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Record W2312808210 · doi:10.1021/ef301200v

Asphaltene Precipitation from Crude Oils in the Presence of Emulsified Water

2012· article· en· W2312808210 on OpenAlexafffund
Asok Kumar Tharanivasan, Harvey W. Yarranton, Shawn D. Taylor

Bibliographic record

VenueEnergy & Fuels · 2012
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsSchlumberger (Canada)University of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAsphalteneChemistryPrecipitationDilutionSolubilityHeptaneChromatographyCrude oilChemical engineeringAdsorptionEmulsionOrganic chemistryGeologyPetroleum engineeringThermodynamics

Abstract

fetched live from OpenAlex

The primary objective of this work was to determine the effect of emulsified water on the onset and the amount of asphaltene precipitation from diluted crude oils. Asphaltene precipitation yields were measured from an Athabasca bitumen and a Gulf of Mexico crude oil diluted with n -heptane. The experiments were performed with and without emulsified water added to the oils. Yields were compared to determine the effect of the emulsified water. At dilution ratios above the onset of precipitation for dewatered oils, yields were observed to be same for both dewatered oils and oils emulsified with water. Hence, the presence of water had no detectable effect on the solubility of asphaltenes in a crude oil. However, asphaltenes adsorbed on the surface of emulsified water droplets were removed with the water droplets and reported as yield below the onset. The secondary objective of this work was to analyze the compositional differences between the asphaltenes precipitated at the onset condition, asphaltenes adsorbed onto the interface, and bulk asphaltenes. On the basis of CHNSO analysis, it was found that there is no compositional difference between these three different asphaltenes.

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 score0.017
Threshold uncertainty score0.520

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 head0.015
GPT teacher head0.243
Teacher spread0.228 · 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

Citations50
Published2012
Admission routes2
Has abstractyes

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