The In-Situ Stress Analysis of Casing Damage Wells in the Sixth Middle District Based on Kriging Interpolation Method
Bibliographic record
Abstract
Casing damage is a common engineering problem, the causes of which mainly include two aspects: geological factors and engineering factors. In this paper, the application of the data of logging and hydraulic fracturing gives the calculation model of stress in three directions in the sixth middle district, and have an interpolation calculation on the in-situ stress data in the casing damage wells based on the Kriging interpolation method, and then have a study on the casing damage problems of the sixth middle district in Karamay oil field from the perspective of the in-situ stress. The results show that: the triangular nose anticlinal structure of the sixth middle district which is influenced by tectonic stress obviously is typical non-uniform loading zone; the horizontal stress is the biggest, the ratio of the two horizontal stress is 1.58, which is the major cause of the casing diameter shrinkage. According to the characteristics of the horizontal stress which is too big and the non-uniform load, it is proposed to abandon the conventional design methods of casing string in uniform load, using the non-uniform loading conditions to design, which lays the foundation for secure and stable development of the sixth middle district reservoir.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".