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Record W2587604122 · doi:10.3968/8953

Mechanisms and Application for Hydraulic Pulsed Cavitating Jet Generator

2016· article· en· W2587604122 on OpenAlexvenueno aff
Hongna Qu, Gensheng Li, Dongxing Jiang

Bibliographic record

VenueAdvances in petroleum exploration and development · 2016
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCavitationRate of penetrationNozzleDrillingJet (fluid)Drilling fluidMaterials sciencePenetration (warfare)Mechanical engineeringPetroleum engineeringMechanicsEngineeringPhysics

Abstract

fetched live from OpenAlex

To improve the rate of penetration (ROP) further, based on analysis of the jet modulating mechanism, a new drilling tool is designed which couples the advantages of both pulsed jet and cavitating jet. When drilling fluid flows through the tool in drilling process, the fluid is modulated to pulsed and cavitating jet by impellers and in self-resonant chamber. Thus, pulsed cavitating jet is formed at the outlet of the bit nozzle. Because of jet pulsation, cavitating erosion and local negative pressure effect, bottom cuttings cleaning efficiency is enhanced and the ROP is improved. The hydraulic pulsed cavitating jet generator has been applied in 8 oil fields and more than 100 wells in China. The results indicated that the maximum density of test drilling fluid was 1.70 g/cm 3 , the maximum test well depth was 6,162 m. The generator could work over 230 h, and the maximum operation time was above 520 h. As the result, the average ROP had been increased by 10.1% to 104.4%. The generator has the characteristics of simple structure and long operation time, and has a well adaptability to the existing drilling equipments, technological parameters, which provides a safe and efficient new drilling technology for deep 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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score0.305

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 communication0.0000.001
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 head0.010
GPT teacher head0.236
Teacher spread0.226 · 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 designOther design
Domainnot available
GenreMethods

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
Published2016
Admission routes1
Has abstractyes

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