多源数据联合反演的2022年门源MW6.6地震同震破裂特征

doi:10.12196/j.issn.1000-3274.2025.01.007

摘要/Abstract

摘要： 收集并处理了2022年门源M_W6.6震中周边的高频GNSS、近场强震动和InSAR等多源观测数据, 初步获得了同震位移波形和InSAR形变场。使用高频GNSS数据快速获取的断层破裂特征表明, 此次地震以左旋走滑运动为主, 冷龙岭断层最大滑动量达3.9 m, 对应滑动深度位于1 km附近; 托莱山断层最大滑动量达2.1 m, 对应滑动深度位于1 km附近。结合高频GNSS、近场强震动和InSAR等多源数据进行联合反演, 结果显示冷龙岭断层最大滑动量为3.8 m, 对应滑动深度位于3.2 km附近; 托莱山断层最大滑动量为1.2 m, 对应滑动深度位于2 km附近。与仅使用高频GNSS和InSAR数据的反演结果相比, 加入近场强震动数据的多源数据联合反演结果更加精确。破裂过程和震源时间函数的分析表明, 此次地震持续时间为14 s, 能量释放主要集中在前9.5 s, 第5 s时地震矩释放速率达到峰值后逐渐减慢, 地震矩总释放量为1.33×10¹⁹ N·m, 对应的矩震级为M_W6.63。

关键词: 2022年门源M_W6.6地震, 高频GNSS, 多源数据, 破裂过程

Abstract: We collected and processed multi-source observational data, including high-rate GNSS, near-field strong motion, and InSAR data, from the area surrounding the epicenter of the 2022 Menyuan M_W6.6 earthquake, to reveal the preliminary results of coseismic displacement waveforms and InSAR deformation fields. Using high-rate GNSS data to quickly obtain fault rupture characteristics, we found that the earthquake was left-lateral strike-slip. The Lenglongling fault exhibited a maximum slip of 3.9 m at a depth of approximately 1 km, while the Tuolaishan fault had a maximum slip of 2.1 m at a similar depth. By combining high-rate GNSS, near-field strong motion, and InSAR data in a joint inversion, the Lenglongling fault’s maximum slip was determined as 3.8 m at a depth of 3.2 km, and the Tuolaishan fault’s maximum slip was 1.2 m at a depth of 2 km. The inclusion of near-field strong motion data in the multi-source joint inversion provided more accurate results compared to existing inversions using only high-rate GNSS and InSAR data. Analysis of the rupture process and source time function indicated that the earthquake lasted 14 seconds, with energy release concentrated in the first 9.5 seconds. The seismic moment release rate peaked at 5 seconds and then gradually slowed down, with a total release of 1.33×10¹⁹ N·m, corresponding to a moment magnitude M_W6.63.

Key words: The 2022 Menyuan M_W6.6 earthquake, High-rate GNSS, Multi-source data, Rupture process

中图分类号:

P315.7

杨宸, 苏小宁, 高志钰, 黄传超. 多源数据联合反演的2022年门源M_W6.6地震同震破裂特征[J]. 地震, 2025, 45(1): 93-110.

YANG Chen, SU Xiao-ning, GAO Zhi-yu, HUANG Chuan-chao. Joint Inversion of Multi-source Data for the Coseismic Rupture Characteristics of the 2022 Menyuan M_W6.6 Earthquake[J]. EARTHQUAKE, 2025, 45(1): 93-110.

