Torsional Vibrations and Nonlinear Dynamic Characteristics of Drill Strings and Stick-Slip Reduction Mechanism
Bibliographic record
Abstract
Torsional stick–slip vibrations easily occur when the drill bit encounters a hard or a hard-soft staggered formation during drilling process. Moreover, serious stick–slip vibrations of the drill string is the main factor leading to low drilling efficiency or even causing the downhole tools failure. Therefore, establishing the stick–slip theoretical model, which is more consistent with the actual field conditions, is the key point for new drilling technology. Based on this, a new torsional vibration tool is proposed in this paper, then the multidegree-of-freedom torsional vibrations model and nonlinear dynamic model of the drill string are established. Combined with the actual working conditions in the drilling process, the stick–slip reduction mechanism of the drill string is studied. The research results show that the higher rotational speed of the top drive, smaller viscous damping of the drill bit, and smaller WOB (weight on bit) will prevent the stick–slip vibration to happen. Moreover, the new torsional vibration tool has excellent stick–slip reduction effect. The research results and the model established in this paper can provide important references for reducing the stick–slip vibrations of the drill string and improving the rock-breaking efficiency.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".