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Record W1967122410 · doi:10.1007/s12182-015-0025-x

Modeling of flow of oil-in-water emulsions through porous media

2015· article· en· W1967122410 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePetroleum Science · 2015
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPorous mediumPetroleum engineeringFlow (mathematics)Water in oilPorosityEmulsionChemical engineeringEnvironmental scienceMaterials scienceEngineeringGeotechnical engineeringMechanics

Abstract

fetched live from OpenAlex

Formation and flow of emulsions in porous media are common in all enhanced oil recovery techniques. In most cases, oil-in-water (O/W) emulsions are formed in porous media due to oil–water interaction. Even now, detailed flow mechanisms of emulsions through porous media are not well understood. In this study, variation of rate of flow of O/W emulsions with pressure drop was studied experimentally, and rheological parameters were calculated. The pressure drop increases with an increase in oil concentration in the O/W emulsion due to high viscosity. The effective viscosity of the emulsion was calculated from the derived model and expressed as a function of shear rate while flowing through porous media. Flow of O/W emulsions of different concentrations was evaluated in sand packs of different sand sizes. Emulsions were characterized by analyzing their stability, rheological properties, and temperature effects on rheological properties.

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 score0.168
Threshold uncertainty score0.316

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 head0.023
GPT teacher head0.250
Teacher spread0.227 · 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