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Record W2028685156 · doi:10.2118/2000-094-ea

Mitigation of Harmonic Distortions in Oilfield Electrical Distribution Systems

2000· article· en· W2028685156 on OpenAlexaffabout
Wilsun Xu

Bibliographic record

VenueCanadian International Petroleum Conference · 2000
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHarmonicHarmonic analysisDistribution (mathematics)Petroleum engineeringComputer scienceEnvironmental scienceGeologyElectronic engineeringEngineeringAcousticsPhysicsMathematics

Abstract

fetched live from OpenAlex

Abstract Variable frequency drives (VFD) are increasingly being used in oil fields to operate pump jacks. Significant harmonic distortions are expected for such applications. Compared to traditional harmonic problems, the oil-field harmonic problem is quite unique since the harmonicproducing VFDs are scattered all over a field. It is the cumulative effect of individual sources that causes unacceptable harmonic distortion in a system. This paper presents a COURSE-sponsored project to develop methods for assessing the cumulative harmonic effect of distributed VFDs and for designing effective harmonic mitigation measures. Introduction Variable frequency drives (VFDs) are increasingly being used in oilfields due to their high efficiency and flexibility. A typical application is to drive the pump jack motors distributed across a field. For new oilfields or existing fields with expansions, a significant portion of the electric loads can be VFDs. This situation is particularly true in Alberta where many oilfield expansion projects are either in progress or to be pursued. VFDs are harmonic-producing loads, that is, they generate currents or voltages that have frequencies of multiples of 60Hz. A typical waveform of the current drawn by a VFD is shown in Figure 1. This harmonics polluted waveform is quite different from the sinusoidal waveform seen in normal electrical systems. The harmonic currents are very disruptive to the operation of variable speed drives and can damage sensitive electronic equipment connected in the system. They also cause electromagnetic interference with telecommunication and computer equipment. International and national standards have been established to limit harmonics in power systems and to define compatibility levels based on which electrical apparatuses are designed [1,2]. As a result, it is essential to reduce the harmonic distortion levels in oilfield distribution systems. A reliable and cost effective solution to this problem could mean sizable savings in investment costs, and reductions in production losses for Alberta's oil and gas industry. Unfortunately, there are no readily available solutions to this problem. Figure 1: Waveform of the current drawn by variable frequency drives. (Available in full paper) In response to industry needs, the COURSE program has approved a research project to undertake strategic research into this emerging problem. The objective is to determine the most reliable and cost-effective means to mitigate harmonic distortions in oilfield electrical systems. A guideline on the assessment and designing of harmonic filtering schemes will be developed. This paper provides an overview on the project and presents some related results 2. PROJECT OBJECTIVE AND SCOPE Harmonic distortion in electrical distribution systems is not a new phenomenon. Considerable knowledge has been accumulated over the past twenty years on the assessment and mitigation of harmonic distortions. What makes the oilfield harmonic problem unique is the distributed nature of the harmonic sources: the harmonicproducing VFDs are scattered all over a field. It is the cumulative effect of individual sources that causes unacceptable harmonic distortion in the system. How to assess the cumulative harmonic effect on the oilfield distribution systems and how to design appropriate mitigation measures is a new area of research. Central to this subject are the following two questions:

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 score0.323
Threshold uncertainty score0.993

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 head0.008
GPT teacher head0.205
Teacher spread0.197 · 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

Citations0
Published2000
Admission routes2
Has abstractyes

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