Seismogenic Fault Research Articles

An exploration of potentially reversible controls on millennial-scale variations in the slip rate of seismogenic faults: Linking structural observations with variable earthquake recurrence patterns

Paleoseismic studies show that faults within a fault system may trade off slip over time, with mechanically complementary faults displaying alternating fast- and slow periods. Each of these periods spans multiple seismic cycles, and typically involves ~20-25m of slip. This suggests that the relative strength (or tendency to slip) of individual faults varies, over time and displacement scales larger than those of individual seismic cycles. The mechanisms responsible for these strength variations must: affect rocks in the strongest portion of the fault (the brittle-ductile transition) as this likely controls the overall slip rate of the fault; be reversible (or able to be counteracted) on a cyclical basis; provide a negative feedback that operates to change the fault from its current state; and have a measurable effect on fault strength over a time or length scale that corresponds to the observed fast and slow periods of fault slip. In this paper, we systematically explore 19 potentially weakening and 11 potential strengthening mechanisms and evaluate them in light of these criteria. This analysis reveals a relatively small subset of mechanisms that could account for the observed behavior, leading us to suggest a possible model for fault strength evolution.

Evaluating Coseismic Landslide Susceptibility Following the 2022 Luding Earthquake: A Comparative Analysis of Six Displacement Regression Models Integrating Epicentral and Seismogenic Fault Distances within the Permanent-Displacement Framework

Coseismic landslides have the potential to cause catastrophic disasters. Thus, it is of crucial importance to conduct a comprehensive regional assessment of susceptibility to coseismic landslides. This study rigorously interprets 13,759 coseismic landslides triggered by the 2022 Luding earthquake within the seismic zone. Employing the Newmark method, we systematically assess the susceptibility to coseismic landslides through the application of six distinct displacement regression models. The efficacy of these models is validated against the actual landslide inventory using the area under the receiver operating characteristic (ROC) curve. A hazard map of coseismic landslides is generated based on the displacement regression model with the highest degree of fit. The results show that Moxi Town, Detuo Town, the flanks of the Daduhe River, Wandonghe River, Hailuogou River, and Yanzigou River are high-susceptibility areas for coseismic landslides. This study explores factors influencing model fit, revealing that the inclusion of the epicentral distance and the distance to the seismogenic fault in displacement prediction enhances model performance. Nevertheless, in close proximity to fault zones, the distance to the seismogenic fault exerts a more significant influence on the spatial distribution density of coseismic landslides compared to the epicentral distance. Conversely, in regions situated further from fault zones, the epicentral distance has a greater impact on the spatial distribution density of coseismic landslides compared to the distance to the seismogenic fault. These findings contribute to a nuanced understanding of coseismic landslide susceptibility and offer valuable insights for future Newmark method-based coseismic landslide displacement calculations.

Asymmetric Bilateral Rupture of the 2021 Mw 7.4 Maduo Earthquake in China and Association with Seismogenic Fault Structures

Asymmetric Bilateral Rupture of the 2021 Mw 7.4 Maduo Earthquake in China and Association with Seismogenic Fault Structures

Reappraising the seismogenic potential of a low-strain rate region: Active faulting in the eastern Siena Basin (southern Tuscany, Italy)

We investigated the active tectonics and earthquake potential of the eastern Siena Basin, a slowly deforming portion of southern Tuscany in the inner Northern Apennines. This region hosts several historical settlements and valuable cultural heritage, but also frequent background seismicity and rare damaging earthquakes in the Mw range 5.0–6.2. We describe in detail an active, capable, and seismogenic fault system that we identified in the eastern Siena Basin, a few kilometers south-east of the city of Siena, thanks to the presence of an active quarry (Cava Capanni) that exploits travertines of Middle Pleistocene-Holocene age. Travertines are unique rock masses that may preserve living evidence of active and seismogenic faulting, thus providing remarkable seismotectonic insight. The active fault system consists of at least two segments rupturing travertines younger than 45 ka, with a cumulative vertical displacement of 111 cm, and an estimated minimum slip rate of 0.02–0.03 mm/y. We maintain that this displacement is the result of at least three coseismic movements accompanied by clastic dykes injected within the fault damage zone due to liquefaction phenomena. The fault system is seen to extend east of the quarry, affecting Pliocene and Mesozoic deposits.The Cava Capanni fault system is evidence of a poorly understood but potentially seismogenic tectonic mechanism of regional extent. Its orientation and kinematics are compatible with the activity of faults that are oriented obliquely or orthogonally to the main chain axis, in contrast with the setting of the axial and outer zone of the Northern Apennines, where extension and compression are accommodated by Apennines-parallel faults.

