Advantages of an LQR Controller for Stick-Slip and Bit-Bounce Mitigation in an Oilwell Drillstring
Bibliographic record
Abstract
Failure of oilwell drillstrings is very costly in terms of money and time. There are many reasons for drillstring failure, such as vibration, fatigue, and buckling. Stick-slip vibration has received considerable attention in recent years with increasing use of polycrystalline diamond compact (PDC) bits in harder formations, and has motivated extensive research on this type of drillstring vibration. This paper addresses the advantages of a linear quadratic regulator (LQR) controller, compared to a spring-damper isolator, for stick-slip and bit-bounce mitigation in an oilwell drillstring. A bond graph model of a drillstring has been used for simulation that predicts axial vibration, torsional vibration, and coupling between axial and torsional vibration due to bit-rock interaction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".