The Role of the Three‐Dimensional Geometry of Fault Steps on Event Migration During Fluid‐Induced Seismic Sequences
Bibliographic record
Abstract
Abstract This study analyses how fault segmentation influences seismicity using 3 high‐resolution earthquake catalogs from tectonically different areas. The studied event patterns reveal 8 fault steps with different 3D geometries reminiscent of relay zones, which refer to the area of displacement transfer between stepping and overlapping segments due to fault segmentation, including cylindrical, bifurcating, dip, strike and oblique relay zones as mapped from seismic reflection surveys. After detailed mapping of the spatiotemporal event migration, we analyze how 3D fault geometry, and in particular internal segmentation, controls event migration. First, we show that events can migrate continuously between segments via connected areas, producing along‐step, around‐step and bidirectional migrations, with steps acting as a barrier. Second, we observe seismicity that hops across bounding segments if a sufficiently strong magnitude event, with a relatively large rupture length compared to the step size, occurs near the step. Thus, fault segmentation, inherited from the early stage of fault development, controls earthquake migration patterns, if coupled with the type of forces driving seismicity. Specifically, tectonic‐dominated sequences with relatively high magnitude seismicity and critically stressed segments promote inter‐segment hopping. In contrast, fluid‐dominated sequences, producing lower‐magnitude events, are strongly channeled by connected segments.
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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 | 0.001 | 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".