The effect of weight on bit on the contact behavior of drillstring and wellbore
Bibliographic record
Abstract
The contact behavior of drillstring and wellbore is of great concern to drilling companies in the oil and mineral exploration industries. Due to the nonlinear, random motion of the drillstring in contact with the wellbore, it is difficult to predict the response of the drillstring. Successive contacts of wellbore and drillstring will result in fatigue failure and inhibit vibration-assisted rotary drilling mechanisms. Transverse vibration of a drillstring under a range of axial loads is studied in this paper. The impact of drill collars with the wellbore is modeled using Hertzian contact theory. The drillstring is treated as a simply supported Euler-Bernoulli beam under axial load, or "weight-on-bit" (WOB). Natural frequencies were generated analytically using the assumed modes method and a bond graph model was generated. Extracting the motion of the contact point on the drill collar, which is at a known axial location, is easily done with modal bond graphs. The effect of WOB on the behavior of drill collar motion near the wellbore is studied, and the expected random, nonlinear behavior of the drillstring at the contact point is demonstrated and discussed. This work illustrates the advantages of the bond graph method to the drilling community, in which bond graphs are currently an underutilized technique.
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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 | 0.002 |
| 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".