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Record W3020998587 · doi:10.2118/198574-pa

Microscale Interactions of Surfactant and Polymer Chemicals at Crude Oil/Water Interface for Enhanced Oil Recovery

2020· article· en· W3020998587 on OpenAlexaff
Subhash Ayirala, Zuoli Li, Rubia Mariath, Abdulkareem M. AlSofi, Zhenghe Xu, Ali Yousef

Bibliographic record

VenueSPE Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMicroscale chemistrySurface tensionPulmonary surfactantRheometerChemical engineeringViscoelasticityEnhanced oil recoveryMaterials sciencePolymerRheologyBrineElastic modulusComposite materialChemistryOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

Summary The conventional experimental techniques used for performance evaluation of enhanced oil recovery (EOR) chemicals, such as polymers and surfactants, have been mostly limited to bulk viscosity, phase behavior/interfacial tension (IFT), and thermal stability measurements. Furthermore, fundamental studies exploring the different microscale interactions instigated by the EOR chemicals at the crude oil/water interface are scanty. The objective of this experimental study is to fill this existing knowledge gap and deliver an important understanding on underlying interfacial sciences and their potential implications for oil recovery in chemical EOR. Different microscale interactions of EOR chemicals, at crude oil/water interface, were studied by using a suite of experimental techniques, including an interfacial shear rheometer, Langmuir trough, and coalescence time measurement apparatus at both ambient (23°C) and elevated (70°C) temperatures. The reservoir crude oil and high-salinity injection water (57,000 ppm total dissolved solids) were used. Two chemicals, an amphoteric surfactant (at 1,000 ppm) and a sulfonated polyacrylamide polymer (at 500 and 700 ppm) were chosen because they are tolerant to high-salinity and high-temperature conditions. Interfacial viscous and elastic moduli (viscoelasticity), interface pressures, interface compression energies, and coalescence time between crude oil droplets are the major experimental data measured. Interfacial shear rheology results showed that surfactant favorably reduced the viscoelasticity of crude oil/water interface by decreasing the elastic and viscous modulus and increasing the phase angle to soften the interfacial film. Polymers in brine either alone or together with surfactant increased the viscous and elastic modulus and decreased the phase angle at the oil/water interface, thereby contributing to interfacial film rigidity. Interfacial pressures with polymers remained almost in the same order of magnitude as the high-salinity brine. In contrast, a significant reduction in interfacial pressures with surfactant was observed. The interface compression energies indicated the same trend and were reduced by approximately two orders of magnitude when surfactant was added to the brine. The surfactant was also able to retain similar interface behavior under compression even in the presence of polymers. The coalescence times between crude oil droplets were increased by polymers, while they were substantially decreased by the surfactant. These consistent findings from different experimental techniques demonstrated the adverse interactions of polymers at the crude oil/water interface to result in more rigid films, while confirming the high efficiency of the surfactant to soften the interfacial film, promote the oil droplets coalescence, and mobilize substantial amounts of residual oil in chemical EOR. This experimental study, for the first time, characterized the microscale interactions of surfactant-polymer chemicals at the crude oil/water interface. The applicability of several interfacial experimental techniques has been demonstrated to successfully understand underlying interfacial sciences and oil mobilization mechanisms in chemical EOR. These techniques and methods can provide potential means to efficiently screen and optimize EOR chemical formulations for better oil recovery in both sandstone and carbonate reservoirs.

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 score0.014
Threshold uncertainty score0.520

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 head0.011
GPT teacher head0.245
Teacher spread0.235 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

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