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Record W4391839036 · doi:10.1021/acs.langmuir.3c03203

A Feasibility Study on Enhanced Oil Recovery of Modified Janus Nano Calcium Carbonate-Assisted Alkyl Polyglycoside to Form Nanofluids in Emulsification Flooding

2024· article· en· W4391839036 on OpenAlexaff
Kaiping Tian, Wanfen Pu, Qianlong Wang, Mengke Xie, Dongdong Wang, Muming Wang, Shun Liu

Bibliographic record

VenueLangmuir · 2024
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
FundersMinistry of Science and Higher Education of the Russian FederationNational Natural Science Foundation of China
KeywordsEmulsionSurface tensionMaterials scienceChemical engineeringViscosityCalcium carbonateKeroseneNanofluidComposite materialChemistryNanoparticleOrganic chemistryNanotechnology

Abstract

fetched live from OpenAlex

Emulsification flooding can effectively enhance crude oil recovery to solve the problem of petroleum shortage. In this work, a modified Janus Nano Calcium carbonate (JNC-12) with a particle size of 30–150 nm was synthesized, and an in situ emulsification nanofluid (ISEN) was prepared with JNC-12 and alkyl polyglycoside (APG). Scanning electron microscope (SEM) showed that the dispersion of JNC-12 in air or APG solution was better than Nano Calcium carbonate (Nano CaCO 3 ). The emulsification properties, interfacial tension, and expansion modulus of ISEN were studied, and the result showed that with the increase in salinity, the emulsification rate decreased, the water yield rate increased, the interfacial tension first decreased and then increased, and the expansion modulus first increased and then decreased. With the increase in temperature, the emulsification rate, emulsion viscosity, and interfacial tension decreased. With the increased oil–water volume, the water yield rate and the emulsion viscosity increased. With increase in the concentration of JNC-12, the water yield rate, the emulsion viscosity, and the interfacial tension decreased but the expansion modulus increased. The emulsion generated by emulsifying ISEN with crude oil was an O/W emulsion, the crude oil viscosity was 4–10 times that of emulsion, and the average particle size of emulsion was 1.107 μm. The addition of ISEN caused the decrease in interfacial tension of oil–water to 0.01–0.1 mN/m. The wettability alteration experiment found that ISEN could change the lipophilic rock to hydrophilic rock. Finally, the core displacement experiments showed that compared with the first water flooding, the oil recovery of the second water flooding after ISEN flooding enhanced by 17.6%. This research has important guiding significance for in situ emulsified nanofluid flooding to enhance 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.034
GPT teacher head0.297
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), 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

Citations15
Published2024
Admission routes1
Has abstractyes

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