Wellbore Stability in Interbedded Weak Formations Utilizing a Shear-Based Method: Numerical Realization and Analysis
Bibliographic record
Abstract
This study employs a finite element approach to investigate wellbore stability in interbedded weak formations, such as unconsolidated layers, with a focus on the failure-tendency method, which is derived according to the principle of Mohr–Coulomb theory. The numerical model is successfully verified through analytical solutions for stress distributions around a borehole. Through finite element modeling, the method captures critical shear failure thresholds, exemplifying how variations in horizontal stress anisotropy, orientation of interbedded weak layers, and mechanical properties of layered geological formations impact wellbore stability in stratified formations. Results indicate that the potential unstable regions, aligned in the direction of minimum principal stress, and the range of unstable regions gradually enlarge as the internal cohesive strength decreases. By modeling heterogeneous rock sequences with explicit representation of interbedded weak layers and stress anisotropy, the analysis reveals that interbedded weak layers are prone to shear-driven borehole breakouts due to stress redistribution and relatively lower internal cohesive strength. As compressive stresses concentrate at interfaces between stiff and compliant layers, breakouts are induced at those weak layers along the interfaces; this type of failure is also manifested through a field borehole breakout observation. Simulation results reveal the significant influences of the mechanical properties of layered formations and in situ stress on the distribution of instability regions around a borehole. The study underscores the necessity of layer-specific geomechanical models to predict shear failure in complex layered geological formations and offers insights for optimizing drilling parameters to enhance wellbore stability in anisotropic, stratified subsurface environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".