Relative Moment Tensor Analysis of the DEEP Heat Enhanced Geothermal System, Finland
Bibliographic record
Abstract
A 40MWth geothermal district heating plant was planned in Espoo, Finland. Heat was to be mined from a granite reservoir at 6100m depth with a temperature of 120°C. To achieve sufficient flow rates, the reservoir was hydraulically fractured, but ultimately permeability was too low and the project was suspended. The wells have been donated to science and an ICDP proposal is in preparation. We here present relMT, a new method to estimate relative earthquake moment tensors (MT) of weak seismic events. Moment tensors yield a description of the size and orientation of the fracturing process at depth. They are important to know, because complexity and size of the activated fracture network limit the maximum magnitude of seismicity and contribute to the success of the stimulation. Relative MTs require less subsurface information than absolute MTs and can be computed small shaking events, allowing to characterize subsurface fracture networks at a finer scale than previously possible.
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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 | 0.000 |
| 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) | 0.001 | 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".