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Record W2187792617

Production froide des huiles visqueuses

2000· article· fr· W2187792617 on OpenAlexaboutno aff
G. Renard, P. Sarda

Bibliographic record

Venuenot available
Typearticle
Languagefr
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhysicsArt
DOInot available

Abstract

fetched live from OpenAlex

Resume — La production froide de certains reservoirs contenant des huiles visqueuses, au Canada et au Venezuela principalement, amene a des productivites et des taux de recuperation superieurs aux predictions calculees a l’aide des equations habituellement utilisees pour decrire les ecoulements classiques. Pour expliquer ces productions anormalement elevees, un certain nombre de mecanismes ont ete evoques, principalement d’origines hydrodynamiques et geomecaniques. Les proprietes hydrodynamiques des fluides produits, partiellement degazes durant la production : huiles moussantes, fluides a bulles, sont en effet plus favorables que celles des fluides en place. Par effet geomecanique d’erosion interne du sable, un reseau de chenaux (wormholes, piping tubes) peut se creer in situ, ameliorant notablement le drainage. Cet article comprend quatre parties : les observations sur champ, l’etude en laboratoire des huiles moussantes, leur modelisation numerique, les effets geomecaniques lies a la production de sable. Mots-cles : production froide, huile lourde, huile visqueuse, production de sable, wormholes.

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 score0.038
Threshold uncertainty score0.075

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.229
Teacher spread0.219 · 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

Citations5
Published2000
Admission routes1
Has abstractyes

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