Dynamic earthquake triggering can be used to investigate the responses of faults to stress disturbances. We develop a new method to detect dynamic triggering by estimating high‐frequency energy change before and during teleseismic waves using the HIgh‐Frequency power Integral ratio (HiFi). Our method is able to identify local events independent of earthquake catalog or subjective judgements. The significance in energy change is evaluated by a statistical analysis of the background ratio in a large number of days, which can suppress the influence of noise and variations in the background seismicity and yield a confidence level of dynamic triggering (0–1). We apply the HiFi method to the Geysers Geothermal Field in California, and the results are largely consistent with previous reports from the β statistic. By comparing the results of HiFi and β statistic, we select a confidence level range of 0.918–0.947 as the optimum threshold to identify dynamic triggering in the region.

Long-term and large-scale observations of dynamic earthquake triggering are urgently needed to understand the mechanism of earthquake interaction and assess seismic hazards. We developed a robust Python package termed DynTriPy to automatically detect dynamic triggering signals by distinguishing anomalous seismicity after the arrival of remote earthquakes. This package is an efficient implementation of the high-frequency power integral ratio algorithm, which is suitable for processing big data independent of earthquake catalogs or subjective judgments and can suppress the influence of noise and variations in the background seismicity. Finally, a confidence level of dynamic triggering (0–1) is statistically yielded. DynTriPy is designed to process data from multiple stations in parallel, taking advantage of rapidly expanding seismic arrays to monitor triggering on a global scale. Various data formats are supported, such as Seismic Analysis Code, mini Standard for Exchange of Earthquake Data (miniSEED), and SEED. To tune parameters more conveniently, we build a function to generate a database that stores power integrals in different time and frequency segments. All calculation functions possess a high-level parallel architecture, thoroughly capitalizing on available computational resources. We output and store the results of each function for continuous operation in the event of an unexpected interruption. The deployment of DynTriPy to data centers for real-time monitoring and investigating the sudden activation of any signal within a certain frequency scope has broad application prospects.

<p>Xiaojiang Fault (XJF) lies at the southeastern edge of the rhombic Sichuan-Yunnan block, and has an extent for over 400km from Qiaojia to Shanhua district. The Sichuan-Yunnan block experiences clockwise rotation and southwestward escaping from the Tibetan Plateau, producing complex fault geometry and seismicity pattern. The strong variation along fault segments provides a special opportunity to study the relationship between fault zone properties and seismicity pattern. However, the fine structure of XJF remains unknown due to the sparse observational stations.</p><p>Seismic data has its unique advantage of resolving fault zone properties at depth. We deployed 48 broad-band seismometers along XJF in order to capture detailed seismicity patterns. Our seismic network covers the northern and middle part of XJF, with an average aperture of 20km; the continuous observation from 2015 to 2019 guarantees enough data volume. We detected about 12,000 earthquakes by STA/LTA phase picking and association, and augmented the detection to over 50,000 events with template matching. The relocated catalog has lateral and vertical resolution of 500m and 1km, respectively; the magnitude of completeness (Mc) reaches ML0.3</p><p>This high-resolution catalog depicts detailed 3D fault geometry. The seismicity shows clustered lateral distribution, with the clusters’ depth extension ranging from 20km at northern to 35km at southern segments. Unmapped orthogonal faults on northern XJF are illuminated by seismicity, which matches orthogonal topography characteristics. Repeating events are detected from 8 seismicity clusters, under a threshold of 5 repeating families, indicating a creeping slip mode, while the separated low-seismicity segments exhibit a high locking rate. Taking advantage of the high detectability, we got reliable b-value estimation for different segments of XJF. The low-b regions correlate well with the margins of locking patches, which points to a high stress concentration. Velocity structure extracted from ambient noise and fault zone head wave present similar spatial variation, which further proved the seismicity pattern. The high heterogeneous characteristics of XJF may produce stress barriers, preventing future earthquake rupture from propagating to a large scale. </p>

Absolute tectonic stress estimation is of fundamental importance to investigating regional earthquake hazards, while traditional algorithms only invert relative stress and its orientations. We use topography data and rupture models to invert the absolute tectonic stress in the source region of the 2016 Mw 7.0 Kumamoto earthquake. We adopt a basic assumption that the slip direction of each sub‐fault is in the shear direction of the total stress tensor, which is a combination of tectonic and topographic stresses. We use the Bayesian theorem to describe the probability density function of stress parameters and perform a grid search for the optimal values and uncertainties of stress parameters. Our synthetic test shows that the true parameters can be reliably estimated over a broad range of tectonic stress magnitudes. In the application to the Kumamoto earthquake, we find that the optimal tectonic stress is uniaxial tensional with a magnitude of 35 MPa and orientation of N6.5°W, which is at an angle of ∼47.5° to the fault strike. The average total shear stress on the fault plane is 16 MPa on the fault plane. With the inverted stress parameters, we evaluate the pore pressure based on the absolute stress field, the result of which is within a range of 0.3–0.45 of the lithostatic stress.