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Record W1986811279 · doi:10.2118/135994-ms

A Saskatchewan Field Trial to Better Understand Downhole Dynamics of PCP Systems

2010· article· en· W1986811279 on OpenAlexaffabout
Shauna Noonan, Daine Studer, P. Skoczylas

Bibliographic record

VenueAll Days · 2010
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsConocoPhillips (Canada)
FundersConocoPhillips
KeywordsStatorTorsion (gastropod)Rotor (electric)Field (mathematics)String (physics)Interference (communication)Computer scienceEngineeringMechanical engineeringMarine engineeringControl theory (sociology)PhysicsTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

Abstract This paper presents the results of a field trial conducted in Saskatchewan, Canada to investigate drive string dynamics between conventional and continuous rod and the impact of interference fit between rotor and stator in progressing cavity pumps (PCP). In August 2009, a well was completed with a downhole monitoring system and a PCP driven by a continuous rod string. At the same time, a second well was completed with a downhole monitoring system and a PCP driven by a conventional rod string. The pumps were identical with the exception of the interference fit of the rotor in the elastomeric stator. Thousands of data values were collected over a period of several months and evaluated to better understand rod stretch, torsion, and axial movement during start-up, shut-down and normal operating conditions and how these values change as a function of the interference fit of the pump itself. While the data evaluation did provide answers to help ConocoPhillips improve their PCP operations, there were even more questions generated that will prove thought-provoking to the industry and stir some great discussion.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.546
Threshold uncertainty score0.903

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.222
Teacher spread0.213 · 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 designObservational
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

Citations0
Published2010
Admission routes2
Has abstractyes

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