参考文献

[1] He X H, Zhang Y P, Shen X Z, et al. Examination of the repeatability of two M_S6.4 Menyuan earthquakes in Qilian-Haiyuan fault zone (NE Tibetan Plateau) based on source parameters[J]. Physics of the Earth and Planetary Interiors, 2020, 299: 106408.
[2] 单新建, 尹昊, 刘晓东, 等. 高频GNSS实时地震学与地震预警研究现状[J]. 地球物理学报, 2019, 62(8): 3043-3052.
SHAN Xin-jian, YIN Hao, LIU Xiao-dong, et al. High-rate real-time GNSS seismology and early warning of earthquakes[J]. Chinese Journal of Geophysics, 2019, 62(8): 3043-3052 (in Chinese).
[3] 陈运泰. 地震预测: 回顾与展望[J]. 中国科学(D辑), 2009, 39(12): 1633-1658.
CHEN Yun-tai. Earthquake prediction: Retrospect and prospect[J]. Science in China (Series D), 2009, 39(12): 1633-1658 (in Chinese).
[4] Brown H M, Allen R M, Hellweg M, et al. Development of the ElarmS methodology for earthquake early warning: Realtime application in California and offline testing in Japan[J]. Soil Dynamics and Earthquake Engineering, 2011, 31(2): 188-200.
[5] Boore D M. Effect of baseline corrections on displacements and response spectra for several recordings of the 1999 Chi-Chi, Taiwan, earthquake[J]. Bulletin of the Seismological Society of America, 2001, 91(5): 1199-1211.
[6] 孟国杰, 苏小宁, 王振, 等. 利用近场高频GPS、强地面运动和远场地震波形数据联合反演2008年汶川M_S8.0地震的震源时空破裂过程[J]. 地震, 2018, 38(2): 11-27.
MENG Guo-jie, SU Xiao-ning, WANG Zhen, et al. Joint inversion for the rupture process of the 2008 Wenchuan M_S8.0 earthquake from 1 Hz GPS, strong motion and teleseismic data[J]. Earthquake, 2018, 38(2): 11-27 (in Chinese).
[7] 高志钰. 基于高频GNSS与合成地震的强震破裂及预警研究[D]. 北京: 中国地震局地质研究所, 2022.
GAO Zhi-yu. Research on rupture and early warning of strong earthquakes based on high-rate GNSS and synthetic earthquakes[D]. Beijing: Institute of Geology, China Earthquake Administration, 2022 (in Chinese).
[8] Gao Z Y, Li Y C, Shan X J, et al. Testing a prototype earthquake early warning system: A retrospective study of the 2021 M_W7.4 Maduo, Tibet, earthquake[J]. Seismological Research Letters, 2022, 93(3): 1650-1659.
[9] Shan X J, Li Y C, Wang Z J, et al. GNSS for quasi-real-time earthquake source determination in eastern Tibet: A prototype system toward early warning applications[J]. Seismological Research Letters, 2021, 92(5): 2988-2997.
[10] Huang C C, Zhang G H, Zhao D Z, et al. Rupture process of the 2022 M_W6.6 Menyuan, China, earthquake from joint inversion of accelerogram data and InSAR measurements[J]. Remote Sensing, 2022, 14(20): 5104.
[11] 李煜航, 梁诗明, 郝明, 等. 2022年1月8日门源M_S6.9地震同震位移场及其发震断层形变破裂特征[J]. 地球物理学报, 2023, 66(2): 589-601.
LI Yu-hang, LIANG Shi-ming, HAO Ming, et al. Coseismic displacement field of Menyuan M_S6.9 earthquake on January 8, 2022 and its implications for rupture characters of seismogenic faults[J]. Chinese Journal of Geophysics, 2023, 66(2): 589-601 (in Chinese).
[12] 吕明哲, 陈克杰, 柴海山, 等. 联合InSAR和高频GNSS位移波形反演2022年青海门源M6.9地震同震破裂过程[J]. 地球物理学报, 2022, 65(12): 4725-4738.
LÜ Ming-zhe, CHEN Ke-jie, CHAI Hai-shan, et al. Joint inversion of InSAR and high-rate GNSS displacement waveforms for the rupture process of the 2022 Qinghai Menyuan M6.9 earthquake[J]. Chinese Journal of Geophysics, 2022, 65(12): 4725-4738 (in Chinese).