Reactivated Seismogenic Faults and Earthquake Source Mechanisms in the Snyder Area of Texas

Abstract Stretching across New Mexico and Texas of the United States, the greater Permian basin is composed of two subunits—the Delaware and the Midland basins. Induced seismicity in the greater Permian basin has significantly increased since 2008, which has revealed previously unmapped seismogenic structures in several geographic regions. Among them, the Snyder area of northwest Texas has a long history of oil and gas activities, resulting in a higher rate of induced seismicity. In this study, we investigated these previously unknown seismogenic structures using three main approaches: (1) relocated and delineated seismicity, (2) performed waveform moment tensor inversion to determine earthquake source mechanisms, as well as (3) conducted stress inversion to assess the stress state. The results show that the overall depth range of seismicity is 0–5.5 km and concentrated in a range of 2–3 km below mean sea level, in the top portion of the crystalline basement. As we have determined 297 source mechanisms, their collective pattern presents a mix of strike-slip and normal faulting, suggesting an extensional strain field at the edge of the Midland basin. We have identified nine significant seismogenic episodes by distinctive increases of seismic moment release in 2017–March 2024. The results also demonstrate a temporal variation of b-value spanning across the seismogenic episodes, associated with the progression of fault reactivation initiated by fluid injection.

Source Parameters and Seismogenic Fault Model of the 2024 Mw 7.0 Wushi (Xinjiang, China) Earthquake Revealed by InSAR Observations

Source Parameters and Seismogenic Fault Model of the 2024 Mw 7.0 Wushi (Xinjiang, China) Earthquake Revealed by InSAR Observations

Identification of the active faults and seismotectonic zonation of Laos territory

In this study, the main active faults in the territory of Laos were identified by analyzing the spatial relationship between the distributions of neo-tectonic faults and earthquake epicenters. The map of neo-tectonic faults was built by integrating the results of neo-tectonic faults research using geological-geomorphological data together with the lineament map obtained from remote sensing analysis. Nontectonic lineaments were eliminated by correlating the spatial distribution of the lineament field with a topographic map, DEM, and geological-geomorphological data. The earthquake data, including 4416 events in Laos and its surroundings, were collected from different sources: the International Seismological Center (ISC), the earthquakes recorded by the local seismic network in Laos, the seismic data in Vietnam, and the earthquake catalog provided by the Thailand Meteorological Department (TMD). Among these, 820 events were located using the hypocenter method, and the local network recorded the data. The magnitude conversion was applied to get a unified scale Mw. The catalog of 1617 main shocks obtained after eliminating foreshocks and aftershocks using the declustering technique was used for a spatial correlation with the neotectonic fault distribution to identify active faults. A total of 14 main active fault zones in the Laos territory were defined. Most are also seismogenic faults with Mw ≥ 5.0 occurring along their trace. Considering the characteristics of seismic activity and the active and neotectonic faults, the territory of Laos can be divided into six seismotectonic zones according to the decreasing level of seismic activity: the Western, the Northeastern Samnua, the Phongsali, the South Truong Son, the North Truong Son, and the Khorat zones. Each zone is characterized by relative homogeneity in the seismic activity and the characteristics of active and neotectonic faults.

A SHAP-enhanced XGBoost model for interpretable prediction of coseismic landslides

In the coseismic landslide hazard assessment (CLHA), advanced machine learning (ML) models have garnered significant attention due to their effectiveness in handling the complex relationships between landslides and various influencing factors. However, explaining the decision-making mechanisms of machine learning models that predict landslide spatial distribution based on these influencing factors remains challenging. This study compares the predictive performance of four models—XGBoost, RF, LR, and SVM—optimized using the TPE algorithm, and introduces the SHAP algorithm into the XGBoost model to achieve both global and local interpretations of CLHA. In various tests, the optimized XGBoost model demonstrated the best predictive performance, achieving an accuracy of 0.864 and an AUC value of 0.886. Global interpretations indicate that the occurrence of coseismic landslides is primarily influenced by triggering factors such as hypocentral distance and distance from the seismogenic fault. Terrain roughness and elevation, on the other hand, make significant contributions among the conditioning factors. Single-factor dependence plots indicate that the contribution of individual factors to landslides varies across different ranges of their feature values. Analysis of two-factor dependence plots reveals that interactions between factors are also crucial in influencing the occurrence of landslides. Combining field surveys with local interpretations confirms significant variations in the contributions of influencing factors within local ranges. The main innovation of this study lies in the integration of the SHAP algorithm into the CLHA model, revealing the decision-making mechanisms of the model for spatial prediction of coseismic landslides.

