Identification of repeating earthquakes (repeaters) usually depends on waveform similarity expressed as the corresponding cross‐correlation coefficient (CC) above a prescribed threshold, typically ranging in 0.70–0.98. However, the robustness and effectiveness of such a strategy have rarely been fully examined. In this study, we examine whether CC is a valid proxy for repeater identification through both synthetic and real earthquake experiments. We reveal that CC is controlled by not only the interevent distance but also many other factors, including station azimuth, epicentral distance, and velocity structure. Consequently, CC lacks the resolution in identifying true repeaters. For reliable repeater identification, we should consider the interevent overlap. Specifically, we define an event pair to be true repeaters if their interevent separation is smaller than the source dimension of the larger event. Our results imply that a systematic recheck of previously identified repeaters and associated interpretations/hypotheses may be important and necessary.

Waveform match‐filtering (MF), based on cross‐correlation between an earthquake pair, is a powerful and widely used tool in seismology. However, its performance can be severely affected by several factors, including the length of the cross‐correlation window, the frequency band of the applied digital filter, and the presence of a large‐amplitude phase(s). To optimize the performance of MF, we first systematically examine the effects of different operational parameters and determine the generic rules for selecting the window length and the optimal frequency passband. To minimize the influence of a large‐amplitude phase(s), we then propose a new approach, namely, MF with multisegment cross‐correlation (MFMC). By equally incorporating the contributions from various segments of the waveforms, this new approach is much more sensitive to small separation between two sources compared to the conventional MF method using the entire waveform template. To compare the reliability and effectiveness of both methods in capturing interevent source separation and identifying repeating earthquakes, we systematically conduct experiments with both synthetic data and real observations. The results demonstrate that the conventional MF method can detect the existence of an event but sometimes lacks the resolution to tell whether the template and detected events are co‐located or not, whereas MFMC works in all cases. The far‐reaching implication from this study is that inferring source separation between an earthquake pair based on the conventional MF method, particularly with data from a single channel/station, may not be reliable.

The subsurface velocity model is crucial for high-resolution seismic imaging. Although full-waveform inversion (FWI) is a high-accuracy velocity inversion method, it inevitably suffers from challenging problems, including human interference, strong nonuniqueness, and high computing costs. As an efficient and accurate nonlinear algorithm, deep learning (DL) has been used to estimate velocity models. However, conventional DL is insufficient to characterize detailed structures and retrieve complex velocity models. To address the aforementioned problems, we propose a hybrid network (AG-ResUnet) involving fully convolutional layers, attention mechanism, and residual unit to estimate velocity models from common source point (CSP) gathers. Specifically, the attention mechanism extracts the boundary information, which serves as a structural constraint in network training. We introduce the structural similarity index (SSIM) to the loss function, which minimizes the misfit between predicted velocity and ground truth. Compared with FWI and other networks, AG-ResUnet is more effective and efficient. Experiments on transfer learning and noisy data inversion demonstrate that AG-ResUnet makes a generalized and robust velocity prediction with rich structural details. The synthetic examples demonstrate that our method can improve seismic velocity inversion, contributing to guiding the imaging of geological structures.

Earthquakes resulting from hydraulic fracturing (HF) can have delayed triggering relative to injection commencement over a varied range of time scales, with the majority of M ≥ 4 mainshocks occurring near/after well completion. This poses serious challenges for risk mitigation and hazard assessment. Here, we document a high‐resolution, three‐dimensional source migration process with delayed mainshock triggering that is controlled by local hydrogeological conditions near Fox Creek, Alberta, Canada. Our results reveal that poroelastic effects might contribute to induced seismicity, but are probably insufficient to activate a large fault segment not critically stressed. The rapid pore‐pressure build‐up from HF can be very localized and capable of producing large, felt earthquakes if adequate hydrological paths exist. We interpret the delayed triggering as a manifestation of pore‐pressure build‐up along pre‐existing faults needed to facilitate seismic failure. Our findings can explain why so few injection operations are seismogenic.

Repeating earthquakes (repeaters) are events that recurrently rupture the same fault patch with nearly identical magnitudes. Although repeaters have been widely studied and utilized in many fields over the last four decades, there are no standard criteria for reliably identifying such events. The current criteria adopted in the geophysical research community are inconsistent and difficult to justify. Different criteria may inescapably incur inadequate hypotheses and lead to controversial interpretations, highlighting the urgent need for seeking a uniform approach to reliably identify repeaters. In this study, we address this long-standing issue by deriving the most logical criteria on the basis of theoretical calculation with simple yet reasonable assumptions. Quantitatively, we define a repeating pair if their interevent distance is ≤80% of the rupture area of the larger event and their magnitude difference is ≤0.3. We demonstrate the superiority of our proposed approach with challenging cases in California, and our results shed new insight into the hierarchical fault structures in the source areas. Although this study focuses on defining repeating earthquakes, the application to repeating seismic events in other planetary bodies such as moonquakes and marsquakes is straightforward, potentially help avoid misinterpretations of the physical processes in both Earth and planetary interiors.