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Record W2916515722 · doi:10.12972/ksmer.2017.54.5.521

Analysis on the SAGD Simulation Using Characteristic Variable of Fracture System in Fractured Carbonate Reservoirs

2017· article· en· W2916515722 on OpenAlex
Ju-Hwan Na, Ilsik Jang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of the Korean Society of Mineral and Energy Resources Engineers · 2017
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPorosityPetroleum engineeringCarbonatePermeability (electromagnetism)GeologyFracture (geology)Matrix (chemical analysis)MineralogyGeotechnical engineeringMaterials scienceComposite materialChemistry

Abstract

fetched live from OpenAlex

The OOIP (original oil in-place) of bitumen in fractured carbonate reservoir of Grosmont, Canada is estimated at about 406.5 billion barrels. The Grosmont reservoir is characterized as various matrix sizes due to heterogeneity in fracture density. SAGD simulations for the Grosmont Formation have been based on the dual porosity and dual permeability model. In this study, characteristic variables for fracture system are considered to reflect the mechanism in fracture due to steam injection. The result shows that the characteristic variables play important role in dual porosity model, while trivial in dual permeability model. The effect of the characteristic variables for fracture system has been investigated in terms of the optimal preheating period, recovery factor, and cSOR.

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.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.368

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 head0.009
GPT teacher head0.211
Teacher spread0.202 · 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