Contrasting Crustal Signatures Across the 2021 M <sub>S</sub> 6.0 Luxian (China) Induced Earthquake Revealed by Dense Seismic and Magnetotelluric Data
Bibliographic record
Abstract
Abstract The 2021 Luxian earthquake has raised concerns about the seismic potential in the southern Sichuan Basin and highlighted the need to gain a further understanding of the area's seismic risks. To elucidate the underlying mechanisms driving the largest recorded hydraulic fracturing‐induced earthquake in China, this study investigates the local seismogenic environment of this notable event through an integrated seismic and magnetotelluric (MT) approach. Utilizing a linear Radon transform‐based mode‐separation method, we derived a 3‐D fine‐resolution velocity structure from dense seismic data. Corroborated by resistivity measurements using a co‐located MT array, our integrated data set provides compelling evidence for a complex upper‐crustal geological structure across the Huayingshan fault (HYS‐F). Apart from the low velocity and resistivity zones at 3–4 km depth within the HYS‐F, consistent with the location of fluid injection sites, we newly discovered a large‐scale low‐resistivity anomaly beneath the mainshock at depths exceeding 15 km. A comparable structural pattern emerges in the southeast of the HYS‐F, where the distribution and focal mechanisms of recently detected earthquakes, including and earthquakes, highlight the combined influence of shallow fluid injection and the ascent of deep metamorphic saline fluids in creating a breeding condition for seismicity. A prominent high‐velocity and high‐resistivity anomaly in the northwest, extending from the surface to depths exceeding 20 km, is potentially linked to intruded ancient materials originating from the lower crust. Our findings reveal that complex geological structures and dynamic processes strongly impact the occurrence and distribution of earthquakes in the Luxian earthquake region.
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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 | 0.000 | 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".