Rui Wang

As global energy systems pursue lower-carbon transition pathways, the rapid expansion of shale-gas development has increased subsurface fluid injection, intensifying concerns about induced seismicity and associated seismic risk. Although regional studies have documented specific induced-seismicity sequences, global patterns, regional variability, forecasting approaches, and governance practices have rarely been examined together within an integrated framework. This review synthesizes shale-gas-related induced seismicity across major production regions, including North America, Europe, and China, with particular emphasis on common patterns and contrasting seismic responses to hydraulic fracturing and wastewater disposal. Across diverse geological and operational settings, the reviewed evidence indicates that wastewater disposal is generally associated with larger-magnitude and more spatially widespread seismicity, whereas hydraulic fracturing typically produces localized seismicity but can also be associated with significant events where critically stressed faults are hydraulically connected to the stimulated zone. Building on this regional synthesis, we compare statistical, physics-based, hybrid, and machine-learning forecasting methods in terms of their operational applicability, predictive capabilities, data requirements, and limitations. However, translating these methodological advances into effective risk reduction requires their integration with robust monitoring and adaptive governance practices. Current governance measures can reduce risk, but their effectiveness depends on sufficiently sensitive monitoring, timely data exchange, regionally calibrated and adaptive operational thresholds, and continued post-injection surveillance. Future risk management should therefore move toward dynamic, physics-constrained geospatial frameworks that integrate seismic observations, injection histories, fault architecture, and regional stress conditions to support adaptive operational decision-making.

The 2025 M _w  7.7 Myanmar earthquake ruptured the central Sagaing fault, a previously identified seismic gap with high seismic potential. Here, we perform hundreds of 3D dynamic rupture simulations to investigate the rupture dynamics, constrained by near‐fault strong‐motion waveforms, optical and SAR pixel offsets, and a kinematic source model. Our preferred model suggests that the rupture involves asymmetric supershear ruptures, with stable rupture speeds following initial bilateral subshear propagation, as supported by the low frequency of aftershocks and high seismic radiation efficiency. The Burridge‐Andrews mechanism and free‐surface effects likely dominate the supershear transition. Moreover, the derived slip distribution exhibits segmentation in both extent and magnitude, with few shallow slip deficits, which correlate with the interseismic locking depth and slip rate. Our results demonstrate that data‐constrained dynamic rupture simulations offer valuable insights into the physical mechanisms governing complex earthquake rupture processes.

Earthquake forecast and risk assessment are of key importance in reducing casualties and property losses. However, they have not been fully achieved due to the complexity of earthquakes. Numerous studies have explored the correspondence of the b-value with changes in effective stress, leveraging temporal and spatial variations to identify precursor characteristics of destructive events in both natural and induced seismic activities. However, robust interpretation of predictive b-values hinges on rigorous estimation, as biased results can mislead conclusions. This paper provides a comprehensive review of spatiotemporal b-value estimation methods alongside statistical significance tests. A pilot b-value analysis of natural earthquakes and induced seismicity manifested the valid impression. The expansion of monitoring datasets with the development of acquisition technology or dense array and advanced estimation methodology will augment the utility of b-value analysis in seismic research and hazard assessment.

The Xiluodu‐Xiangjiaba Cascade Reservoirs have been built in the lower reaches of the Jinsha River, Yunnan Province, China since 2012. Following the impoundment of these two contiguous reservoirs, widely felt seismicity has been recorded along the mainstream of the river, including three events with magnitudes greater than 4.5. To explore the correlation between the evolution of stress induced by reservoir impoundment and the spatial‐temporal seismicity, we establish a three‐dimensional poroelastic finite element model and compute the stress changes due to the elastic load of reservoir water storage and pore pressure diffusion based on the fully‐coupled poroelastic theory. The results show that the hypocenters of earthquakes after impounding are spatially correlated with the pore pressure increase. The Coulomb failure stress changes (ΔCFS) resolved on both nodal planes of the focal mechanisms of the three events with magnitudes greater than 4.5 suggest that the increased pore pressure could lead to significantly positive ΔCFS and contribute to the occurrence of the three events. Further investigation indicates that pore pressure and ΔCFS on active faults close to the river mostly increase after impounding, probably enhancing the regional seismicity. The pore pressure on active faults close to the Xiluodu Reservoir shows a clear seasonal variation. Our study reveals that the faults and geologic anomaly bodies with high permeability could provide preferential diffusion channels, thereby controlling the spatial‐temporal evolution of pore pressure changes and affecting the seismicity distribution, which are essential to understanding the occurrence of earthquakes far from the reservoir.

