Numerical assessment of the geothermal resource potential of the Charlevoix meteorite impact crater, Canada
Bibliographic record
Abstract
• The geothermal exploration of a meteorite impact crater is presented. • A 2D groundwater flow and transfer model is used to simulate temperature at depth. • Temperature below Charlevoix is predicted considering the crater characteristics. • Insulating anorthosite and fractured basement rocks provide a favorable geothermal potential. Geothermal targets may be found in naturally fractured rocks of meteorite impact craters hosting low temperature resources. We therefore conducted a study with the objective of evaluating the geothermal potential of the 400 million year old Charlevoix impact crater in Quebec (Canada). Finite element simulations of steady state groundwater flow and heat transfer were made based on field characterization that allowed for the evaluation of rock thermohydraulic properties. Simulations provided a definition of the temperature field in cross-sections of the crater up to 10 km depth. Results allowed quantification of the impact of the deep groundwater recharge, the rock thermal conductivity and the Earth heat flow on the temperature distribution at depth. The calculated geothermal gradient inside the Charlevoix crater reaches 31 °C km -1 in the most favorable areas. The average temperature at 3 km depth was 70 °C inside the crater and was higher compared to outside the crater. This suggests greater potential for low-temperature geothermal direct use in the crater.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".