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Record W2736160489 · doi:10.4236/aces.2017.73022

Efficiency of Ionic Liquid 1-Ethyl-3-Methyl-Imidazolium Acetate ([EMIM][Ac]) in Enhanced Medium Oil Recovery

2017· article· en· W2736160489 on OpenAlexaff
Ali Alarbah, Mohamed Shirif, Ezeddin Shirif

Bibliographic record

VenueAdvances in Chemical Engineering and Science · 2017
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsIonic liquidChemistryEthyl acetateChromatographyOrganic chemistryNuclear chemistryCatalysis

Abstract

fetched live from OpenAlex

Chemical flooding is one of the most efficient methods for Enhanced Oil Recovery (EOR). This study demonstrates the efficiency of mixing different concentrations of Ionic Liquid (IL), 1-Ethyl-3-Methyl-Imidazolium Acetate ([EMIM][Ac]), with Weyburn brine to improve a medium oil recovery, Weyburn oil, from an unconsolidated sand pack sample at room conditions. Effects of Slug Size (SS), IL + brine slug initiation time, and combining IL with alkali on the Recovery Factor (RF) were investigated. This study showed that the optimum concentration of ([EMIM][AC]) was 1000 ppm and the most efficient injection time of the chemical slug was at the beginning of the flooding procedure (as secondary flooding mode). In addition, it was proved that the potential of injecting a slug of IL + brine is much better than that of introducing a slug of alkali + brine. Besides, the combination of IL and alkali (AIL) resulted in better RF than injecting either of them alone. Finally, the Surface Tension (SFT), pH, wettability alteration, and viscosity of the displacing phases were measured.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.059
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.005
GPT teacher head0.247
Teacher spread0.242 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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