Characterized by frequent earthquakes and a dense population, Yunnan Province, China, faces significant seismic hazards and is a hot place for earthquake forecasting research. In a previous study, we evaluated the performance of the b value for 5-year seismic forecasting during 2000–2019 and made a forward prediction of M ≥ 5.0 earthquakes in 2020–2024. In this study, with the forecast period having passed, we first revisit the results and assess the forward prediction performance. Then, the background seismicity rate, which may also offer valuable long-term forecasting information, is incorporated into earthquake prediction for Yunnan Province. To assess the effectiveness of the prediction, the Molchan Error Diagram (MED), Probability Gain (PG), and Probability Difference (PD) are employed. Using a 25-year catalog, the spatial b value and background seismicity rate across five temporal windows are calculated, and 86 M ≥ 5.0 earthquakes as prediction samples are examined. The predictive performance of the background seismicity rate and b value is comprehensively tested and shown to be useful for 5-year forecasting in Yunnan. The performance of the b value exhibits a positive correlation with the predicted earthquake magnitude. The synergistic effect of combining these two predictors is also revealed. Finally, using the threshold corresponding to the maximum PD, we integrate the forecast information of background seismicity rates and the b value. A forward prediction is derived for the period from January 2025 to December 2029. This study can be helpful for disaster preparedness and risk management in Yunnan Province, China.

As the forefront of inland extension on the Indian plate, the northeastern Tibetan Plateau, marked by low strain rates and high stress levels, is one of the regions with the highest seismic risk. Analyzing seismicity through statistical methods holds significant scientific value for understanding tectonic conditions and assessing earthquake risk. However, seismic monitoring capacity in this region remains limited, and earthquake frequency is low, complicating efforts to improve earthquake catalogs through enhanced identification and localization techniques. Bi-scale empirical probability integral transformation (BEPIT), a statistical method, can address these data gaps by supplementing missing events shortly after moderate to large earthquakes, resulting in a more reliable statistical data set. In this study, we analyzed six earthquake sequences with magnitudes of M_S ≥ 6.0 that occurred in northeastern Tibet since 2009, following the upgrade of the regional seismic network. Using BEPIT, we supplemented short-term missing aftershocks in these sequences, creating a more complete earthquake catalog. ETAS model parameters and b values for these sequences were then estimated using maximum likelihood methods to analyze parameter variability across sequences. The findings indicate that the b value is low, reflecting relatively high regional stress. The background seismicity rate is very low, with most mainshocks in these sequences being background events rather than foreshock-driven events. The p-parameter of the ETAS model is high, indicating that aftershocks decay relatively quickly, while the α-parameter is also elevated, suggesting that aftershocks are predominantly induced by the mainshock. These conditions suggest that earthquake prediction in this region is challenging through seismicity analysis alone, and alternative approaches integrating non-seismic data, such as electromagnetic and fluid monitoring, may offer more viable solutions. This study provides valuable insights into earthquake forecasting in the northeastern Tibetan Plateau.

On 5 September 2022 (BJT), Luding, located in southwestern Sichuan Province, China, experienced an M_S 6.8 earthquake. This earthquake occurred within the historical rupture zone of the 1786 M_S 7.75 event, part of the southern section of the Xianshui He Fault belt. Given the average 155-year recurrence interval for strong earthquakes in this area, the 236 years since the last event made this earthquake somewhat expected. However, prior to this event, we did not detect any anomalies indicating low surface b-values, which are often indicative of a high-stress state in the source area before strong earthquakes, as highlighted by numerous studies. Our research focused on the northern section of the eastern boundary of the Sichuan–Yunnan sub-block, encompassing the Xianshui He, Anning He, Zemu He, and Daliang Shan fault belts. We meticulously located earthquakes of M_L ≥ 1.5 from 2009 to May 2022. The catalog was divided into two periods: 2009–2014 and 2015–May 2022. Using an AIC-constraint method, we analyzed the changes in b-values (Δb) in the latter period compared to the former. Our findings revealed a significant abnormal Δb zone (Δb < −0.3), with a radius of approximately 50 km, when ΔAIC ≥ 2 was selected. Intriguingly, the epicenter of the recent Luding M_S 6.8 earthquake fell within this abnormal zone. Furthermore, we calculated the b-value cross-section for the southern section of the Xianshui He fault belt using a directory of precisely located small earthquakes. This revealed that the location, scale, and shape of the abnormally low-b-value area corresponded with the large displacement co-seismic area of the main earthquake, affirming the b-value’s effectiveness in identifying asperities. The b-value’s temporal evolution prior to the mainshock exhibited a nearly decade-long continuous decrease, signifying a long-term stress-loading process akin to that observed before many strong earthquakes. The b-value anomalies observed from different profiles before the Luding earthquake underline the necessity of a comprehensive, multi-dimensional analysis of such anomalies. Finally, our analysis indicates that nine earthquakes with M_S ≥ 6.5, including the Luding M_S 6.8 event, have contributed to increased Coulomb Failure Stress change (ΔCFS) in the Daofu (DF)–Kangding (KD) section of the Xianshui He fault belt and the northern section of the Anning He fault belt south of Shimian (SM), with amplitudes surpassing the 0.01 MPa threshold. This suggests the potential for strong earthquakes in these zones.

