Optimizing a Deepwater Subsalt Drilling Program by Evaluating Anisotropic Rock Strength Effects on Wellbore Stability and Near-Wellbore Stress Effects on the Fracture Gradient
Bibliographic record
Abstract
Abstract An understanding of geomechanics can save millions of dollars in drilling costs by reducing the likelihood of poor borehole conditions, stuck pipe and lost circulation. Basic wellbore stability modeling has been successful in the past, but may prove inadequate in some cases because the mechanism of borehole failure and characterization of fracturing is not sufficiently addressed. In these cases, a more complex geomechanical model is required. We describe an example where a complex geomechanical model was applied to address anisotropic wellbore failure due to weakly bedded rocks, and lost circulation due to equivalent annular mud weights in excess of near and far field stresses. This same model was then used to predict mud weights that should mitigate problems in future wellbores.
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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) | 0.001 | 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 | 0.001 |
| 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".