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Current State and Prospects of Shale Gas Production

2019· article· en· W2951046023 on OpenAlexaboutno aff
Vladimir Shcherba, A.P. Butolin, Artur Zieliński

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsDirectional drillingOil shaleHydraulic fracturingPetroleum engineeringResource (disambiguation)Shale gasUnconventional oilFossil fuelProduction (economics)Environmental scienceDrillingGroundwaterChinaNatural resource economicsGeologyMining engineeringWaste managementEngineeringGeographyGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract The article compares the technologically recoverable reserves of shale gas as an unconventional resource of hydrocarbon raw materials in various countries of the world. An assessment is made of the use of horizontal well drilling in combination with hydraulic fracturing of the formation during shale gas production, characterized by the level of technology that allows the most efficient extraction of this resource in the US, Canada, China and Argentina. The article outlines perspectives for the development of shale gas in the near and distant future and shows the obstacles to the development of the oil shale industry in some countries. The basic geo-ecological problems in the development of shale gas: the contamination of surface water and soil, groundwater pollution, gas emissions, seismic risks. The ways of solving these problems are primarily through the use of new field development technologies, the implementation of integrated monitoring safety equipment, taking into account local and regional conditions and the condition of the geological 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 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)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.003

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 head0.006
GPT teacher head0.185
Teacher spread0.179 · 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
GenreReview

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

Citations10
Published2019
Admission routes1
Has abstractyes

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Same venueIOP Conference Series Earth and Environmental Science→Same topicAtmospheric and Environmental Gas Dynamics→French-language works237,207→