Discriminating induced seismicity from natural earthquakes using moment tensors and source spectra
Bibliographic record
Abstract
Abstract Earthquake source mechanisms and spectra can provide important clues to aid in discriminating between natural and induced events. In this study, we calculate moment tensors and stress drop values for eight recent induced earthquakes in the Western Canadian Sedimentary Basin with magnitudes between 3.2 and 4.4, as well as a nearby magnitude 5.3 event that is interpreted as a natural earthquake. We calculate full moment tensor solutions by performing a waveform‐fitting procedure based on a 1‐D transversely isotropic velocity model. In addition to a dominant double‐couple (DC) signature that is common to nearly all events, most induced events exhibit significant non‐double‐couple components. A parameter sensitivity analysis indicates that spurious non‐DC components are negligible if the signal to noise ratio (SNR) exceeds 10 and if the 1‐D model differs from the true velocity structure by less than 5%. Estimated focal depths of induced events are significantly shallower than the typical range of focal depths for intraplate earthquakes in the Canadian Shield. Stress drops of the eight induced events were estimated using a generalized spectral‐fitting method and fall within the typical range of 2 to 90 MPa for tectonic earthquakes. Elastic moduli changes due to the brittle damage production at the source, presence of multiple intersecting fractures, dilatant jogs created at the overlapping areas of multiple fractures, or non‐planar pre‐existing faults may explain the non‐DC components for induced events.
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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 | 0.002 |
| 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".