On the 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 kilometers 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 much larger thermal anomalies, 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 is considered. Exploitation of shallow thermal anomalies for heat and power production partly depends on the volume and temperature of the hydrothermal reservoir. This study presents a non-exhaustive numerical investigation of fluid flow models within and around simplified fault zones, wherein realistic fluid and rock properties are accounted for, as are appropriate boundary conditions. 2D simplified models point out relevant physical mechanisms for geological problems, such as “thermal inheritance” or pulsating plumes. 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 simplified 3D models wherein the fault zone dip angle and fault zone thickness are varied, the anomalously hot reservoir exhibits a kilometer-sized “hot air balloon” morphology or, when permeability is depth-dependent, a “funnel-shaped” 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 wherein 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 | 0.000 |
| 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 | 0.000 | 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".