[13] Wang R, Schurr B D, Milkereit C, et al. An improved automatic scheme for empirical baseline correction of digital strong-motion records[J]. Bulletin of the Seismological Society of America, 2011, 101(5): 2029-2044.
[14] 单新建, 李彦川, 高志钰, 等. 2022年泸定M_S6.8地震同震形变特征及周边强震危险性[J]. 科学通报, 2023, 68(8): 944-953.
SHAN Xin-jian, LI Yan-chuan, GAO Zhi-yu, et al. Coseismic deformation of the 2022 Luding M_S6.8 earthquake and seismic potential along adjacent major faults[J]. Chinese Science Bulletin, 2023, 68(8): 944-953 (in Chinese).
[15] 刘晓东. 强震动数据在地震P波预警中的应用[D]. 青岛: 中国石油大学(华东), 2019.
LIU Xiao-dong. Application of strong-motion data in earthquake P-wave early warning[D]. Qingdao: China University of Petroleum (East China), 2019 (in Chinese).
[16] 李振洪, 韩炳权, 刘振江, 等. InSAR数据约束下2016年和2022年青海门源地震震源参数及其滑动分布[J]. 武汉大学学报(信息科学版), 2022, 47(6): 887-897.
LI Zhen-hong, HAN Bing-quan, LIU Zhen-jiang, et al. Source parameters and slip distributions of the 2016 and 2022 Menyuan, Qinghai earthquakes constrained by InSAR observations[J]. Geomatics and Information Science of Wuhan University, 2022, 47(6): 887-897 (in Chinese).
[17] Geng J H, Chen X Y, Pan Y X, et al. PRIDE PPP-AR: An open-source software for GPS PPP ambiguity resolution[J]. GPS Solutions, 2019, 23(4): 1-10.
[18] Geng J H, Zhang Q Y, Li G C, et al. Observable-specific phase biases of Wuhan multi-GNSS experiment analysis center’s rapid satellite products[J]. Satellite Navigation, 2022, 3(3): 91-105.
[19] 方荣新. 高采样率GPS数据非差精密处理方法及其在地震学中的应用研究[D]. 武汉: 武汉大学, 2010.
FANG Rong-xin. High-rate GPS data non-difference precise processing and its application on seismology[D]. Wuhan: Wuhan University, 2010 (in Chinese).
[20] 张小红, 李星星, 李盼. GNSS精密单点定位技术及应用进展[J]. 测绘学报, 2017, 46(10): 1399-1407.
ZHANG Xiao-hong, LI Xing-xing, LI Pan. Review of GNSS PPP and its application[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(10): 1399-1407 (in Chinese).
[21] Li Y J, Liu S F, Chen L W, et al. Mechanism of crustal deformation in the Sichuan-Yunnan region, southeastern Tibetan Plateau: Insights from numerical modeling[J]. Journal of Asian Earth Sciences, 2017, 146: 142-151.
[22] Li Z C, Zang J F, Fan S J, et al. Real-time source modeling of the 2022 M_W6.6 Menyuan, China earthquake with high-rate GNSS observations[J]. Remote Sensing, 2022, 14(21): 5378.
[23] 李瑜, 刘静, 梁宏, 等. 全球定位系统测定的尼泊尔M_W7.8级地震同震位移[J]. 科学通报, 2015, 60(36): 3606-3616.
LI Yu, LIU Jing, LIANG Hong, et al. Co-seismic displacement field associated with the 25 April, 2015 M_W7.8 Nepal earthquake recorded by Global Positioning System[J]. Chinese Science Bulletin, 2015, 60(36): 3606-3616 (in Chinese).
[24] Boore D M, Stephens C D, Joyner W B. Comments on baseline correction of digital strong-motion data: Examples from the 1999 Hector Mine, California, earthquake[J]. Bulletin of the Seismological Society of America, 2002, 92(4): 1543-1560.
[25] Lin Y Z, Zong Z H, Tian S Z, et al. A new baseline correction method for near-fault strong-motion records based on the target final displacement[J]. Soil Dynamics and Earthquake Engineering, 2018, 114: 27-37.
[26] Rosen P A, Gurrola E, Sacco G F, et al. The InSAR scientific computing environment[C]. EUSAR 2012: 9th European conference on synthetic aperture radar. VDE, 2012: 730-733.
