情景地震震源特征对速度脉冲分布的影响——以虎牙断层为例

doi:10.3969/j.issn.0253-4967.2024.05.012

摘要/Abstract

摘要：

文中根据中国四川省平武—松潘地区的地质地貌特征和情景地震模型构建流程, 建立虎牙断层不同震源特征的情景地震, 并采用三维有限差分法进行计算。结合脉冲识别方法研究区域速度脉冲的分布特征, 与速度脉冲概率分布曲线进行拟合。结果表明: 1)强速度脉冲不仅会出现在断层在地表的投影区域附近, 也会由于破裂方向性效应在距震中较远处引发速度脉冲; 2)速度脉冲概率分布曲线的形状与模拟得到的速度脉冲分布特征相似, 但不同震源机制下的速度脉冲分布存在明显差异, 对于不同分量(如EW和NS), 拟合效果也存在偏差; 3)对于长周期结构, 可通过构造措施改变自振周期, 从而避开脉冲型地震动的主要周期范围。文中的研究成果能够用于长周期结构的抗震分析, 可为虎牙断裂附近区域重大工程的建设和地震危险性分析提供参考。

关键词: 情景地震：有限差分法, 虎牙断层, 速度脉冲, 分布概率

Abstract:

In August 1976, within a week, three earthquakes with a magnitude of 6.5 or higher occurred at the border of Songpan County and Pingwu County in Sichuan Province, China. The seismogenic structure of the three earthquakes is the Huya Fault. The Huya Fault is still a strong active fault, and there is still a possibility of major future earthquakes in the Songpan and Pingwu regions. Historical earthquake records only represent earthquakes that have occurred, and there is uncertainty in estimating earthquake motion using existing records, especially in near-fault areas without strong earthquake records. Estimating near-fault ground motion has become a research hotspot in the interdisciplinary field of seismology and engineering seismology in recent years. The research and methods differ from the design of earthquake motion methods for earthquake safety evaluation in engineering. They are developed by integrating earthquake source physics, seismic wave propagation theory, and engineering seismology. Based on the geological and geomorphological characteristics of the Songpan-Pingwu area in Sichuan Province and the process framework for constructing scenario earthquake models, we have developed three scenario earthquake source models with a magnitude of M_W7.0. These models include rupture models and source mechanisms related to the Huya Fault. The seismic source parameters were referenced from existing statistical models. Utilizing the three-dimensional finite difference method, we can simulate the long-term ground motion of scenario earthquakes for its facile discretization and computational efficiency. We set virtual observation stations within the calculated area, enabling the acquisition of velocity wave fields and waveforms across diverse earthquake scenarios. Besides, the velocity pulse identification method is combined to identify the seismic motion of the virtual station to study the distribution characteristics of regional velocity pulses. We use the pulse recognition method to identify velocity pulses of earthquake motion(observed or simulated earthquake motion). It can be summarized as a continuous wavelet transform of two orthogonal components of earthquake motion to determine whether it is a pulse. When the pulse index PI>0, the original record is determined to be a pulse, and the larger the PI, the stronger the pulse characteristics of the original record. When the pulse index PI<0, the original record is deemed nonpulse. This method can obtain the pulse amplitude and pulse period. Finally, the obtained results will be fitted with the probability distribution curve of velocity pulses to explore the impact of rupture mode and source mechanism on the distribution of velocity pulses. The results of this article indicate that: 1)The rupture mode is significant to the distribution of regional velocity pulses. For strike-slip faults, the velocity pulses caused by unilateral rupture mode are mainly in the E-W direction, and the peak value of the pulses does not exceed 50cm/s. The range of pulse distribution and the peak intensity of strong vibrations generated on the surface are smaller than the bilateral rupture mode. Strong velocity pulses not only appear near the projection area of faults on the surface but also trigger velocity pulses at a distance from the epicenter due to the directional effect of rupture. 2)The shape of the velocity pulse probability distribution curve is similar to the simulated velocity pulse distribution characteristics, and there are significant differences in the distribution of seismic motions under different source mechanisms. The current velocity pulse probability distribution model only considers the rupture characteristics and the relative position relationship between stations and faults without considering the influence of source parameters such as rupture velocity. There are deviations in the fitting effect for different components, such as E-W and N-S. The speed pulse period identified by virtual stations varies from 1-7s. By adding structural measures to the building structure, the natural vibration period of the structure can be changed, thereby avoiding the potential hazards of pulse-type seismic motion. More actual observation data is needed to study the distribution of velocity pulse periods in the future. This article’s simulation results are consistent with the existing understanding of earthquake motion. However, our study employs a simplified crustal structure characterized by horizontal layers, temporarily ignoring the site condition in the simulation of long-period ground motion. We do not encapsulate the complexities introduced by the site conditions. Average shear wave velocity at 30m underground (V_S30) is a factor that affects the number of pulse recognition. In addition, this article does not discuss the effects of rupture speed, the number of asperities, and the position of asperities. Therefore, we will conduct more in-depth research on these factors in our subsequent work. The research in this article calculates the scenario earthquake of the Huya Fault under rupture mode and focal mechanism. The research results can be used for seismic analysis of long-period structures, providing a reference for the construction of significant projects and seismic hazard analysis near the Huya Fault. This article referred to previous research when setting parameters for scenario earthquakes. However, due to the limitations of statistical models, the set scenario earthquakes cannot fully represent the Huya Fault situation and the region’s possible earthquake scenarios.

