Technical Difficulties and Countermeasures of Drilling of Φ118mm Sidetracking Horizontal Well in Changqing Oilfield
Bibliographic record
Abstract
The boreholes of the horizontal side-drilled wells with casing windows in Changqing Oilfield are all Φ118mm. Difficulties in the construction of small-hole drilling include high landing risk in the horizontal section, difficulty in slope prediction and trajectory control, and limited extension capacity of small wellbore. By optimizing the trajectory of the borehole, designing the trajectory adjustment section before the horizontal landing well, and introducing the equilibrium trend angle method to predict the slope of the directional tool, we improved the trajectory control ability; by calculating the stability of the drill string and the loss of cyclic pressure and analyzing the displacement extension ability, we optimized drill string selection and formed a precise trajectory control method based on sidetrack horizontal well trajectory optimization. Based on the analysis of displacement and extension ability, a non-standard drill pipe with a large diameter of 88.9mm and a small hydrophthalmia was selected. It is considered that the technical countermeasures and suggestions in this paper are of good reference and guiding significance for the development of sidetracked horizontal wells drilling in Changqing Oilfield.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".