Seismicity during and after stimulation of a 6.1 km deep Enhanced Geothermal System in Helsinki, Finland
Bibliographic record
Abstract
Abstract. In this study, we present a high-resolution dataset of seismicity framing the stimulation campaign of a 6.1 km deep Enhanced Geothermal System (EGS) in Helsinki suburban area and discuss the complexity of fracture network development. Within St1 Deep Heat project, 18 160 m3 of water was injected over 49 days in summer 2018. The seismicity was monitored by a seismic network of near-surface borehole sensors framing the EGS site in combination with a multi-level geophone array located at ≥ 2 km depth. We expand the original catalog of Kwiatek et al. (2019) and provide the community with the dataset including detected seismic events and earthquakes that occurred two month after the end of injection, totalling to 61 163 events. We relocated events of the catalog with sufficient number of available phase onsets and moment magnitudes between Mw −0.7 and Mw 1.9 using the double-difference technique and a new velocity model derived from a post-stimulation vertical seismic profiling campaign. The analysis of the fault network development at reservoir depth of 4.5–7 km is one primary focus of this study. To achieve this, we investigate 191 focal mechanisms of the induced seismicity using cross-correlation based technique. Our results indicate that seismicity occurred in three spatially separated clusters centered around the injection well. We observe a spatio-temporal migration of the seismicity during the stimulation starting from the injection well in northwest (NW) – southeast (SE) direction and in northeast (NE) direction towards greater depth. The spatial evolution of the cumulative seismic moment, the distribution of events with Mw ≥ 1 and the fault plane orientations of focal mechanisms indicate an active network of at least three NW–SE to NNW-SSE orientated permeable zones which is interpreted to be responsible for migration of seismic activity away from the injection well. Fault plane solutions of the best-constrained focal mechanisms as well as results for the local stress field orientation indicate a reverse faulting regime and suggest that seismic slip occurred on a sub-parallel network of pre-existing weak fractures favorably oriented with the stress field, striking NNW-SEE with a dip of 45° ENE, parallel to the injection well.
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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 | 0.001 |
| 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".