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Record W1989228816 · doi:10.1002/aic.12800

Modeling of asphaltene deposition in a production tubing

2011· article· en· W1989228816 on OpenAlexaff
Dmitry Eskin, John Ratulowski, Kamran Akbarzadeh, Simon Ivar Andersen

Bibliographic record

VenueAIChE Journal · 2011
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsSchlumberger (Canada)
Fundersnot available
KeywordsAsphalteneDeposition (geology)Petroleum engineeringOil productionCylinderCouette flowOil fieldMaterials scienceMechanicsChemical engineeringChemistryEngineeringGeologyMechanical engineeringPhysicsFlow (mathematics)

Abstract

fetched live from OpenAlex

Abstract Asphaltene deposition phenomena are investigated both theoretically and experimentally. A Couette device, where the inner cylinder rotates and particles deposit on the outer wall, is used for deposition laboratory studies. A deposition modeling approach, recently proposed by the authors is improved. Empirical parameters of the model are obtained from Couette device experiments. The deposition mechanism peculiarities are explained based on an analogy between the deposition and water in oil emulsion stabilization by asphaltenes, and on an analysis of interaction of asphaltene molecules. The model performance is illustrated by modeling oil production, accompanied with asphaltene deposition, from a cylindrical reservoir through vertical tubing. The computations, performed for a reservoir depleting over time, demonstrate a good qualitative agreement with the field data reported in literature. © 2011 American Institute of Chemical Engineers AIChE J, 2012

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 score0.007
Threshold uncertainty score0.014

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 studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.241
Teacher spread0.211 · 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

Citations43
Published2011
Admission routes1
Has abstractyes

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