Stress-Corrosion Cracking as an Alternative Time-Dependent Shale-Stability Model
Bibliographic record
Abstract
Summary Wellbore stability in shale has been a crucial issue for drilling in all kinds of environments. The analysis of time-dependent wellbore stability in shales has largely concentrated on the influence of fluid chemistry and filtrate invasion into the formation to predict compressive failure using poroelasticity and continuum models. This paper presents another possible mechanism for time-dependent behavior—stress-corrosion cracking (subcritical crack growth). Using the discrete-element method (DEM) to simulate grainscale processes, we apply the concept of time-dependent cracking to hole enlargement for vertical wellbores. We use a published example from the North Sea to verify the stress-corrosion model and demonstrate the application to wellbore stability in shale. Laboratory results on rocks indicate a wide range of susceptibility to stress-corrosion cracking related to rock petrology and contact-fluid chemistry. Using laboratory calibrated rock properties, we run 2D, plane-strain simulations of vertical-wellbore stability in shale, where hole enlargement is tracked through time. As a result of stress-corrosion cracking, the numerical models show a time-dependent failure history, with an initial stable period of varying duration (influenced by mud weight, rock properties, and in-situ stress), followed by a brief period of combined shear and tensile failure, and ending with stabilization at an enlarged, elliptically shaped geometry. Time to failure increases with increasing mud weight. Enlarged-hole shape changes from elliptical to roughly circular with decreasing stress anisotropy. These behaviors simulated by the stress-corrosion model coincide with previously reported field experience. This new modeling approach for time-dependent wellbore failure can be readily constrained with straight forward fracture-mechanics tests on rock samples and has the potential to also be applied to time-dependent, intermittent sand or fines generation during production.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.000 | 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".