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Record W2156332696 · doi:10.2118/80139-ms

Modeling Sand Production and Erosion Growth under Combined Axial and Radial Flow

2002· article· en· W2156332696 on OpenAlexaff
Richard Wan, Jin Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBody orificePorosityErosionGeotechnical engineeringCylinderMechanicsFlow (mathematics)GeologyPorous mediumOil productionMaterials sciencePetroleum engineeringEngineeringPhysicsMechanical engineeringGeomorphology

Abstract

fetched live from OpenAlex

Abstract The paper investigates the phenomenon of sand production in both axial and radial flow conditions using a coupled particle erosion-fluid transport-stress model that has been developed recently by the authors. We first examine sand production and wormhole growth in a sand pack as heavy oil is being drawn from it through a small orifice. Numerical results are in close agreement with experimental data available for the sand pack experiment. In particular, the computed porosity field and its temporal evolution during wormhole propagation match very well with available CT scan images of the sand pack. Then, we model a sand production hollow cylinder test in which sand is being produced under combined axial and radial flow of light oil in a sandstone specimen. Aspects such as sand flux and porosity evolutions, as well as erosion growth around the inner wall of the cylinder are investigated using the numerical model.

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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.186
Teacher spread0.175 · 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

Citations5
Published2002
Admission routes1
Has abstractyes

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