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Record W2165404391 · doi:10.1109/acc.2007.4282265

Modeling and Control of Three-Phase Gravilty Separators in Oil Production Facilities

2007· article· en· W2165404391 on OpenAlexafffund
Atalla F. Sayda, James Taylor

Bibliographic record

VenueProceedings of the ... American Control Conference/Proceedings of the American Control Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsUniversity of New Brunswick
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaAtlantic Canada Opportunities AgencyCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCape Breton University
KeywordsSeparator (oil production)PetroleumProcess engineeringMathematical modelComputer sciencePetroleum engineeringSimulationEngineeringChemistry

Abstract

fetched live from OpenAlex

Oil production facilities exhibit complex and challenging dynamic behavior. A dynamic mathematical modeling study was done to address the tasks of design, control and optimization of such facilities. The focus of this paper is on the three-phase separator, where each phase's dynamics are modeled. The hydrodynamics of liquid-liquid separation are modeled based on the American Petroleum Institute design criteria. Given some simplifying assumptions, the oil and gas phases' dynamic behaviors are modeled assuming vapor-liquid phase equilibrium at the oil surface. In order to validate the developed mathematical model, an oil production facility simulation was designed and implemented based on such models. The simulation model consists of a two-phase separator followed by a three-phase separator. An upset in the oil component of the incoming oil-well stream is introduced to analyze its effect of the different process variables and produced oil quality. The simulation results demonstrate the sophistication of the model in spite of its simplicity.

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: none
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.264
Teacher spread0.246 · 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

Citations62
Published2007
Admission routes2
Has abstractyes

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