Estimating the Critical Velocity of the Incipient Motion of Particles on the Cuttings Bed Surface: An Experimental and Theoretical Analysis
Bibliographic record
Abstract
During the drilling of highly deviated and horizontal wells, a pump shutdown causes drill cuttings to settle and form a cuttings bed in the annulus. This study investigated the incipient motion law of the particles on the cuttings bed surface when the drilling fluid starts circulating again. This work could help field engineers to determine a reasonable incipient pump displacement to improve hole-cleaning efficiency. In this study, the effects of the well inclination angle, cuttings size, and different cuttings densities on the critical velocity of particle motion are analyzed experimentally, using a large-scale flow loop. Next, based on a stress analysis of the particles on the cutting bed surface and on the boundary layer flow around the particles, an analytical formula for the surface shear force of the drilling fluid on particles is derived and a critical velocity model for incipient motion is established. Verification is then carried out and combined with the experimental results. This study has important implications for the design of drilling operations and for the management of cuttings transport in oil and gas wells. It can guide the setting and prediction of pump discharge to improve hole-cleaning 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".