Key words: Scenario earthquake, finite difference method, Huya Fault, velocity pulse, distribution probability

纪志伟, 李宗超, 张琰, 琚长辉. 情景地震震源特征对速度脉冲分布的影响——以虎牙断层为例[J]. 地震地质, 2024, 46(5): 1207-1225.

JI Zhi-wei, LI Zong-chao, ZHANG Yan, JU Chang-hui. THE INFLUENCE OF SEISMIC SOURCE CHARACTERISTICS ON VELOCITY PULSE DISTRIBUTION IN SCENARIOS: A TEST IN HUYA FAULT[J]. SEISMOLOGY AND GEOLOGY, 2024, 46(5): 1207-1225.

图/表 16

图 1 历史地震及断层位置图a中的白色实线框表示中国地震科学试验场区域

Fig. 1 Location of historical earthquakes and faults.

图 2 情景地震建模流程

Fig. 2 Modeling process of scenario earthquake.

表1 虎牙断层情景地震的震源参数

Table 1 Seismic parameters for scenario earthquake of the Huya Fault

震源参数	事件A	事件B	事件C	参考文献
破裂面积(长×宽)		50km×24km		Somerville et al., 1999 Wells et al., 1994
子断层尺寸(长×宽)		1km×1km		王海云, 2004
总地震矩		4.0×10¹⁹N·m		Wells et al., 1994
背景区域的平均滑动量		115cm		Somerville et al., 1999
凹凸体的平均滑动量		330cm
凹凸体的面积		264km²		Somerville et al., 1999 王海云, 2004
背景区域的地震矩		2.56×10¹⁹N·m
凹凸体的地震矩		1.44×10¹⁹N·m
方位角/倾角/滑动角	340°/90°/0°	340°/90°/0°	340°/90°/90°	*
平均上升时间		1.5s		Somerville et al., 1999
破裂模式	双侧破裂	单侧破裂	双侧破裂	*
震源深度	18km	12km	18km	唐荣昌等,1981; 王海云, 2004
破裂速度		2700m/s		*

图 3 凹凸体与破裂的相对位置; 单侧(双侧)破裂示意图

Fig. 3 Relative positions of the asperity and rupture, diagram of unilateral (bilateral) rupture.

图 4 计算区域的地壳速度结构

Fig. 4 Crustal velocity structure in the calculation area.

图 5 事件A的EW分量速度波场

Fig. 5 The velocity wave field of the east-west(EW)component of event A.

