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Record W4412569536 · doi:10.1115/1.4069212

Lateral Vibration Characteristics Analysis and Vibration Mode Study of Drill String in Deep Horizontal Well

2025· article· en· W4412569536 on OpenAlexaff
Jialin Tian, Guoqing Xiao, Liming Dai

Bibliographic record

VenueJournal of Computational and Nonlinear Dynamics · 2025
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsVibrationDrill stringStructural engineeringMode (computer interface)Normal modeGeologyAcousticsDrillEngineeringPhysicsMaterials scienceComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

Abstract This study examines lateral drill string vibrations under factors including preload torque, rotational inertia, and fluid density. Theoretical models analyze dynamic characteristics, vibration frequencies, and critical loads (Tcr), with experimental validation. Key findings reveal drill string length, drilling fluid density, and external loads critically influence lateral vibration frequencies. When string length is below 1500 m, vibration frequencies decrease sharply, with a marked reduction in decay rate beyond this threshold. Increased fluid density further reduces frequencies. Boundary condition variations alter load-bearing capacity and induce mode transitions between stable sinusoidal buckling and helical buckling. Analyses of transverse displacements, phase diagrams, and Poincare maps demonstrate system instability near critical loads (T ≈ Tcr), where steady-states transition to severe sinusoidal buckling vibrations. At T > Tcr, lateral vibrations exhibit 0.5 s periodic behavior, evolving from sinusoidal to helical buckling with quasi-periodic chaotic features. Phase diagrams reveal periodic convergence, annular motion regions, and attractors, indicating multiperiodic bifurcations between stability and chaos. Notably, the transition from nonperiodic to quasi-periodic motion highlights the system's sensitivity to load thresholds. These results provide insights into vibration mitigation strategies by clarifying relationships between operational parameters (length, fluid density, torque) and dynamic responses. The identified buckling phase transitions and chaotic patterns enhance predictive capabilities for drill string failure prevention under complex downhole conditions.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.312
Threshold uncertainty score0.330

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 head0.003
GPT teacher head0.211
Teacher spread0.208 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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