A Novel Model of Brittleness Index for Shale Gas Reservoirs: Confining Pressure Effect
Bibliographic record
Abstract
Abstract Brittleness indices (BI) commonly used in the petroleum industry are based on elastic modulus or mineralogy that can be calculated from well logs. However, they both ignore the effect of confining pressure. Shale is usually distributed at different depth under different confining pressure. Models without considering the influence of confining pressure will directly lead to inaccuracy in BI calculation, thus resulting in the failure of hydraulic fracturing. In this work, we compared confining pressure with rock mechanics parameters and the microcrack quantity of a core, introduced "fracture toughness" to explain how confining pressure influences BI, and finally developed a new model to correct the effect of confining pressure in BI calculation. Fracture toughness is an important parameter that characterizing a rock’s resistance to a fracture. It increases with confining pressure, since an increase of confining pressure may close preexisting cracks and restrict the crack propagation. The results show that BI is usually larger at low confining pressure than at high pressure. Also, higher content in brittle mineral does not necessarily mean brittler. The results calculated by the new model, which considers the influence of Young’s modulus, Poisson’s ratio, tensile strength, confining pressure and fracture toughness in BI calculation, match well with experimental results.
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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 | 0.000 |
| 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".