Geophysical Journal International

SummaryHigh-resolution detection of hidden geological faults is vital for city planning, earthquake disaster prevention, and large-scale engineering construction. This study deployed 229 short-period seismometers across a 10×30 km region within the Xianlin area of Nanjing. Of which, 199 formed a 2-D array, and 30 formed a linear array. Various methods were applied to detect hidden faults in the study area. Using ambient noise tomography, a three-dimensional (3D) S-wave velocity structure was obtained from the surface to a depth of 6.0 km, allowing the first locations of a hidden fault to be mapped via velocity anomalies. A linear array was subsequently deployed based on these early findings, and the horizontal-to-vertical spectral ratio (HVSR) method was applied to estimate bedrock depth and define shallow fault features in greater detail. Finally, a shallow seismic exploration was performed to verify the detection results of ambient noise tomography and HVSR analysis. The results indicate the presence of a hidden fault in the study area, which manifests as a distinctive area of alteration in the high- and low-velocity anomalies in the 3D S-wave velocity structure. Significant variation was identified in the sediment layer thickness in the shallow subsurface, as observed in the HVSR records. In addition, shallow seismic exploration defined important wave-group phase-axis discontinuities in areas with abrupt sedimentary thickness changes. Thus, the hidden fault identified in this study is a normal fault with a nearly north-dipping direction, dip angle of approximately 60°, and fault displacement of approximately 30 m. By linking these results with previous data, it is possible to suggest that such hidden faults are part of the Mufushan–Jiaoshan Fault. Future urban designs and buildings must thoroughly consider the seismic dangers in this region and apply suitable mitigation strategies.

SummaryShipborne gravity anomaly data exhibit multi-vintage characteristics due to their extended temporal coverage. Currently, the measurement accuracy of gravimeters and the processing methods for shipborne gravity anomaly data have been significantly improved and refined. At this stage, the influence of temporal error on the processing of shipborne gravity anomaly data has become an issue that cannot be neglected. We propose a joint reprocessing method for multi-vintage shipborne gravity anomaly data considering temporal error effects. Firstly, the gross error of the shipborne gravity anomaly data is eliminated and filtered. When compensating for the survey line error, the time variable is added to the error equation in order to retain the temporal information in the observed value. The corrected shipborne gravity anomaly data by this method is closer to the real gravity field information. We applied this method to the real shipborne gravity anomaly data in the Philippine Sea. The results showed that the standard deviation of the discrepancy at the intersection points of the survey lines was reduced from the initial 13.46 mGal to 4.30 mGal. The shipborne gravity anomaly data processed after considering the temporal error effects conforms more closely to the actual gravity field information.

SummaryPassive surface wave method is increasingly being applied to urban subsurface exploration due to its non-invasiveness, low cost, and high efficiency. However, its imaging quality is often influenced by limited data acquisition time and the heterogeneous distribution of seismic ambient fields in complex urban environments. To extract coherent surface wave signals for seismic imaging in such challenging setting, we developed a multi-stage urban ambient noise deep clustering framework based on a convolutional autoencoder and deep embedded clustering algorithm. The initial clustering characterizes the distribution patterns of urban noise sources, which informs a secondary, finer clustering to select noise sources optimized for urban seismic imaging. Real-world experiment on the urban train noise field demonstrates our urban noise cluster framework effectively identifies and elucidates the temporal evolution patterns of moving train sources. Compared to traditional data selection methods, our approach yields superior dispersion measurements and significantly attenuates artifacts from the fundamental mode. Furthermore, by employing mode-specific clustering, we successfully capture the refined first overtone, enhancing the accuracy and depth resolution of seismic imaging. This study presents a new perspective to analyzing and selecting complex noise sources, significantly advancing seismic imaging and monitoring in alignment with emerging Artificial Intelligence trends.

SummaryBoth short-term coseismic off-fault damage and long-term fault growth during interseismic periods have been suggested to contribute to the formation and evolution of fault damage zones. Most previous numerical models focus on simulating either off-fault damage in a single earthquake or off-fault plasticity in seismic cycles ignoring changes of elastic moduli. Here we developed a new method to simulate the damage evolution of fault zones and dynamic earthquake cycles together in a 2D anti-plane model. We assume fault slip is governed by the laboratory-derived rate-and-state friction law while the constitutive response of adjacent off-fault material is controlled by a simplified version of the Lyakhovsky-Ben-Zion continuum brittle damage model. This study aims to present this newly developed modeling framework which opens a window to simulate the co-evolution of earthquakes and fault damage zones. We also demonstrate one example application of the modeling framework. The example simulation generates coseismic velocity drop as evidenced by seismological observations and a long-term shallow slip deficit. In addition, the coseismic slip near the surface is smaller due to off-fault inelastic deformation and results in a larger coseismic slip deficit. Here we refer to off-fault damage as both rigidity reduction and inelastic deformation of the off-fault medium. We find off-fault damage in our example simulation mainly occurs during earthquakes and concentrates at shallow depths as a flower structure, in which a distributed damage area surrounds a localized, highly damaged inner core. With the experimentally based logarithmic healing law, coseismic off-fault rigidity reduction cannot heal fully and permanently accumulates over multiple seismic cycles. The fault zone width and rigidity eventually saturate at long cumulative slip, reaching a mature state without further change.