Multiscale fracture networks and their impact on hydroshearing response in the Canadian Shield (Kuujjuaq, Canada)
Bibliographic record
Abstract
Abstract Understanding the natural fracture network is essential for geothermal-related investigations. However, the geometrical attributes depend on the scale of observation. Therefore, a multiscale characterization of the fracture network is essential to ensure that heat and flow simulations are based on stochastically generated discrete fracture network models representative of the natural fracture system observed. The objective of this project was to understand the scale effect of fracture data on the performance of a potential enhanced geothermal system in crystalline rock in northern Canada. This was accomplished by collecting and characterizing fracture data from core, outcrops and satellite image, and then constructing a discrete fracture network model which was used to simulate the performance of the geothermal system. The numerical simulations suggest that fracture length and spacing have an important impact on its performance. Thermal short-circuiting can be easily achieved if the fracture network is modelled based solely on satellite image data, and hydroshearing may be less effective if the DFN is constructed based solely on outcrop data. The simulations suggest that combining the different datasets provides the best compromise between heat extraction, water losses, hydraulic impedance and thermal drawdown. Despite the uncertainties, the fracture data used highlights the importance of multiscale fracture analysis for heat-flow simulations of geothermal reservoirs.
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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 | 0.001 | 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".