Understanding of landslides induced by 2022 Luding earthquake, China

On September 5, 2022, at least 10,855 landslides had been triggered by a magnitude Mw 6.7 (Ms 6.8) earthquake on the eastern margin of the Tibetan Plateau. Unfortunately, a detailed analysis of the spatial patterns of landslides in the eastern margin of the Baryan Har block is lacking. The observations show that the highest landslide concentrations are distributed along the seismogenic fault (Moxi fault) and Dadu River valley, coinciding with the effects of the hanging wall and microepicenter. Seismogenic tectonics controlled the regional distribution of new landslides, and the local topography influenced the detailed positions on the slopes. The total landslide mass wasting volume was 223.1 × 106 m3, and the maximum occurred in the Wandong Basin (value of 74 × 106 m3). Thirty landslide dams were temporarily existing. Although some local collapses occurred at the toe of the Hailuogou glacier, seismic shaking had no obvious influence on the overall stability of the glacier. A post debris flow assessment indicates that some large basins contained much loose material and that some steep small basins had high debris flow susceptibility. On the eastern margin of the Bayan Har block, the landslide-triggering thrust and strike-slip events both follow the distributions of the hanging wall.

Coseismic deformation and seismogenic structure of the 2024 Hualien Earthquake measured by InSAR and GNSS

On April 3, 2024, an M7.3 earthquake occurred in the offshore area of Hualien County, Taiwan, China. The seismogenic structure at the epicentral location was highly complex, and studying this earthquake is paramount for understanding regional fault activity. In this study, we employed ascending and descending orbit Sentinel-1 Synthetic Aperture Radar (SAR) data and utilized differential interferometry (InSAR) technique to obtain the co-seismic deformation field of this event. The line-of-sight deformation field revealed that the main deformation caused by this earthquake was predominantly uplift, with maximum uplift values of approximately 38.8 ​cm and 46.1 ​cm for the ascending and descending orbits, respectively. By integrating the three-dimensional GNSS co-seismic deformation field, we identified the seismogenic fault located in the offshore thrust zone east of Hualien, trending towards the northwest. The fault geometry parameters, obtained through the inversion of an elastic half-space homogeneous model, indicated an optimal fault strike of 196°, a dip angle of 30.9°, and an average strike-slip of 0.4 ​m and dip-slip of −2.6 ​m. This suggests that the predominant motion along the seismogenic fault is thrusting. The distribution of post-seismic Coulomb stress changes revealed that aftershocks mainly occurred in stress-loaded regions. However, stress loading was observed along the northern segment of the Longitudinal Valley Fault, with fewer aftershocks. This highlights the importance of closely monitoring the seismic hazard associated with this fault segment.

Three-dimensional fault model and features of chained hazards of the Luding MS 6.8 earthquake, Sichuan Province, China

The MS 6.8 Luding earthquake in 2022 is located on the NNW-trending Moxi segment of the Xianshuihe fault with left-lateral strike-slip behavior. This area is where the Xianshuihe, Anninghe, Daliangshan and Longmenshan faults intersect. China Earthquake Administration has identified that intersection area, among the Moxi segment of the Xianshuihe fault, the Anninghe fault, the Daliangshan fault and the southern part of the Longmenshan fault, as a high-magnitude earthquake hazard area. According to existing data on the Luding earthquake, including the focal parameters, the spatial distribution of re-located aftershocks, dominated azimuth of the earthquake intensities and earthquake-induced ground fissures, we built a 3D earthquake fault model. We found that two discontinuous NNW-trending vertical strike-slip faults with left stepping were the seismogenic faults of the Luding earthquake. Its coseismic left-lateral dislocation triggered transtensional slips and aftershocks on the NW-trending secondary faults at its northernmost tensile area. Meanwhile, local crustal coseismic shortening on the side of Mt. Gongga triggered the aftershocks on the NE- and NW-trending secondary conjugated strike-slip faults, which were confirmed by GNSS observations and InSAR deformation field around the epicenter. This earthquake rupturing pattern also controlled the spatial distribution of the earthquake intensity IX area and earthquake chain hazards. The Coulomb stress calculation shows that the Luding earthquake increases the risk of high-magnitude earthquake occurrence on the southernmost part of the Xianshuihe fault and the Anninghe fault. Finally, we suggested doing good monitoring of the Anninghe fault and the southernmost part of the Xianshuihe fault and avoiding active faults with seismogenic capacity and areas prone to earthquake-chained hazards during the site selection and planning of reconstruction.

