On morphology and amplitude of 2D and 3D thermal anomalies induced by buoyancy-driven flow within and around fault zones
Bibliographic record
Abstract
Abstract. In the first kilometres of the subsurface, temperature anomalies due to heat conduction processes rarely exceed 20–30 °C. When fault zones are sufficiently permeable, fluid flow may lead to thermal anomalies much higher, as evidenced by the emergence of thermal springs or by fault-related geothermal reservoirs. Hydrothermal convection triggered by buoyancy effects creates thermal anomalies whose morphology and amplitude are not well known, especially when depth- and time-dependent permeability are considered. Exploitation of shallow thermal anomalies for heat and power production partly depends on the volume and on the temperature of the hydrothermal reservoir. This study presents a non-exhaustive numerical investigation of fluid flow models within and around simplified fault zones, where realistic fluid and rock properties are accounted for, as well as appropriate boundary conditions. 2D simplified models point out relevant physical mechanisms for geological problems, such as thermal inheritance or splitting plumes showing a pulsating behaviour. When permeability is increased, the classic finger-like upwellings evolve towards a bulb-like geometry, resulting in a large volume of hot fluid at shallow depth. In the simplified 3D models, where fault zone dip angle and fault zone thickness are varied, the anomalously hot reservoir exhibits a kilometre-sized hot air balloon morphology, or, when permeability is depth-dependent, a funnel-shape geometry. For thick faults, the number of thermal anomalies increases but not the amplitude. The largest amplitude (up to 80–90 °C) is obtained for vertical fault zones. At the top of a vertical, 100 m wide, fault zone, temperature anomalies greater than 30 °C may extend laterally over more than 1 km from the fault boundary. These preliminary results should motivate further geothermal investigations of more elaborated models where topography and fault intersections would be accounted for.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".