Design and dynamic characteristics of automatic vertical drilling tool
Bibliographic record
Abstract
Higher performance is needed in deeper and longer horizontal wellbore drilling. In vertical drilling conditions, wellbore trajectory often be led to deviation due to objective conditions. Based on the engineering issues, this paper presents a new automatic vertical drilling tool, including the innovative design and working mechanism research. This tool working mechanism are carried out, such as the mechanics model of eccentric tube and the relationships between eccentric torque and deflection angle. The eccentric tube torque increases with the wellbore deviation angle. When wellbore deviation angle is constant, the eccentric tube torque reaches maximum value when its deflection angle is 90°. The internal flow parameters are studied by fluid field simulation, such as drilling fluid flow rate, pressure drop, and pressure distribution inside this tool during downhole drilling process. The larger the diameter of switch hole, the higher is the pressure drop around, which leads to the force on push block increasing. The drilling fluid pressure increases with higher input flow rate inside this tool. The comparison of results, the data of simulation and theoretical model calculations, verified the reliability and accuracy of research. This study has provided innovative ideas and reference for drilling tool design and wellbore trajectory control methods.
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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 | 0.000 |
| Open science | 0.001 | 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".