图 6 事件B的 EW分量速度波场

Fig. 6 The velocity wave field of the east-west(EW)component of event B.

图 7 事件C的 EW分量速度波场

Fig. 7 The velocity wave field of the east-west(EW)component of event C.

图 8 模拟结果在多个虚拟台站的三分量速度时程 a 走滑断层(事件A); b 逆冲断层(事件C)

Fig. 8 Simulation results show three-component velocity time histories at multiple virtual stations.

图 9 速度脉冲识别示例 EW 东西分量; NS 南北分量; UD垂直分量。Tp 脉冲周期; PI 脉冲指数

Fig. 9 Example of velocity pulse identification.

图 10 走滑断层和倾滑断层的破裂方向性参数(Somerville et al., 1997)

Fig. 10 Rupture directivity effect parameters of strike and dip slip faults(Somerville et al., 1997).

图 11 事件A(MW7.0)的脉冲指数、脉冲周期及脉冲幅值(PGV)分布

Fig. 11 Distribution of pulse index, pulse period, and pulse amplitude (PGV) for event A (MW7.0).

图 12 事件B(MW7.0)脉冲指数、脉冲周期及脉冲幅值 (PGV) 分布

Fig. 12 Distribution of pulse index, pulse period and pulse amplitude (PGV) for event B(MW7.0).

图 13 事件C(MW7.0)脉冲指数、脉冲周期及脉冲幅值 (PGV) 分布

Fig. 13 Distribution of pulse index, pulse period, and pulse amplitude (PGV) for event C(MW7.0).

图 14 事件A、 B、 C脉冲周期分布区间

Fig. 14 Pulse period distribution interval of event A, B and C.

表2 虎牙断裂不同情景地震下的脉冲周期范围

Table 2 Pulse period range of the Huya Fault under different scenario earthquakes

事件	A			B			C
方向	EW	NS	UD	EW	NS	UD	EW	NS	UD
Tp_max/s	10.8	15.4	9.3	8.2	8.2	3.9	9.0	8.2	12.9
Tp_min/s	2.3	2.2	2.1	2.0	1.9	2.2	1.6	1.7	1.8

