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Record W1910748443 · doi:10.1007/s11743-015-1692-8

Complexation of Surfactant/β‐Cyclodextrin to Inhibit Surfactant Adsorption onto Sand, Kaolin, and Shale for Applications in Enhanced Oil Recovery Processes. Part III: Oil Displacement Evaluation

2015· article· en· W1910748443 on OpenAlexafffund
Sirinthip Kittisrisawai, Laura Romero‐Zerón

Bibliographic record

VenueJournal of Surfactants and Detergents · 2015
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaMahidol UniversityCanada Foundation for InnovationUniversity of New Brunswick
KeywordsPulmonary surfactantChemistryEnhanced oil recoveryResidual oilAdsorptionOil in placeChemical engineeringOil shaleChromatographyPorous mediumPetroleum engineeringPorosityPetroleumOrganic chemistryWaste managementGeology

Abstract

fetched live from OpenAlex

Abstract This proof of concept research evaluates the performance of a surfactant/β‐cyclodextrin (β‐CD) inclusion complex during chemical flooding for enhanced oil recovery. It was hypothesized that the encapsulated surfactant propagates well through the porous media. Sodium dodecyl sulfate (SDS) was used to study the surfactant/β‐CD complexations. Phase behavior analysis was carried out to prepare the most favorable chemical slug formulation. A series of core flooding tests were conducted to determine the efficiency of the SDS/β‐CD inclusion complex in displacing residual oil. Surfactant flooding was conducted as tertiary oil recovery mode (after mature water flooding) by injecting 0.3 pore volume (PV) of the optimum surfactant slug that was chased by 0.3 PV of a polymer slug; followed by continuous water flooding until oil production stopped. The experimental results indicate that the encapsulated surfactant propagates well through the sandpack system and consistently produces higher incremental oil recoveries that range from 40 to 82 % over the incremental oil recovery achieved by conventional surfactant flooding.

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)0.000
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 score0.209
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.037
GPT teacher head0.288
Teacher spread0.252 · 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

Citations6
Published2015
Admission routes2
Has abstractyes

Explore more

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