The effect of mineral composition and rock fabric on brittleness index: an example using the Montney Formation, Canada
Bibliographic record
Abstract
This study deals with brittleness index, which is a conceptual property that affects fracture behavior in rocks. Generally, more fracture networks are developed in more brittle rocks. For this reason, brittleness has been used as a guide to decide the target formation of hydraulic fracturing stimulation for shale and tight gas productions. Previous studies have been conducted to find out which factors have influences on the estimations of various brittleness indices to represent rock brittleness quantitatively. The objective of this study is to investigate the effect of rock fabric on the estimation of the mineralogy-based brittleness index. Both elastic moduli- and mineralogy-based brittleness indices, which are the most commonly used indices, are obtained using available data from the Montney Formation, Canada. The former index is evaluated using the Young’s modulus and the Poisson’s ratio that are calculated from the sonic and density logs. The latter index is estimated based on the mineral composition from X-ray diffraction quantitative analysis. Comparison between the results from two different methods indicates that quartz might be the controlling mineral on the brittleness index of the lower Montney Formation. Thin section observations, however, show that the strength of the lower Montney Formation might be determined by dolomite and clay considering matrix-supported textures. This means that rock strength and brittleness may not be governed by same controlling factors. This suggests that rock fabrics, such as anisotropy due to the lamination or quantitative analysis of minerals which constitute grain, cement, and matrix through thin section observation, should be considered in addition to the mineral composition in order to evaluate mineralogy-based brittleness index more accurately.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".