Fracture Network in a Shale Cube Hydraulically Fractured in the Laboratory
Bibliographic record
Abstract
The figure shows the fracture network in a fractured middle Montney shale core sample visualized at a spatial resolution of 39 × 39 × 50 µm3 utilizing the serial-section reconstruction method. The shale cube was made by casting gypsum cement around a fulldiameter shale core and drilling a horizontal borehole (light green) to the middle of the sample. The fracture network formed by laboratory hydraulic fracturing test was complex due to the impact of the intrinsic anisotropy of the shale sample contributed by natural fractures and bedding planes. The hydraulic fracturing test not only generated new hydraulic fractures (yellow) dipping toward σ 3 , but also opened subvertical natural fractures (dark gray) and activated bedding planes (blue) dipping 17° to horizontal. The opened natural fractures and bedding planes dominate in the volume of the fracture network, where the natural fractures cross-cut most of the bedding planes - encouraging fracture connectivity and accordingly fluid transmissivity. This fracture network pattern can be expected to be a reliable proxy for the fracturing process occurring near the wellbore in similar shale formations [1].
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".