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Fate of Organic Liquid-Crystal Domains during Steam-Assisted Gravity Drainage/Cyclic Steam Stimulation Production of Heavy Oils and Bitumen

2017· article· en· W2606365211 on OpenAlexafffund
Chuan Qin, Mildred Becerra, John M. Shaw

Bibliographic record

VenueEnergy & Fuels · 2017
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Alberta
FundersVirtual Materials GroupConocoPhillipsNatural Sciences and Engineering Research Council of CanadaTotalShellBP
KeywordsSteam-assisted gravity drainageAsphalteneOil sandsAsphaltSteam injectionPetroleum engineeringHeat transferChemistryEnvironmental scienceMaterials scienceGeologyOrganic chemistryMechanics

Abstract

fetched live from OpenAlex

The fate and impacts of hydrocarbon-based amphotropic liquid-crystal-rich domains (a recently identified material class found in hydrocarbon resources) during production transport and refining are unknown. New materials and process knowledge on this topic will contribute to parsing impacts currently attributed to asphaltenes or other crude oil fractions. In this qualitative work, the fate of liquid-crystal-rich domains in steam-assisted gravity drainage (SAGD) and cyclic steam stimulation (CSS) production environments is surveyed, using a combined laboratory and field study. In the laboratory, a fraction of liquid-crystal-rich domains present in Athabasca bitumen is shown to transfer to the water-rich phase under simulated SAGD and CSS conditions and transfer mechanisms are discussed. In the field study, liquid-crystal-rich domain transfer from Peace River and Athabasca bitumen to process water during SAGD production is demonstrated. Transferred liquid-crystal-rich domains are subsequently captured in surface facilities (primary separation, secondary separation, and water treatment processes) and do not impact steam generator operation, under normal operating conditions. Most of the liquid-crystal-rich domains are returned to the hydrocarbon-rich phase during primary separation. Impacts of liquid-crystal-rich domains on hydrocarbon resource transport and refining and SAGD surface facility optimization comprise foci for future study.

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 score0.003
Threshold uncertainty score0.006

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 head0.008
GPT teacher head0.227
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

Citations6
Published2017
Admission routes2
Has abstractyes

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