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Record W2029149003 · doi:10.2118/2004-024-ea

Elasticity of a Model Oil/Water Interface

2004· article· en· W2029149003 on OpenAlexafffund
Mohammad Kazem Jafari, Danuta M. Sztukowski, Harvey W. Yarranton

Bibliographic record

VenueCanadian International Petroleum Conference · 2004
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaSyncrude
KeywordsElasticity (physics)MathematicsMaterials scienceComposite material

Abstract

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Introduction Water-in-crude oil emulsions are often created during the recovery, treatment, and transportation of crude oil. Some oilfield emulsions are difficult to break into separate phases using conventional methods. In order to develop more effective treatments for these emulsions, it is necessary to determine the properties of the interfacial film that contributes to their stability. In many cases and, in particular with heavy oils, this film is believed to consist of surface-active materials such as resins, asphaltenes, and native solids. This work focuses on asphaltenes and their role in the formation of interfacial films and emulsion stability. It has been shown that asphaltenes can adsorb as a monolayer at the water-oil interface(1). When the monolayer is present, emulsion stability is significantly enhanced. One possible explanation for the strong stabilizing effect of the monolayer is that it is highly elastic and therefore provides resistance to coalescence. To test this idea, the interfacial rheology of asphaltene films on hydrocarbon/water interfaces is measured using drop shape analysis of an oscillating hydrocarbon droplet in an aqueous medium. The hydrocarbon phase consists of asphaltenes dissolved in mixtures of toluene and heptane. The aqueous phase is distilled water. Elasticity is measured as a function of the frequency of the oscillations, the asphaltene concentration, and the solvent composition. Emulsion stability is assessed for model emulsions prepared from the same phases that were tested in the elasticity experiments. A correlation between elasticity and emulsion stability is sought. Experimental Methods Asphaltenes were precipitated from Athabasca bitumen with n-heptane in a 40:1 solvent to bitumen (cm3 /g) ratio. The mixture was sonicated for 45 minutes, then left to stand for a period of 24 hours. The supernatant was filtered through Whatman #2 filter paper and the filtrate was further diluted to a 4:1 n-heptane to bitumen cm 3 /g) ratio. This mixture was sonicated for 45 minutes, left to stand overnight, and poured through the filter paper. The asphaltene filter cake was allowed to dry until the mass was invariant. The yield of asphaltenes was 15.0%. Precipitated asphaltenes contain non-asphaltenic solids (NAS) such as sand and clay. These solids can introduce error into interfacial tension and elasticity measurements. The solids were removed as follows: an asphaltene sample was dissolved in toluene in a 100:1 toluene:asphaltene (cm3/g) ratio. The mixture was sonicated for 20–40 minutes to ensure complete asphaltene dissolution. The mixture was allowed to stand for one hour, after which it was centrifuged at 4000 rpm (1640 RCF) for six minutes. The supernatant was decanted, and the solvent evaporated until only dry asphaltenes remained. NAS made up 3.1% of the asphaltenes. All emulsion and elasticity experiments were performed with asphaltenes free of NAS. Model emulsions were prepared with asphaltenes, toluene, heptane and water. A known mass of asphaltene was dissolved in toluene and then heptane was added to make up mixtures ranging from 0 to 50 vol% heptane. Water was added to the hydrocarbon phase while the mixture was homogenized with a C A T - 5 2 0 D homogenizer for five minutes.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.981

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 head0.014
GPT teacher head0.227
Teacher spread0.213 · 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 designSimulation or modeling
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

Citations1
Published2004
Admission routes2
Has abstractyes

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