue. 1. Is there a technology that can deliver results cost-effectively and address the community concerns about emissions? 2. Is it possible to comply with the new rules in the current low oil and natural gas price environment?

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.019
GPT teacher head0.266
Teacher spread0.246 · 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.

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

Citations1
Published2015
Admission routes1
Has abstractyes

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