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Record W2406356518 · doi:10.1002/cjce.22541

Rheological and thermal properties of novel surfactant‐polymer systems for EOR applications

2016· article· en· W2406356518 on OpenAlexvenueno aff
Izhar A. Malik, Usamah A. Al‐Mubaiyedh, Abdullah S. Sultan, Muhammad Shahzad Kamal, Ibnelwaleed A. Hussein

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
FundersSaudi Aramco
KeywordsPulmonary surfactantChemical engineeringThermal stabilityRheologyEnhanced oil recoveryPolymerSurface tensionPolyacrylamideChemistryViscosityMaterials scienceChromatographyPolymer chemistryOrganic chemistryComposite materialThermodynamics

Abstract

fetched live from OpenAlex

In this work, two surfactant‐polymer (SP) systems were evaluated for enhanced oil recovery applications. The first SP system contained partially hydrolyzed polyacrylamide and alkyl polyethylene glycol ether‐based non‐ionic surfactant. The second SP system consisted of the same polymer and alcohol propoxylate sulphate‐based anionic surfactant. Rheology, thermal stability, interfacial tension (IFT), and core flooding experiments were performed to evaluate the SP systems at different temperatures, surfactant concentrations, and salt concentrations. The anionic surfactant reduced the viscosity of the polymer. However, the effect of the non‐ionic surfactant on the rheological properties was not significant. The non‐ionic surfactant was found to be stable at 80 °C while the structural changes were identified in the anionic surfactant after aging. IFT values of both surfactants were measured at various temperatures and salinities. Due to poor thermal stability and IFT increasing with temperature, the SP system containing the propoxylated anionic surfactant is recommended for applications in low‐temperature reservoirs only. However, the SP system containing the ethoxylated non‐ionic surfactant showed promising results at high‐temperature and high‐salinity conditions and 26 % additional oil recovery was obtained.

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 score0.066
Threshold uncertainty score0.215

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 head0.183
Teacher spread0.169 · 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

Citations30
Published2016
Admission routes1
Has abstractyes

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