参考文献 36

[1]	邓起东, 陈社发, 赵小麟. 1994. 龙门山及其邻区的构造和地震活动及动力学[J]. 地震地质, 16(4): 389—403.
	DENG Qi-dong, CHEN She-fa, ZHAO Xiao-lin. 1994. Tectonics, seismicity and dynamics of Longmenshan Mountains and its adjacent Regions[J]. Seismology and Geology, 16(4): 389—403 (in Chinese).
[2]	李峰, 刘华国, 贾启超, 等. 2018. 青藏高原东缘岷江断裂北段全新世活动特征[J]. 地震地质, 40(1): 97—106. doi: 10.3969/j.issn.0253-4967.2018.01.008.
	LI Feng, LIU Hua-guo, JIA Qi-chao, et al. 2018. Holocene active characteristics of the northern segment of the Minjiang Fault in the eastern margin of the Tibetan plateau[J]. Seismology and Geology, 40(1): 97—106 (in Chinese).
[3]	刘皓晴, 李玉江, 陈连旺. 2023. 青藏高原东缘虎牙断裂带南北段运动方式差异性机理: 来自数值模拟的约束[J]. 地球物理学报, 66(7): 2757—2771.
	LIU Hao-qing, LI Yu-jiang, CHEN Lian-wang. 2023. Mechanisms of the different senses of fault slip in the north and south segments of the Huya fault zone, eastern Tibetan plateau: Constraints from numerical modeling[J]. Chinese Journal of Geophysics, 66(7): 2757—2771 (in Chinese).
[4]	刘华国, 李峰, 张效亮, 等. 2018. 青藏高原东缘虎牙断裂晚第四纪活动特征[J]. 地震研究, 41(4): 594—604, 658.
	LIU Hua-guo, LI Feng, ZHANG Xiao-liang, et al. 2018. Late Quaternary activity of Huya Fault on the eastern margin of the Tibetan plateau[J]. Journal of Seismological Research, 41(4): 594—604, 658 (in Chinese).
[5]	唐荣昌, 陆联康. 1981. 1976年松潘、平武地震的地震地质特征[J]. 地震地质, 3(2): 41—47, 85—86.
	TANG Rong-chang, LU Lian-kang. 1981. On the seismogeological characteristics of 1976 Songpan-Pingwu earthquakes[J]. Seismology and Geology, 3(2): 41—47, 85—86 (in Chinese).
[6]	王海云. 2004. 近场强地震动预测的有限断层震源模型[D]. 哈尔滨: 中国地震局工程力学研究所:27—33, 59—61.
	WANG Hai-yun. 2004. Finite fault source model for predicting near-field strong ground motion[D]. Institute of Engineering Mechanics, China Earthquake Administration, Harbin: 27—33, 59—61 (in Chinese).
[7]	许力生, 陈运泰. 2002. 震源时间函数与震源破裂过程[J]. 地震地磁观测与研究, 23(6): 1—8.
	XU Li-sheng, CHEN Yun-tai. 2002. Source time function and rupture process of earthquake[J]. Seismological and Geomagnetic Observation and Research, 23(6): 1—8 (in Chinese).
[8]	中国地震科学实验场科学设计编写组. 2019. 中国地震科学实验场科学设计[M]. 北京: 中国标准出版社:4.
	Working Group on the Scientific Challenges Report, China Seismic Experimental Site. 2019. China Seismic Experimental Site: Scientific Challenges[M]. China Standard Press, Beijing: 4 (in Chinese).
[9]	Alonso R A, Miranda E. 2015. Assessment of building behavior under near-fault pulse-like ground motions through simplified models[J]. Soil Dynamics and Earthquake Engineering, 79(A): 47—58.
[10]	Ameri G, Gallovič F, Pacor F, et al. 2009. Uncertainties in strong ground-motion prediction with finite-fault synthetic seismograms: An application to the 1984 M5.7 Gubbio, central Italy, earthquake[J]. Bulletin of the Seismological Society of America, 99(2A): 647—663.
[11]	Aoi S, Fujiwara H. 1999. 3D finite-difference method using discontinuous grids[J]. Bulletin of the Seismological Society of America, 89(4): 918—930.
[12]	Baker J W. 2007. Quantitative classification of near-fault ground motions using wavelet analysis[J]. Bulletin of the Seismological Society of America, 97(5): 1486—1501.
[13]	Beck J L, Hall J F. 1985. Factors contributing to the catastrophe in Mexico city during the earthquake of September 19[J]. Geophysical Research Letters, 13(6): 593—596.
[14]	Bjerrum L W, Sørensen M B, Atakan K. 2010. Strong ground-motion simulation of the 12 May 2008 M_W7.9 Wenchuan earthquake, using various slip models[J]. Bulletin of the Seismological Society of America, 100(5B): 2396—2424.
[15]	Bray J D, Rodriguez M A. 2004. Characterization of forward-directivity ground motions in the near-fault region[J]. Soil Dynamics and Earthquake Engineering, 24: 815—828.
[16]	Cork T G, Kim J H, Mavroeidis G P, et al. 2016. Effects of tectonic regime and soil conditions on the pulse period of near-fault ground motions[J]. Soil Dynamics and Earthquake Engineering, 80: 102—118.
