Updated 3D resistivity model of the Tres Vírgenes geothermal field (Mexico) from magnetotelluric data: Implications for geothermal exploration and development
Bibliographic record
Abstract
A case study is presented involving the 3D inversion of a legacy magnetotelluric (MT) dataset from the Tres Vírgenes Volcanic Complex (TVVC), Baja California Sur, Mexico, which is a significant geothermal energy resource with an installed capacity of 10 MWe. The MT dataset consists of 76 stations acquired between 1992 and 1999 (bandwidth: 0.003 – 100 Hz), and was previously analyzed using 1D, 2D, and 3D approaches, revealing a layered resistivity structure. However, significant uncertainty surrounds the capability of this dataset to resolve deep resistivity structures associated with the magmatic system. This study applies a 3D inversion approach that incorporates topography and bathymetry and inversion tests to assess the sensitivity of the model features to the data. Well-logs and laboratory measurements of resistivity were used to constrain the interpretation. The integrated methodology enabled a more accurate delineation of the resistivity structure of the TVVC, mapping an extensive conductor primarily associated with a brine-saturated smectite clay cap (10 – 60 % clay fraction, 150 – 200 °C). Internal variability within the conductor suggests the presence of a small sill with andesitic mush (30 – 85 % melt fraction) north of El Azufre Volcano, possibly associated with sulphate-type hydrothermal activity along the El Azufre Fault Zone. Moreover, a zone of lower resistivity to the north of the main conductor suggests a possible intrusion of seawater that remains isolated from the main hydrothermal systems in TVVC. Sensitivity tests indicate that the dataset lacks the resolution required to image deep bodies beneath the main conductor; consequently, deep conductors modelled in previous studies are likely inversion artifacts, and are unrelated to the deep magmatic system. These findings have the potential to improve the delineation of the geothermal system boundaries, and provide insights for future geothermal and magnetotelluric exploration.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".