Thermoporoelastoplastic Wellbore Breakout Modeling by Finite Element Method
Bibliographic record
Abstract
Drilling a hole into rock results in stress concentration and redistribution close to the hole. When induced stresses exceed the rock strength, wellbore breakouts will happen. Research on wellbore breakout is the fundamental of wellbore stability. A wellbore breakout is a sequence of stress concentrations, rock falling, and stress redistributions, which involve initiation, propagation, and stabilization sequences. Therefore, simulating the process of a breakout is very challenging. Thermoporoelastoplastic models for wellbore breakout analysis are rare due to the high complexity of the problem. In this paper, a fully coupled thermoporoelastoplastic finite element model is built to study the mechanism of wellbore breakouts. The process of wellbore breakouts, the influence of temperature and the comparison between thermoporoelastic and thermoporoelastoplastic models are studied in the paper. For the finite element modeling, the D-P criterion is used to determine whether rock starts to yield or not, and the maximum tensile strain criterion is used to determine whether breakouts have happened.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".