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Record W1995669821 · doi:10.2118/06-11-07

Evolution of Foamed Gel Confined in Pore Network Models

2006· article· en· W1995669821 on OpenAlexafffund
Laura Romero‐Zerón, Apostolos Kantzas

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of New Brunswick
FundersCanada Research Chairs
KeywordsPorous mediumMaterials scienceMicromodelPorosityBubbleWettingPetroleum engineeringAir bubbleComposite materialGeologyComputer science

Abstract

fetched live from OpenAlex

Abstract Conventional foams and foamed gels present a variety of relevant properties that make them suitable for use in the oil and gas sector. Some applications include drilling operations, CO2 foam injection, steam foam, foam-assisted water alternate gas (WAG), and gas shut-off techniques to control excessive gas production in oil wells. Foamed gels have also demonstrated great potential as gas and liquid diverting fluids. Furthermore, foam systems can be injected into rock formations as an important means for CO2 and green gases recycling. In foamed gel applications, an issue of particular interest is understanding the evolution of partially gelled foam bubbles confined in porous media. This is significant because after foamed gel placement in porous media, the pore level configuration of the gelled lamellar structure determines the fluid diverting performance of mature foamed gel barriers. This paper reports the experimental results of a pore level visualization study conducted to evaluate the evolution of foamed gel after placement in porous media as a function of aging time. In addition, the experiments assisted in the examination of the effect of rock wettability, foamed gel texture, type of gas used for foamed gel formulation, and type of oil that saturates the porous media and how these play on the evolution of the confined foamed gel. Etched-glass micromodels and Helle-Shaw cells were used to visualize the growth of foamed gel bubbles as a function of time. Through image analysis, changes in bubble sizes were quantified and statistically analyzed. Laboratory evidence indicates that right after immature foamed gel placement in etched-glass micromodels, significant changes in bubble size occur. After the first 20 hours of foamed gel placement inside the pore network model, bubble growth levels off. The lamellar structure in the micromodel reaches a stable configuration, which remains steady for an indefinite period if external instabilities are absent. Quite the opposite was observed when the same foamed gel was placed in a Helle-Shaw cell. In this case, due to the absence of geometric restrictions, homogeneous bubble shapes and rapid bubble growth were observed. The experimental results demonstrated that porous media wettability, foamed gel texture, the type of gas used for foamed gel production, and the type of oil that saturates the pore models significantly influence the evolution of foamed gel confined in porous media. Introduction In spite of the well known limitations of etched-glass micromodels and Helle-Shaw cells in representing reservoir rocks(1–3), if the visual observations of pore level behaviour are conducted away from the model boundaries, the underlying capillary phenomena do represent those occurring in reservoir media(3). Thus, micromodels facilitate the direct visualization of fluid interfaces movement, making it possible to gather qualitative and semi-quantitative information of foam propagation in porous media, especially on the specific mechanism of foam performance under practical physical situations(1). This explains why the current accepted theories on foam flow have been largely assembled on the basis of pore model observations(4).

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.172
Teacher spread0.168 · 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 designSimulation or modeling
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

Citations10
Published2006
Admission routes2
Has abstractyes

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