Transient Stress Distribution and Failure Response of a Wellbore Drilled by a Periodic Load
Bibliographic record
Abstract
The poroelastodynamic failure of a wellbore due to periodic loading during drilling is an unsolved problem. The conventional poroelastic method to calculate the stress distribution around wellbore is for static loading cases and cannot be used for short-time dynamic-loading cases which result in wave propagation in the formation. This paper formulates a poroelastodynamic model to characterize dynamic stress and pressure wave due to periodic loadings and to analyze the transient failure of the suddenly drilled wellbore in a non-hydrostatic stress field. The fully coupled poroelastodynamic model was developed based on the equations of motion, fluid flow and constitutive equations to reflect stress and pressure waves that resulted from a periodic stress perturbation at the wellbore surface. The model was analytically solved by means of field expansions of the solutions, by performing a Laplace transform as well as some special techniques. Simulation results show that the pressure and stress responses inside the formation resemble a damped oscillator where the amplitude decays as the distance to wellbore increases. Especially the potential shear failure zone around the wellbore was computed and plotted. Influences of poroelastic parameters, in-situ stress and periodic load parameters on the shear failure responses were analyzed in a detailed parametric study, and the results provide fundamental insights into wellbore stability maintenance in different reservoirs.
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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 | 0.000 | 0.000 |
| 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".