[27] Farr T G, Rosen P A, Caro E, et al. The shuttle radar topography mission[J]. Reviews of Geophysics, 2007, 45(2): RG2004.
[28] Goldstein R M, Werner C L. Radar interferogram filtering for geophysical applications[J]. Geophysical Research Letters, 1998, 25(21): 4035-4038.
[29] Pepe A, Lanari R. On the extension of the minimum cost flow algorithm for phase unwrapping of multitemporal differential SAR interferograms[J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(9): 2374-2383.
[30] Yu C, Li Z H, Penna N T, et al. Generic atmospheric correction model for interferometric synthetic aperture radar observations[J]. Journal of Geophysical Research: Solid Earth, 2018, 123(10): 9202-9222.
[31] Jónsson S, Zebker H, Segall P, et al. Fault slip distribution of the 1999 M_W7.1 Hector Mine, California, earthquake, estimated from satellite radar and GPS measurements[J]. Bulletin of the Seismological Society of America, 2002, 92(4): 1377-1389.
[32] 潘家伟, 李海兵, Marie-Luce Chevalier, 等. 2022年青海门源M_S6.9地震地表破裂带及发震构造研究[J]. 地质学报, 2022, 96(1): 215-231.
PAN Jia-wei, LI Hai-bing, Marie-Luce Chevalier, et al. Coseismic surface rupture and seismogenic structure of the 2022 M_S6.9 Menyuan earthquake, Qinghai Province, China[J]. Acta Geologica Sinica, 2022, 96(1): 215-231 (in Chinese).
[33] Fan L P, Li B R, Liao S R, et al. High-precision relocation of the aftershock sequence of the January 8, 2022, M_S6.9 Menyuan earthquake[J]. Earthquake Science, 2022, 35(2): 138-145.
[34] 李智敏, 盖海龙, 李鑫, 等. 2022年青海门源M_S6.9级地震发震构造和地表破裂初步调查[J]. 地质学报, 2022, 96(1): 330-335.
LI Zhi-min, GAI Hai-long, LI Xin, et al. Seismogenic fault and coseismic surface deformation of the Menyuan M_S6.9 earthquake in Qinghai, China[J]. Acta Geologica Sinica, 2022, 96(1): 330-335 (in Chinese).
[35] Melgar D, Bock Y. Kinematic earthquake source inversion and tsunami runup prediction with regional geophysical data[J]. Journal of Geophysical Research: Solid Earth, 2015, 120(5): 3324-3349.
[36] Zhu L P, Rivera L A. A note on the dynamic and static displacements from a point source in multilayered media[J]. Geophysical Journal International, 2002, 148(3): 619-627.
[37] Wang C S, Ding X L, Li Q C, et al. Adaptive regularization of earthquake slip distribution inversion[J]. Tectonophysics, 2016, 675: 181-195.
[38] Melgar Moctezuma D. Seismogeodesy and rapid earthquake and tsunami source assessment[D]. California: University of California, San Diego, 2014.
[39] Akaike H. Likelihood and the Bayes procedure[M]. New York: Springer New York, 1998.
[40] Fukahata Y, Nishitani A, Matsu’ura M. Geodetic data inversion using ABIC to estimate slip history during one earthquake cycle with viscoelastic slip-response functions[J]. Geophysical Journal International, 2004, 156(1): 140-153.
[41] 余鹏飞, 陈威, 乔学军, 等. 基于多源SAR数据的2022年门源M_S6.9地震同震破裂模型反演研究[J]. 武汉大学学报(信息科学版), 2022, 47(6): 898-906.
YU Peng-fei, CHEN Wei, QIAO Xue-jun, et al. Slip model of the 2022 Menyuan M_S6.9 earthquake constrained by mulit-source SAR data[J]. Geomatics and Information Science of Wuhan University, 2022, 47(6): 898-906 (in Chinese).
[42] Wessel P, Smith W H F, Scharroo R, et al. Generic mapping tools: Improved version released[J]. Eos, Transactions American Geophysical Union, 2013, 94(45): 409-410.