MT data inversion and dimensionality analysis in Varton geothermal central Iran
Bibliographic record
Abstract
The Varton geothermal is located circa 70 kilometers northeast of Isfahan, central Iran. The study area consists of highly fractured rocks with argillic alteration zones and some hot springs. Here, we conduct a magnetic and magnetotelluric data survey to study the effect of the fractures on the hydrothermal convection system. The magnetic data processing exposed two parallel main faults with NW-SE strike in the northern and southern borders of the area. Here, we used nine magnetotelluric (MT) stations along a profile perpendicular to the main faults. Dimensionality analysis of MT impedance and phase tensors in the stations indicated a media with two-dimensional structures. However, 1D MT data inversion revealed a three-layered earth beneath most stations, though the layers' thickness and resistivities varied along the profile. Also, 2D MT data inversion results showed that the resistivity between the two main faults was significantly smaller than zones beyond the faults. However, a large zone with low resistivity was close to the southern fault. Besides, a shallow layer overlain a thin conductive layer with a resistivity of one ohmm or less. In depths more than 500 m, the resistivity noticeably increased gradually to 1000 ohmm. According to the mentioned results, we deduce that the southern fault is the main feeding fault for the geothermal system. Furthermore, the layer with the lowest resistivity correlates with clay alteration and could be the clay cap of the reservoir. Therefore, the deeper resistive rock is the geothermal reservoir.
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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 | 0.000 | 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 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".