Strong controlling effect of stress evolution on the 2022 Ms5.0 Honghe earthquake sequence

Understanding stress evolution patterns as a response to earthquake ruptures at geologically complex tectonic faults is vital because of the role of fault geometry as a source for the stress evolutionary constraints. Here, we analyze the 2022 Ms5.0 Honghe earthquake sequence and calculate the tectonic stress distribution of the two Ms. ≥ 3.5 earthquakes in this sequence. Results indicate that the focal mechanism type of the sequence obtained corresponds to strike-slip motion with an ESE-oriented strike and a steeply dipping NE-oriented nodal plane. The focal region is subjected to NNW-oriented horizontal compression and ENE-oriented horizontal tension. We find that the adjacent Ailaoshan fault constituted the major seismogenic fault of the mainshock and the regional stress field exerted a strong controlling effect on the associated postseismic events. Our results suggest that the stabilization of tectonic faults may help to enhance the effects of stress accumulation on the occurrence of medium-to-strong earthquakes.

Uncovering a Seismogenic Fault in Southern Iran through Co-Seismic Deformation of the Mw 6.1 Doublet Earthquake of 14 November 2021

On 14 November 2021, a doublet earthquake, each event of which had an Mw of 6.1, struck near Fin in the Simply Folded Belt (SFB) in southern Iran. The first quake occurred at 12:07:04 UTC, followed by a second one just a minute and a half later. The SFB is known for its blind thrust faults, typically not associated with surface ruptures. These earthquakes are usually linked to the middle and lower layers of the sedimentary cover. Identifying the faults that trigger earthquakes in the region remains a significant challenge and is subject to high uncertainty. This study aims to identify and determine the fault(s) that may have caused the doublet earthquake. To achieve this goal, we utilized the DInSAR method using Sentinel-1 to detect deformation, followed by finite-fault inversion and magnetic interpretation to determine the location, geometry, and slip distribution of the fault(s). Bayesian probabilistic joint inversion was used to model the earthquake sources and derive the geometric parameters of potential fault planes. The study presents two potential fault solutions—one dipping to the north and the other to the south. Both solutions showed no significant difference in strike and fault location, suggesting a single fault. Based on the results of the seismic inversion, it appears that a north-dipping fault with a strike, dip, and rake of 257°, 74°, and 77°, respectively, is more consistent with the geological setting of the area. The fault plane has a width of roughly 3.6 km, a length of 13.4 km, and a depth of 5.6 km. Our results revealed maximum displacements along the radar line of sight reaching values of up to −360 mm in the ascending orbit, indicating an unknown fault with horizontal displacements at the surface ranging from −144 to 170 mm and maximum vertical displacements between −204 and 415 mm. Aeromagnetic data for Iran were utilized with an average flight-line spacing of 7.5 km. The middle of the data observation period was considered to apply the RTP filter, and the DRTP method was used. We calculated the gradient of the residual anomaly in the N-S direction due to the direction of the existing faults and folds. The gradient map identified the fault and potential extension of the observed anomalies related to a fault with an ENE-WSW strike, which could extend to the ~ E-W. We suggest that earthquakes occur in the sedimentary cover of the SFB where subsurface faulting is involved, with Hormuz salt acting as an important barrier to rupture. The multidisciplinary approach used in this study, including InSAR and magnetic data, underscores the importance of accurate fault characterization. These findings provide valuable insights into the seismic hazard of the area.

