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Record W4400531631 · doi:10.1021/acsomega.4c04946

Investigation of Unresolved Interface “Rag Layer” in Athabasca Oil Sand Bitumen <i>In Situ</i> Recovery

2024· article· en· W4400531631 on OpenAlexafffund
Evgeniya Hristova, Stanislav R. Stoyanov, Richard A. McFarlane, Kasra Nikooyeh

Bibliographic record

VenueACS Omega · 2024
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsNatural Resources Canada
FundersOffice of Energy Research and DevelopmentInnotech AlbertaCenovus Energy
KeywordsAsphaltOil sandsChemistryDiluentOil fieldLayer (electronics)MineralogyMixing (physics)Petroleum engineeringGeologyMaterials scienceComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Steam-assisted gravity drainage (SAGD), the leading commercial in situ bitumen recovery process, involves the underground injection of steam and produces at the well head a hot fluid containing water, hydrocarbons, and sand. This fluid is subjected to separation by diluent addition and gravity in several parallel treaters. Occasionally, the separation may be disrupted in one or few treaters by the occurrence of an unresolved interface or "rag layer" while continuing without disruption in the rest of the treaters. In the current study, we investigate "rag layer" occurrence based on the quantification of laboratory-scale and SAGD field tests and imaging of the "rag layer" morphology. The quantification results show that the formation and volume of the "rag layer" are affected by solids, mixing speed, and solvent addition. The microscopic images demonstrate the presence of both water-in-oil or oil-in water emulsions with a distinct transition between the continuous phases. The visual detection boundaries of the "rag layer" are defined as the threshold between the agglomerated and individual droplet layers. The extent of agglomeration increases in the proximity to the oil-water interface. The contribution of hydrophobic fine inorganic solids (less than 10 μm) to forming a "rag layer" is supported by their accumulation observed at the treaters' oil-water interface, compared to the feed. In well-controlled field operations, the perceived randomness of "rag layer" occurrence could be associated with the fluctuation of fine solid contents in the feed.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.238
Teacher spread0.225 · 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 teacher head, 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

Citations2
Published2024
Admission routes2
Has abstractyes

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