A high-resolution seismic catalog for the 2021 MS6.4/MW6.1 Yangbi earthquake sequence, Yunnan, China: Application of AI picker and matched filter

Zhou, Yijian; Ghosh, Abhijit; Fang, Lihua; Yue, Han; Zhou, Shuhua; Su, Youjin

doi:10.29382/eqs-2021-0031

Cited by 32 publications

(31 citation statements)

References 37 publications

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“…These results are consistent with those of Zhou et al. (2021), except a large discrepancy for EGF2. These relocations have no impact on the foregoing AMRF analysis, given the alignment adjustments made to the deconvolved signals.…”

Section: Discussionsupporting

confidence: 94%

“…With the hypocenter located at ∼10 km (8 km from the YEA catalog; 10 km from the CENC catalog with limited solution; 6.69 km from the high‐resolution catalog by Zhou et al. (2021), and 11 km relocated using handpicked P arrivals by Chen et al., 2022), the main slip during the M W 6.0 Yangbi mainshock is likely to be at depths around 6–12 km and any shallow slip is minor.…”

Section: Discussionmentioning

confidence: 99%

“…In the 2021 Yangbi sequence, most of the foreshocks and aftershocks, including the four relocated earthquakes, are distributed near the periphery of the main slip area of the mainshock, although the locations have large uncertainties (Figure S11 in Supporting Information S1). The relocation results of some studies (Long et al., 2021; Su et al., 2021; Zhang et al., 2022; Zhou et al., 2021) have shown that foreshocks and aftershocks are mainly shallower than the mainshock, indicating that coseismic slip with a down‐dip rupture may extend deeper than the foreshock and aftershock area. The augmented catalog of Zhou et al.…”

Section: Discussionmentioning

confidence: 99%

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Rupture Directivity of the 2021M_W6.0 Yangbi, Yunnan Earthquake

Gong

Kanamori

et al. 2022

JGR Solid Earth

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The 2021 MW 6.0 Yangbi, Yunnan strike‐slip earthquake occurred on an unmapped crustal fault near the Weixi‐Qiaoho‐Weishan Fault along the southeast margin of the Tibetan Plateau. Using near‐source broadband seismic data from ChinArray, we investigate the spatial and temporal rupture evolution of the mainshock using apparent moment‐rate functions (AMRFs) determined by the empirical Green's function (EGF) method. Assuming a 1D line source on the fault plane, the rupture propagated unilaterally southeastward (∼144°) over a rupture length of ∼8.0 km with an estimated rupture speed of 2.1 km/s to 2.4 km/s. A 2D coseismic slip distribution for an assumed maximum rupture propagation speed of 2.2 km/s indicates that the rupture propagated to the southeast ∼8.0 km along strike and ∼5.0 km downdip with a peak slip of ∼2.1 m before stopping near the largest foreshock, where three bifurcating subfaults intersect. Using the AMRFs, the radiated energy of the mainshock is estimated as ∼1.6×10130.25emnormalJ $1.6\times {10}^{13}\,\mathrm{J}$. The relatively low moment scaled radiated energy ER/M0 ${E}_{R}/{M}_{0}$ of 1.5 × 10−5 and intense foreshock and aftershock activity might indicate reactivation of an immature fault. The earthquake sequence is mainly distributed along a northwest‐southeast trend, and aftershocks and foreshocks are distributed near the periphery of the mainshock large‐slip area, suggesting that the stress in the mainshock slip zone is significantly reduced to below the level for more than a few overlapping aftershock to occur.

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Section: Discussionsupporting

confidence: 94%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Rupture Directivity of the 2021M_W6.0 Yangbi, Yunnan Earthquake

Gong

Kanamori

et al. 2022

JGR Solid Earth

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“…Such strategy gives reliable and highly complete detection, and thus, the catalog reaches a complete magnitude of M L 1.0 and a minimum magnitude of M L ‐1.0. The relocation process utilized cross‐correlated differential travel times, which provides sub‐sampling‐rate precision (<0.01‐s), leading to a relative location uncertainty of ∼10 m laterally and ∼20 m vertically in the hypoDD inversion process (Waldhauser, 2001; Zhou, Ghosh, et al., 2021). Note that the real location uncertainty is larger than that given by least‐square criteria.…”

