Numerical Modelling of Fold-Related Fractures
Bibliographic record
Abstract
Fractures induced by folds are pivotal in hydrocarbon exploration, ground water transport and harnessing of geothermal energy. This is because of the need to predict and understand fracture propagation in reservoirs which have folded rock formations. Despite its prominence, there is a lack of reliable numerical models for simulating fractures resulting from rock folding. This is partially due to the difficulty involved in fracture modelling. As a contribution to fold-fracture modelling, this work applies a coupled plasticity-damage model to rock fracturing and anticlinal folds. Parametric studies on a single folded layer give insight into the fold formation and behaviour. The anisotropic continuum damage model which considers both tension and compression is formulated using the power damage evolution law. For ease in formulation, strain equivalence hypothesis is adopted whereby the strain is the same for both damaged and undamaged configurations. Lubliner plasticity yield criterion is adopted for plastic deformation. The model is coded in Abaqus user subroutine UMAT and is applicable to quasi-brittle materials. © 2015 by the Canadian Institute of Mining.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".