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Record W2987520121 · doi:10.7939/r3-333x-6t13

Adsorption at Oil/Water Interface: Application in SAGD Operation

2019· article· en· W2987520121 on OpenAlexaboutno aff
Maryam Kargar

Bibliographic record

VenueUniversity of Alberta Library · 2019
Typearticle
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsAdsorptionPetroleum engineeringInterface (matter)Environmental scienceProcess engineeringChemistryEngineering

Abstract

fetched live from OpenAlex

Interfacial activity of SAGD PW endogenous surfactants, humic acids (HAs), and their interaction dynamics with naphtha-diluted Alberta oil sand bitumen (AOSB) present in model SAGD produced water has been addressed in the first part of this PhD thesis. Dynamic interfacial tension σ(t) between oil and water phases has been studied using a pendant drop tensiometer in the first part of this PhD thesis and its correlation to the properties of SAGD PW has been further investigated. The effect of AOSB dilution ratios, pH of model SAGD PW and surfactant concentrations on the dynamic interfacial tension (IFT) of naphtha-diluted bitumen/water interface has been monitored. A theoretical model of surfactant adsorption at the interface of naphtha-diluted bitumen/model SAGD produced water has been applied to the experimental curves. In the next part of this PhD thesis, the oil/water (O/W) interface at nano-scale has been studied using a thin liquid film (TLF) set up. The interface of O/W has been monitored for different aqueous phases of surfactant solutions and ionic liquids. Later, a systematic study of TLF of n-dodecane as an intervening liquid phase in aqueous surfactant solution is performed using a 3D-printed modified Scheludko-cell (MSC). The effect of the ionic strength of the ionic liquid (IL) phase on the current–voltage characteristic curve of the system is monitored. It is found that TLF conductivity increases as the ionic strength of the IL phase increases. Moreover, the transient study of the TLF conductivity showed that the TLF conductivity increases over time until it reaches to a quasi-steady condition. We obtained an induced conductivity for the TLF formed for two cases of SDS as anionic surfactants and KCl as inorganic hydrophilic ions. We later developed a model for the adsorption of the ionic species at the perfect dielectric liquid (PDL)/IL interface in both cases of the anionic surfactants and inorganic hydrophilic ions. In order to rule out the charge leakage effect within oil phase in the observed increase in the TLF conductivity, the oil film conductivity without the presence of any aqueous phase is measured under the current experimental conditions. The electric field applied to the TLF is also quantified by simultaneously solving the non-linear Poisson-Boltzmann equation for IL phase and Laplace equation for the PDL phase. Either studies rule out the evidence of charge leakage within the oil phase under the current experimental conditions. The validity of the surfactants adsorption at O/W interface is also examined by utilizing the pendant drop tensiometric study of the oil phase in aqueous solution. The adsorption time-scale of surfactants present in IL phase at O/W interface using this method was comparable to the electrical conductivity measurement done by MSC. In the last part of this PhD thesis work, a theoretical model has been developed to study the O/W interface electric potential at different applied voltages to the TLF. We anticipate that the results of this study will bring about a better understanding of the interfacial film properties leading to the advancement of the design of the next generation SAGD W/O or O/W emulsion separation unit operations and the furtherance of the prediction of the coalescence mechanism in SAGD PW emulsions.

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 score0.679
Threshold uncertainty score0.291

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 head0.002
GPT teacher head0.141
Teacher spread0.139 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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