Section: Methodsmentioning

confidence: 99%

Seismological Characterization of the 2021 Yangbi Foreshock‐Mainshock Sequence, Yunnan, China: More than a Triggered Cascade

et al. 2022

Self Cite

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Foreshocks are known as smaller earthquakes preceding the large mainshock (Jones & Molnar, 1979). Due to the neighboring location and temporal correlation, foreshocks are considered as a possible precursory phenomenon, for example, the success prediction of 1975 M w 7.0 Haicheng earthquake largely relies on the ∼1-day foreshock activity (Wang et al., 2006). Traditionally, two end-member models are proposed to explain the triggering relationship between the foreshocks and mainshock (Dodge et al., 1996): the cascade model and the pre-slip model. The cascade model describes the seismic sequence as the cascade failure of isolated asperities, where each event is triggered by the stress transfer from the previous earthquake (Ellsworth & Bulut, 2018;Felzer et al., 2004;

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“…Different from the methods above that use only manually designed features for quality control, deep-learning-based methods can automatically extract abundant features from labeled receiver functions. Deep learning has made significant progress not only in the field of artificial intelligence over the last decade (LeCun et al, 2015), such as natural language processing and computer vision, but also in a variety of seismic applications (e.g., Kong et al, 2018;Zhou et al, 2021). In brief, deep learning aims to automatically build a mapping function from input to output with a given dataset.…”

Section: Introductionmentioning

confidence: 99%

Deep learning for quality control of receiver functions

et al. 2022

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Receiver function has been routinely used for studying the discontinuity structure in the crust and upper mantle. The manual quality control of receiver functions, which plays a key role in high-quality data selection and accurate structural imaging, has been challenged by today’s booming data volumes. Traditional automatic quality control methods usually require tuning hyperparameters and fail to generalize to low signal-to-noise ratio data. Deep learning has been increasingly used to deal with extensive seismic data. However, it generally requires a manually labeled dataset, and its performance is highly related to the network design. In this study, we develop and compare four different deep learning network designs with manual and traditional quality control methods using 53293 receiver functions from three broadband seismic stations. Our results show that a combination of convolutional and long-short memory layers achieves the best performance of ∼91% accuracy. We also propose a fully automatic training schema that requires zero manually labeled receiver function yet achieves similar performance to that using carefully labeled ones. Compared with the traditional automatic method, our model retrieves ∼5 times more reliable receiver functions from relatively small earthquakes with magnitudes between 5.0 and 5.5. The average waveforms and H-κ stacking results of these receiver functions are comparable to those obtained by manual quality control from earthquakes with magnitudes larger than 5.5, which further demonstrates the validity of our method and indicates its potential for making use of smaller earthquakes in the receiver function analysis.

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A high-resolution seismic catalog for the 2021 MS6.4/MW6.1 Yangbi earthquake sequence, Yunnan, China: Application of AI picker and matched filter

Cited by 32 publications

References 37 publications

Rupture Directivity of the 2021M_W6.0 Yangbi, Yunnan Earthquake

Rupture Directivity of the 2021M_W6.0 Yangbi, Yunnan Earthquake

Seismological Characterization of the 2021 Yangbi Foreshock‐Mainshock Sequence, Yunnan, China: More than a Triggered Cascade

Deep learning for quality control of receiver functions

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A high-resolution seismic catalog for the 2021 MS6.4/MW6.1 Yangbi earthquake sequence, Yunnan, China: Application of AI picker and matched filter

Cited by 32 publications

References 37 publications

Rupture Directivity of the 2021MW6.0 Yangbi, Yunnan Earthquake

Rupture Directivity of the 2021MW6.0 Yangbi, Yunnan Earthquake

Seismological Characterization of the 2021 Yangbi Foreshock‐Mainshock Sequence, Yunnan, China: More than a Triggered Cascade

Deep learning for quality control of receiver functions

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Rupture Directivity of the 2021M_W6.0 Yangbi, Yunnan Earthquake

Rupture Directivity of the 2021M_W6.0 Yangbi, Yunnan Earthquake