Deep reinforcement learning for inverting earthquake focal mechanism and its potential application to marine earthquakes

Earthquake data are one of the key means by which to explore our planet. At a large scale, the layered structure of the Earth is revealed by the seismic waves of natural earthquakes that go deep into its inner core. At a local scale, seismology for exploration has successfully been employed to discover massive fossil energies. As the volume of recorded seismic data becomes greater, intelligent methods for processing such a volume of data are eagerly anticipated. In particular, earthquake focal mechanisms are important for assessing the severity of tsunamis, characterizing seismogenic faults, and investigating the stress perturbations that follow a major earthquake. Here, we report a novel deep reinforcement learning method for inverting the earthquake focal mechanism. Unlike more typical deep learning applications, which require a large training dataset, a deep reinforcement learning system learns by itself. We demonstrate the validity and efficacy of the proposed deep reinforcement learning method by applying it to the Mw 7.1 mainshock of the Ridgecrest earthquakes in southern California. In the foreseeable future, deep learning technologies may greatly contribute to our understanding of the oceanographic process. The proposed method may help us understand the mechanism of marine earthquakes.

The 2023 Mw 6.8 Morocco Earthquake: A Lower Crust Event Triggered by Mantle Upwelling?

AbstractA M6.8 earthquake struck the High Atlas Mountains in Morocco on 8 September 2023, ending a 63‐year seismic silence. We herein attempt to clarify the seismogenic fault and explore the underlying mechanism for this seismic event based on multiple data sets. Utilizing probabilistic Bayesian inversion on interferometric radar data, we determine a seismogenic fault plane centered at a depth of 26 km, striking 251° and dipping 72°, closely aligned with the Tizi n’Test fault system. Given a hypocenter at the Moho depth, the joint inversion of radar and teleseismic data reveals that the rupture concentrates between depths of 12 and 36 km, offsetting the Mohorovičić discontinuity (Moho) at ∼32 km. Considering a strong link between magma activity and failure in lower crust, we propose that the triggering of the earthquake possibly was mantle upwelling that also supports the high topography.

Comprehensive Study on the 143 A.D. West Gangu Earthquake in the West Qinling Area, Northeastern Margin of Tibetan Plateau

The 143 A.D. west Gangu earthquake is documented to have occurred in the West Qinling area, which is located on the northeastern margin of the Tibetan Plateau. Initial limited historical records suggest the earthquake took place along the West Qinling fault (WQLF) in the western region of Gangu County. However, the absence of corresponding geological and geomorphological evidence has posed a considerable challenge in accurately quantifying parameters such as the precise location, magnitude, and seismogenic fault segment in earlier investigations. In this study, a comprehensive examination of multiple residual surface rupture zones within the macroseismic zone of this earthquake enabled the determination of the seismogenic structure, magnitude, and rupture zone scale through diverse methodologies, which include field geological investigations, chronology testing, Unmanned Aerial Vehicle (UAV) aerial surveying, and interpretation of landslides along the fault zone. The results reveal that the seismogenic structure of this seismic event is associated with the Zhangxian fault segment of the WQLF, also marked by a dense distribution of large landslides from Zhangxian to Yuanyangzhen. The epicenter was identified at the eastern end of the Zhangxian fault segment of the WQLF. Furthermore, the magnitude of the 143 A.D. west Gangu earthquake is estimated to be approximately Ms 7–7.3, with the residual surface rupture zone intermittently extending over about 22 km and a maximum horizontal dislocation along the rupture zone of 2.8 ± 0.5 m. This detailed investigation contributes foundational insights for further evaluating the seismic risk across various segments of the WQLF.

The 2022 Har Lake earthquake sequence highlights a complex fault system in the western Qilian Shan, northeastern Tibetan Plateau

SUMMARY The 2022 Har Lake earthquake sequence, which began in 2022 January and lasted for ∼70 d, jolted the Har Lake area, which is located in the western Qilian Shan, northeastern Tibetan Plateau. Two Mw > 5.5 earthquakes occurred during the earthquake sequence, among which the March 25 Mw 5.8 event is considered the largest event recorded in the area. However, determining the seismogenic faults of the earthquake sequence, as well as the detailed rupture features, is difficult due to the lack of geological data and near-field seismological observations. In this study, we use Sentinel-1 synthetic aperture radar (SAR) data to obtain the coseismic deformation field, identify possible ruptured faults and associated fault geometries, and further estimate detailed coseismic slip models of the two Mw > 5.5 earthquakes. The results show that the January 23 Mw 5.6 earthquake (Earthquake A) occurred on a N15° W-trending dextral-slip fault with a dip angle of ∼61°. For the March 25 Mw 5.8 earthquake (Earthquake B), the interferometric synthetic aperture radar (InSAR) data can be described by either an ∼N–S-trending dextral-slip fault or an ∼E–W-trending sinistral-slip fault. The ∼N–S-trending fault better describes the aftershock distribution, while the ∼E–W-trending model is more consistent with the regional geological setting. We suggest that the complex coseismic ruptures in the multiple-fault system are driven by widespread NE–SW-trending compression in the western Qilian Shan. This study demonstrates the importance of integrating geodetic and seismological observations to capture the full complexity of moderate earthquakes and further suggests potential seismic hazards in the Har Lake area.

