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Record W1647719711 · doi:10.1109/icps.2015.7266427

Downhole monitoring tool design using power line disturbances

2015· article· en· W1647719711 on OpenAlexaff
Xiaodong Liang, Wilsun Xu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWellheadEngineeringSubmersible pumpLine (geometry)SIGNAL (programming language)Power (physics)Sensitivity (control systems)Automotive engineeringElectronic engineeringComputer scienceMarine engineeringMechanical engineering

Abstract

fetched live from OpenAlex

The downhole monitoring tool is a critical component in electrical submersible pump (ESP) wells to monitor downhole parameters such as the pump intake pressure, the temperature of motor winding and oil reservoir, the motor vibration etc. to ensure proper ESP system operation and to optimize production. In this paper, a downhole monitoring tool design method is proposed using power line disturbances. This method is based on the technology of two-way automatic communication system (TWACS). The AC current signal is used for the downhole tool. This new design scheme utilizes an external impedance connecting one phase of the ESP system to the ground on the wellhead, and a controlled thyrsitor connected between the neutral of the ESP motor and the ground by conducting at a specific firing angle and cycles. This design can overcome the impact of single-line-to-ground faults of the ESP system on the communication of downhole tools. The design method is verified through the simulation using PSCAD by case and sensitivity studies. The lab testing is conducted to further validate the effectiveness of the proposed design method.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.304

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 head0.070
GPT teacher head0.270
Teacher spread0.200 · 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 designBench or experimental
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

Citations3
Published2015
Admission routes1
Has abstractyes

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