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Record W7006211672

Técnicas conjuntas para recuperação avançada de óleo utilizando irradiação eletromagnética e unidades de fluxo hidráulico

2019· dissertation· en· W7006211672 on OpenAlexaboutno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2019
Typedissertation
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsnot available
Fundersnot available
KeywordsAntenna (radio)Electromagnetic fieldScale (ratio)Flow (mathematics)Work (physics)Field (mathematics)ViscosityParametric model
DOInot available

Abstract

fetched live from OpenAlex

This work proposes a model to investigate the use of a cylindrical antenna as a thermal recovery method by electromagnetic irradiation of high viscosity oil, associated with the hydraulic flow unit (HFU) technique to determine the best producing zones in the reservoir. The antenna has a simple geometry, of the adapted dipole type, the distribution of energy and temperature produced by the electric field is carefully calculated for analysis of the antenna as an electromagnetic heater. The production will be analyzed using thermo- fluid dynamics simulations on a field scale using a heterogeneous synthetic model built from data sets from the SE-AL oil field for heavy crude oil, whose viscosity model corresponds to that found in Canadian tar sands. The parametric study evaluates the best operating frequency, well configuration, antenna distance to the producing well, and economic analysis for accumulated net production, with electrical energy, using numerical simulations, through adaptation in the STARS® (CMG) software.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.038
GPT teacher head0.295
Teacher spread0.257 · 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 designBench or experimental
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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)Same topicNeurobiology and Insect Physiology ResearchFrench-language works237,207