Experimental Study on Axial Impact Mitigating Stick‐Slip Vibration with a PDC Bit
Bibliographic record
Abstract
Stick‐slip vibration reduces the drilling rate of penetration, causes early wear of bits, and threatens the safety of downhole tools. Therefore, it is necessary to study suppression methods of stick‐slip vibration to achieve efficient and safe drilling. Field tests show that the use of downhole axial impactors is helpful to mitigate stick‐slip vibration and improve rock‐breaking efficiency. However, there are many deficiencies in the study of how axial impact load affects stick‐slip vibration of a PDC bit. In this paper, based on the two‐degrees‐of‐freedom spring‐mass‐damper model and similarity theory, a laboratory experiment device for suppressing stick‐slip vibration of a PDC bit under axial impact load has been developed, and systematic experimental research has been carried out. The results show that the axial impact force can suppress the stick‐slip vibration by reducing the amplitude of weight on bit and torque fluctuations and by increasing the main frequency of torque. The amplitude of impact force affects the choice of the optimal back‐rake angle. The impact frequency is negatively correlated with the fluctuation amplitude of the rotary speed. When the impact frequency is greater than 100 Hz, the fluctuation amplitude of the rotary speed will not decrease.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".