Insights of using control theory for minimizing induced seismicity in underground reservoirs

Deep Geothermal Energy, Carbon Capture, and Storage and Hydrogen Storage have significant potential to meet the large-scale needs of the energy sector and reduce the CO2 emissions. However, the injection of fluids into the earth’s crust, upon which these activities rely, can lead to the formation of new seismogenic faults or the reactivation of existing ones, thereby causing earthquakes. In this study, we propose a novel approach based on control theory to address this issue. First, we obtain a simplified model of induced seismicity due to fluid injections in an underground reservoir using a diffusion equation in three dimensions. Then, we design a robust tracking control approach to force the seismicity rate to follow desired references. In this way, the induced seismicity is minimized while ensuring fluid circulation for the needs of renewable energy production and storage. The designed control guarantees the achievement of the control objectives even in the presence of system uncertainties and unknown dynamics. Finally, we present simulations of a simplified geothermal reservoir under different scenarios of energy demand to show the reliability and performance of the control approach, opening new perspectives for field experiments based on real-time regulators.

Source Models of the 2016 and 2022 Menyuan Earthquakes and Their Tectonic Implications Revealed by InSAR.

The Haiyuan fault system plays a crucial role in accommodating the eastward expansion of the Tibetan Plateau (TP) and is currently slipping at a rate of several centimeters per year. However, limited seismic activities have been observed using geodetic techniques in this area, impeding the comprehensive investigation into regional tectonics. In this study, the geometric structure and source models of the 2022 Mw 6.7 and the 2016 Mw 5.9 Menyuan earthquakes were investigated using Sentinel-1A SAR images. By implementing an atmospheric error correction method, the signal-to-noise ratio of the 2016 interferometric synthetic aperture radar (InSAR) coseismic deformation field was significantly improved, enabling InSAR observations with higher accuracy. The results showed that the reliability of the source models for those events was improved following the reduction in observation errors. The Coulomb stress resulting from the 2016 event may have promoted the strike-slip movement of the western segment of the Lenglongling fault zone, potentially expediting the occurrence of the 2022 earthquake. The coseismic slip distribution and the spatial distribution of aftershocks of the 2022 event suggested that the seismogenic fault may connect the western segment of the Lenglongling fault (LLLF) and the eastern segment of the Tuolaishan fault (TLSF). Additionally, the western segment of the surface rupture zone of the northern branch may terminate in the secondary branch close to the Sunan-Qilian fault (SN-QL) strike direction, and the earthquake may have triggered deep aftershocks and accelerated stress release within the deep seismogenic fault.

Seismogenic Fault Model for the 2021 Ms 6.4 Yangbi, China, Earthquake, Constraints from Multisource Data

Abstract Deciphering a comprehensive 3D fault model for the regions with moderate-to-strong earthquakes is crucial for understanding earthquake triggering mechanisms and assessing future seismic hazards. On 21 May 2021, a massive Ms 6.4 earthquake occurred in Yangbi, Dali City, China, near the northern Red River fault zone. Despite numerous studies conducted over the past two years, the seismogenic fault of this earthquake remains a topic of controversy. In this article, we refine the workflow for 3D construction of fault surfaces from Riesner et al. (2017) and used it for the Yangbi earthquake. We constructed a seismogenic fault model for the Yangbi earthquake and Caoping fault from the collected multisource data. One utilizes a combination of focal mechanisms and relocated hypocenters, whereas the other combines geological and geophysical data from the study area. Upon analyzing these two fault models and the relocated hypocenter data, we propose that the seismogenic fault in the Yangbi earthquake is an undiscovered blind fault or a secondary blind fault of the Weixi–Qiaohou fault, rather than the surface-emerging Caoping fault.