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Record W2007424551 · doi:10.2118/159593-ms

Modeling and Dynamical Analysis of the Wave Equation of Sucker-Rod Pumping System

2012· article· en· W2007424551 on OpenAlexaff
Yu Yang, Jeff Watson, Stevan Dubljević

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2012
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPartial differential equationSucker rodMathematical analysisDifferential equationFourier seriesWave equationMathematicsTruncation (statistics)Ordinary differential equationControl theory (sociology)Boundary value problemComputer scienceEngineering

Abstract

fetched live from OpenAlex

Abstract The use of sucker-rod pumping systems is the most common method of artificial lift in the oil-well industry. In this work, the viscous-damped-wave equation model has been developed to describe the rod-string dynamical behavior at various well depths utilizing the inputs of load and position originating from the surface-card measurement. In contrast to the existing solutions of viscous-damped-wave equation dynamics, which is based on Fourier series truncation and finite difference method, in this paper a novel technique is presented and utilized in the real time estimation framework. In particular, an infinite-differential state space representation of the viscous-damped-wave equation dynamics is developed based on appropriate boundary transformation. The spectral decomposition and truncation of an infinite number of modes is realized, so that the partial differential equation model is cast to the system of coupled ordinary differential equations, which can be solved in real time and utilized for period and non-periodic motion stroke. Finally, the new method is validated by the real case study associated with the existing well.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.865
Threshold uncertainty score0.256

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 head0.028
GPT teacher head0.242
Teacher spread0.214 · 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 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
Published2012
Admission routes1
Has abstractyes

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