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Record W1978909791 · doi:10.1190/tle31080898.1

Environmental challenges in fracturing of unconventional resources

2012· article· en· W1978909791 on OpenAlexaff
Azra N. Tutuncu, C. Krohn, Stephan Gelinsky, Jacques P. Leveille, Cengiz Esmersoy, A.I. Mese

Bibliographic record

VenueThe Leading Edge · 2012
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsGeomechanica (Canada)
Fundersnot available
KeywordsHydraulic fracturingUnconventional oilSession (web analytics)Petroleum engineeringDirectional drillingTight oilTight gasShale gasOil shaleWork (physics)Resource (disambiguation)Emerging technologiesFossil fuelDrillingGeologyComputer scienceEngineeringWaste managementMechanical engineering

Abstract

fetched live from OpenAlex

With support of the SEG Research Committee, the authors of this paper organized a special session at the 2011 SEG Annual Meeting focused on the environmental challenges of developing tight, unconventional hydrocarbon reservoirs with special emphasis on the controversial hydraulic fracturing technology. Goals of the session were to support a better understanding of the challenges from the environmental perspective and to discuss possible solutions to these challenges through improving existing methods and developing novel exploration and stimulation techniques. Recognized unconventional resource experts brought their perspectives to the special session to highlight these challenges and work toward bringing the community together for solutions. It is evident that advances in horizontal drilling and multistage fracturing technologies have had significant influence on the global spread of the exploration for and production from gas shale and shale oil reservoirs.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score0.219

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 communication0.0000.000
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 head0.022
GPT teacher head0.221
Teacher spread0.199 · 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 designSimulation or modeling
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

Citations8
Published2012
Admission routes1
Has abstractyes

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