Development of connected permeability in massive crystalline rocks through hydraulic fracture propagation and shearing accompanying fluid injection
Bibliographic record
Abstract
The ability to generate deep flow in massive crystalline rocks is governed by the interconnectivity of the fracture network and its permeability, which in turn is largely dependent on the in situ stress field. The increase in stress with depth reduces fracture aperture, leading to a decrease in rock mass permeability. In massive crystalline rocks, often favored for enhanced geothermal system projects, permeability is governed by fracture connectivity and aperture. Injection of pressurized fluid for hydraulic treatments is critical for enhancing the interconnectivity of fracture permeability in tight rock masses. Two injection procedures may be employed in this context: hydraulic fracturing and hydraulic shearing (HS). This chapter reports the findings from a detailed set of numerical models performed as part of the experiment design. These analyses have been used to help define the fluid injection magnitudes and rates, optimal locations of monitoring sensors, and preliminary estimates of expected response.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".