The northeastern margin of the Tibetan Plateau (NE Tibetan Plateau) exhibits active geological structures and has experienced multiple strong earthquakes, with M ≥ 7, throughout history. Particularly noteworthy is the 1920 M8¹/₂ earthquake in the Haiyuan region that occurred a century ago and is documented as one of the deadliest earthquakes. Consequently, analyzing seismic risks in the northeastern margin of the Tibetan Plateau holds significant importance. The b value, a crucial parameter for seismic activity, plays a pivotal role in seismic hazard analyses. This study calculates the spatial b values in this region based on earthquake catalogs since 1970. The study area encompasses several major active faults, and due to variations in b values across different fault types, traditional grid-search methods may introduce significant errors in calculating the spatial b value within complex fault systems. To address this, we employed the hierarchical space–time point–process (HIST-PPM) method proposed by Ogata. This method avoids partitioning earthquake samples, optimizes parameters using Akaike’s Bayesian Information Criterion (ABIC) with entropy maximization, and theoretically allows for a higher spatial resolution and more accurate b value calculations. The results indicate a high spatial heterogeneity in b values within the study area. The northwestern and southeastern regions exhibit higher b values. Along the Haiyuan fault zone, the central rupture zone of the Haiyuan earthquake has relatively higher b values than other regions of this fault zone, which is possibly related to the sufficient release of stress during the main rupture of the Haiyuan earthquake. The b values vary from high in the west to low in the east along the Zhongwei fault. On the West Qinling fault zone, the epicenter of the recent Minxian–Zhangxian earthquake is associated with a low b value. In general, regions with low b values correspond well to areas with moderate–strong seismic events in the past 50 years. The spatial differences in b values may reflect variances in seismic hazards among fault zones and regions within the same fault zone.

There have been reports about anomalies in mobile geomagnetic data before earthquakes; however, whether it can be used as an indicator for identifying potential earthquake areas was not be explored. In this study, we propose two parameters for earthquake forecasting based on annual mobile geomagnetic observation data. The spatial horizontal and three components’ changes are calculated in each year and then used to forecast moderate–large earthquakes (M ≥ 5.0) in southwest China in the subsequent period. It is found that earthquakes are more likely to occur in low H- or F-value regions. We statistically assess their forecasting performance by using Molchan’s error diagram, and the results indicate that there is considerable precursory information in the spatial H and F values. It is concluded that mobile geomagnetic observations might be useful in middle-term earthquake forecasts in the study area. We discuss the physical mechanisms of H and F values to explain their reasonability. The methodology proposed in this study could be helpful in finding out the optimal solution for annual mobile geomagnetic measurements for middle-term earthquake forecasting.

One important question in earthquake prediction is whether a moderate or large earthquake will be followed by an even bigger one. Through temporal b-value evolution analysis, the traffic light system can be used to estimate if an earthquake is a foreshock. However, the traffic light system does not take into account the uncertainty of b-values when they constitute a criterion. In this study, we propose an optimization of the traffic light system with the Akaike Information Criterion (AIC) and bootstrap. The traffic light signals are controlled by the significance level of the difference in b-value between the sample and the background rather than an arbitrary constant. We applied the optimized traffic light system to the 2021 Yangbi earthquake sequence, which could be explicitly recognized as foreshock–mainshock–aftershock using the temporal and spatial variations in b-values. In addition, we used a new statistical parameter related to the distance between earthquakes to track earthquake nucleation features. We also confirmed that the optimized traffic light system works on a high-resolution catalog that includes small-magnitude earthquakes. The comprehensive consideration of b-value, significance probability, and seismic clustering might improve the reliability of earthquake risk judgment.