Replacing conventional brittleness indices determination with new attributes using true hydrofracturing mechanism
Bibliographic record
Abstract
Shale resource plays are associated with low permeability; hence, hydraulic fracturing is required for their stimulation and production. Even though considerable nonuniqueness exists in identifying favorable zones for hydraulic fracturing, geophysicists seem to be avid followers of low-Poisson’s ratio and high-Young’s modulus brittleness criteria, proposed a decade ago. We highlight the misinterpretation that one may run into in following such a criterion for any shale play and develop a new attribute that makes use of strain energy density and fracture toughness. Although the former controls fracture initiation, the propagation of fractures is governed by the latter. Because hydraulic fracturing comprises both these properties, it is firmly believed that the new proposed attribute could be used to highlight the favorable intervals for fracturing. Core data, well log curves, along with mud logs have been used to authenticate the proposed attribute. Finally, computation of the new attributes is implemented on the seismic data with encouraging 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".