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Record W2319190135 · doi:10.1021/ie5014986

Evaluation of Two New Self-assembly Polymeric Systems for Enhanced Heavy Oil Recovery

2014· article· en· W2319190135 on OpenAlexafffund
Bing Wei, Laura Romero‐Zerón, Denis Rodrigue

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2014
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversité LavalUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationCenovus Energy
KeywordsPolyacrylamideEnhanced oil recoveryChemical engineeringViscoelasticityXanthan gumPorosityHydrolysisMaterials scienceChemistryPolymer chemistryOrganic chemistryComposite materialRheology

Abstract

fetched live from OpenAlex

In enhanced oil recovery (EOR), the stability of polymeric systems in harsh reservoir conditions is significant. A proof of concept research on the application of supramolecular self-assembly for EOR is presented in this paper. The motivation was to acquire new insights on the effectiveness of these extended polymolecular assemblies with improved salinity and hardness tolerance and viscoelastic properties for EOR. The formation of these self-assemblies relies on noncovalent interactions that hold them together. The performance of two self-assembly systems derived from a partially hydrolyzed polyacrylamide (SAP-HPAM) and xanthan gum (SAP-XG) for heavy oil recovery was established and compared to the performance of a commercial hydrophobically modified polyacrylamide (HMSPAM). The SAP-HPAM produced 20% higher incremental heavy oil recovery than the baseline HPAM; while the SAP-XG does not show suitable propagation within the porous media. These experimental results provide new helpful insights for the technical and cost-effective optimization of these self-assembly compositions for EOR applications.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.076
GPT teacher head0.347
Teacher spread0.271 · 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.

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

Citations45
Published2014
Admission routes2
Has abstractyes

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