Seismic Anisotropy Reveals Stress Changes around a Fault as It Is Activated by Hydraulic Fracturing
Bibliographic record
Abstract
Abstract Subsurface stress conditions evolve in response to earthquakes or fluid injection. Using observations of an induced seismicity sequence from a dense local array, anisotropy analysis is employed to characterize stress changes around a fault. The dataset comprises high signal-to-noise ratio S-wave data from 300 events, ranging in magnitude from −0.45 to 4.1, recorded on 98 three-component geophones cemented in shallow wells. It is found that the orientation of the fast S-wave direction remains relatively constant for all stations over time, but the magnitude of the anisotropy, as measured by the delay time between the fast and slow S wave, exhibits significant local variations. Some stations experience a systematic increase or decrease in the delay time, with a spatial coherence about the injection well. The stress changes due to hydraulic fracturing, aseismic slip, and observed earthquakes are modeled to determine the best fit to the observed anisotropy changes. Our analysis indicates that the creation of a network of tensile hydraulic fractures during fluid injection is likely to be the cause of the observed anisotropy changes. This study confirms that the measurements of seismic anisotropy over time reflects the evolving stress state of a fault prior to and during rupture.
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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 | 0.002 | 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".