[17]	Graves R W, Aagaard B T, Hudnut K W, et al. 2008. Broadband simulations for M_W7.8 southern San Andreas earthquakes: ground motion sensitivity to rupture speed[J]. Geophysical Research Letters, 35(22): L22302.
[18]	Hanks T C, Kanamori H. 1979. A moment magnitude scale[J]. Journal of Geophysical Research, 84(B5): 2348.
[19]	Hirasawa T, Stauder W. 1965. On the seismic body waves from a finite moving source[J]. Bulletin of the Seismological Society of America, 55(2): 237—262.
[20]	Iwaki A, Morikawa N, Maeda T, et al. 2017. Spatial distribution of ground-motion variability in broadband ground-motion simulations[J]. Bulletin of the Seismological Society of America, 107(6): 2963—2979.
[21]	Ji Z W, Li Z C, Chen X L, et al. 2022. Uncertainties in the prediction of near-fault long-period ground motion: An application to the 1970 Tonghai earthquake(M_S7.8)[J]. Pure and Applied Geophysics, 179: 2637—2660.
[22]	Jones L M, Han W, Hauksson E, et al. 1984. Focal mechanisms and aftershock locations of the Songpan earthquakes of August 1976 in Sichuan, China[J]. Journal of Geophysical Research: Solid Earth, 89(B9): 7697—7707.
[23]	Kirby E, Harkins N, Wang E Q, et al. 2007. Slip rate gradients along the eastern Kunlun Fault[J]. Tectonics, 26(2): TC2010.
[24]	Luo Q B, Dai F, Liu Y, et al. 2020. Simulating the near-field pulse-like ground motions of the Imperial Valley, California, earthquake[J]. Soil Dynamics and Earthquake Engineering, 138:106347.
[25]	Luo Q B, Dai F, Liu Y, et al. 2021. Seismic performance assessment of velocity pulse-like ground motions under near-field earthquakes[J]. Rock Mechanics and Rock Engineering, 54(8): 3799—3816.
[26]	Maeda T, Iwaki A, Morikawa N, et al. 2016. Seismic-hazard analysis of long-period ground motion of megathrust earthquakes in the Nankai trough based on 3D finite-difference simulation[J]. Seismological Research Letters, 87(6): 1265—1273.
[27]	Mavroeidis G P, Papageorgiou A S. 2003. A mathematical representation of near-fault ground motions[J]. Bulletin of the Seismological Society of America, 93(3): 1099—1131.
[28]	Miyake H, Iwata T, Irikura K. 2003. Source characterization for broadband ground-motion simulation: Kinematic heterogeneous source model and strong motion generation area[J]. Bulletin of the Seismological Society of America, 93(6): 2531—2545.
[29]	Schmedes J, Archuleta R J, Lavallée D. 2010. Correlation of earthquake source parameters inferred from dynamic rupture simulations[J]. Journal of Geophysical Research: Solid Earth, 115(B3): B03304.
[30]	Sehhati R, Adrian R M, Elgawady M, et al. 2011. Effects of near-fault ground motions and equivalent pulses on multi-story structures[J]. Engineering Structures, 33(3): 767—779.
[31]	Shahi S K, Baker J W. 2014. An efficient algorithm to identify strong-velocity pulses in multicomponent ground motions[J]. Bulletin of the Seismological Society of America, 104(5): 2456—2466.
[32]	Somerville P G, Smith N F, Graves R W, et al. 1997. Modification of empirical strong ground motion attenuation relations to include the amplitude and duration effects of rupture directivity[J]. Seismological Research Letters, 68(1): 199—222.
[33]	Somerville P, Irikura K, Graves R, et al. 1999. Characterizing crustal earthquake slip models for the prediction of strong ground motion[J]. Seismological Research Letters, 70(1): 59—80.
[34]	Viens L, Denolle M A. 2019. Long-period ground motions from past and virtual megathrust earthquakes along the Nankai Trough, Japan[J]. Bulletin of the Seismological Society of America, 109(4): 1312—1330.
[35]	Wells D L, Coppersmith K J. 1994. New empirical relationships among magnitude, rupture length, rupture width, rupture area, and surface displacement[J]. Bulletin of the Seismological Society of America, 84(4): 974—1002.
[36]	Wessel P, Smith W H F, Scharroo R, et al. 2013. Generic mapping tools: Improved version released[J]. EOS Transactions American Geophysical Union, 94(45): 409—410.