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Record W2068294982 · doi:10.2118/138969-pa

Simulation of O/W Emulsion Flow in Alkaline/Surfactant Flood for Heavy Oil Recovery

2010· article· en· W2068294982 on OpenAlexafffund
Jinxun Wang, Mingzhe Dong

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2010
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaPetroleum Technology Research Centre
KeywordsEmulsionPulmonary surfactantOil fieldPetroleum engineeringSurface tensionEnhanced oil recoveryAdsorptionChemical engineeringEnvironmental sciencePermeability (electromagnetism)ChemistryMaterials scienceGeologyMembraneEngineeringThermodynamicsOrganic chemistry

Abstract

fetched live from OpenAlex

Summary The formation and flow of emulsions during alkaline flooding process plays an important role for improving heavy oil recovery. In this study alkaline/surfactant (A/S) flood tests were performed in sandpacks to demonstrate the effectiveness of sweep efficiency improvement by the in-situ generated oil-in-water (O/W) emulsion. High tertiary oil recoveries were obtained in sandpack flood tests. Experimental results were history matched by including the mechanisms of in-situ generation and flow of O/W emulsion, as well as the chemical adsorption and the reduction of interfacial tension involved in the chemical flooding process. The decrease in local water phase permeability caused by the entrapment of emulsion droplets was modelled using the filtration theory. Both the pressure response and the oil recovery improvement were fairly matched. Field-scale simulations were conducted to investigate the potential of A/S flooding for heavy oil reservoirs. Simulations showed promising results of chemical flooding for heavy oils. It was indicated that a certain length of waterflooding time would benefit the final oil recovery, and there existed an optimum chemical slug size. These laboratory results and the simulation technique are helpful in the simulation and design of field-scale projects of chemical flooding for enhanced heavy oil recovery.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.221
Teacher spread0.215 · 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

Citations44
Published2010
Admission routes2
Has abstractyes

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