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Record W4414510397 · doi:10.3390/pr13103067

Insights into Foamy Oil Phenomenon in Porous Media: Experimental and Numerical Investigation

2025· article· en· W4414510397 on OpenAlexaff
Morteza Sabeti, Farshid Torabi, Ali Cheperli

Bibliographic record

VenueProcesses · 2025
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsPorosityPorous mediumBubbleSaturation (graph theory)Bubble pointEnhanced oil recoveryNucleationVolume (thermodynamics)

Abstract

fetched live from OpenAlex

Cyclic Solvent Injection (CSI) is a method for enhanced heavy oil recovery, offering a reduced environmental impact. CSI processes typically involve fluid flow through both wormholes and the surrounding porous media in reservoirs. Therefore, understanding how foamy oil behavior differs between bulk phases and porous media is crucial for optimizing CSI operations. However, despite CSI’s advantages, limited research has explained why foamy oil, a key mechanism in CSI, displays weaker strength and stability in bulk phases than in porous media. To address this gap, three advanced visual micromodels were employed to monitor bubble behavior from nucleation through collapse under varying porosity with a constant pressure reduction. A sandpack depletion test in a large cylindrical model further validated the non-equilibrium bubble-reaction kinetics observed in the micromodels. Experiments showed that, under equivalent operating conditions, bubble nucleation in porous media required less energy and initiated more rapidly than in a bulk phase. Micromodels with lower porosity demonstrated up to a 2.5-fold increase in foamy oil volume expansion and higher bubble stability. Moreover, oil production in the sandpack declined sharply at pressures below 1800 kPa, indicating the onset of critical gas saturation, and yielded a maximum recovery of 37% of the original oil in place. These findings suggest that maintaining reservoir pressure above critical gas saturation pressure enhances oil recovery performance during CSI operations.

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 score0.341
Threshold uncertainty score0.448

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 head0.007
GPT teacher head0.234
Teacher spread0.227 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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