基于气枪主动源的祁连山地区地下介质衰减变化

doi:10.3969/j.issn.0253-4967.2025.04.20240071

摘要/Abstract

摘要：

国内外利用重复震源开展地下介质变化监测研究主要基于激发源波形的时间变化信息, 而将振幅变化信息应用于地下介质变化的相关研究仍很有限。文中利用甘肃祁连山气枪主动源激发的高重复性波形的振幅信息, 应用频谱比法计算祁连山中东段地区的介质衰减参数t^*随时间的变化, 获得了观测台站不同震相的衰减变化特征。与气枪激发波形的走时变化、张掖甘州地区地面气压、地表温度、降水量等物理量进行对比, 结果表明衰减变化与走时变化具有正相关性, 且2019年张掖甘州 M_S5.0 地震震源区附近的ZDY27台的衰减变化存在0.03s的同震相对变化。相关研究成果表明, 基于气枪主动源的衰减变化计算是探测地下介质变化的有效方法, 这为基于气枪主动源连续探测地下介质变化提供了另一种途径。

关键词: 张掖甘州M_S5.0地震, 甘肃祁连山气枪主动源, 衰减变化, 走时变化

Abstract:

Accurately characterizing stress state changes along active faults in seismogenic zones remains a key challenge in geophysics. Although direct observation of stress evolution in the subsurface is difficult, such changes can be indirectly inferred by monitoring variations in seismic wave parameters—particularly wave velocity and attenuation—to track dynamic alterations in regional stress fields. However, wave velocity changes associated with stress redistribution are typically extremely subtle, requiring high-precision observation systems and highly repeatable seismic sources to be detected reliably.

In recent years, land-based seismic airgun active-source technology has emerged as a promising tool for long-term monitoring of crustal media. Airgun sources offer distinct advantages, including high signal repeatability, strong energy output, long propagation distance, and minimal environmental impact, making them ideal for detecting both static structures and temporal variations in crustal properties. In July 2015, we established the Qilian Mountain airgun active-source system at the Xiliushui Reservoir in Zhangye, Gansu Province, to investigate crustal structure and its temporal changes in the fault zones of the eastern Qilian Mountains.

Previous studies using repeatable sources have largely focused on waveform traveltime variations to detect media changes. However, relatively few studies have explored the application of seismic wave amplitude variations, especially in the context of monitoring attenuation. Non-elastic attenuation, commonly described by the quality factor(Q), captures energy losses due to inelastic behavior and heterogeneities in the medium. It is highly sensitive to factors such as microcrack formation, fluid presence, temperature fluctuations, and phase transitions, making it an important indicator of subsurface physical and mechanical states.

One reason for the limited application of attenuation monitoring is the complexity of amplitude interpretation, as amplitudes are affected by geometric spreading, reflection, refraction, scattering, and other propagation effects. Nevertheless, laboratory studies demonstrate that attenuation is more sensitive than wave velocity to stress-induced changes, and under controlled field conditions—such as fixed source-receiver geometry and waveform consistency—high-precision monitoring of attenuation is feasible.

In this study, we apply the spectral ratio method to waveforms generated by the highly repeatable Gansu Qilian Mountain airgun source to calculate the time-dependent attenuation parameter (t^*) at multiple stations in the eastern Qilian region. We then analyze the temporal variations of t^* across different seismic phases and compare these changes with traveltime variations, as well as with surface environmental variables such as barometric pressure, temperature, and precipitation in Zhangye Ganzhou.

Our results show a positive correlation between attenuation changes and traveltime shifts. At station ZDY27, located near the epicenter of the 2019 Zhangye Ganzhou M_S5.0 earthquake, a relative change in t^* of approximately 0.03 seconds was observed. These findings demonstrate that airgun-based attenuation monitoring is a robust and sensitive method for detecting subsurface stress and property changes. This approach provides an important supplement to existing monitoring methods and enhances our capability for continuous, high-resolution surveillance of crustal media in seismically active regions.

Key words: Zhangye Ganzhou M_S5.0 earthquake, Gansu Qilian Mountain Airgun active source, attenuation change, travel-time change

邹锐, 郭晓, 孙点峰, 王亚红, 张元生, 秦满忠, 刘旭宙, 李少华, 宋婷, 刘岸果. 基于气枪主动源的祁连山地区地下介质衰减变化[J]. 地震地质, 2025, 47(4): 1204-1221.

ZOU Rui, GUO Xiao, SUN Dian-feng, WANG Ya-hong, ZHANG Yuan-sheng, QIN Man-zhong, LIU Xu-zhou, LI Shao-hua, SONG Ting, LIU An-guo. RESEARCH ON ATTENUATION CHANGES OF SUBSURFACE MEDIA IN THE QILIAN MOUNTAINS REGION BASED ON ACTIVE AIRGUN SOURCE[J]. SEISMOLOGY AND GEOLOGY, 2025, 47(4): 1204-1221.

图/表 11

图1 甘肃祁连山气枪主动源、观测台站位置及张掖甘州地震5.0级地震震中位置

Fig. 1 Locations of active sources of airguns, observation stations, and the epicenter of the M5.0 Zhangye Ganzhou earthquake in the Qilian Mountains of Gansu Province.

图2 祁连山主动源全景及激发波形 a 祁连山气枪主动源全景图片; b 祁连山气枪主动源60次激发波形; c 祁连山气枪主动源激发瞬间; d ZDY22台记录的800次激发波形重叠(带通滤波2~10Hz); e ZDY22台记录的800次激发波形的相关系数

Fig. 2 Panoramic view and excitation waveform of active source in Qilian Mountains.

图3 祁连山气枪主动源叠加剖面 60次线性叠加, 共54个台站

Fig. 3 Active source stacking profile of Qilian Mountains air guns.

图4 祁连山气枪主动源部分台站记录的激发波形全部波形叠加, 灰色阴影部分为选取的有效时间窗范围

Fig. 4 The excitation waveforms recorded by partial active source stations in the Qilian Mountains.

图5 祁连山气枪主动源部分台站记录不同沉放深度激发波形的优势频率分布

Fig. 5 Dominant frequencies of excitation waveforms at different depths recorded by partial active source stations in the Qilian Mountains.

图6 ZDY27台应用谱比法计算Δt*实例

Fig. 6 An example of calculation of ZDY27 station using spectral ratio method Δt* instance.

图7 部分台站Δt*的长期变化

Fig. 7 Long-term variation of Δt* at some stations.

图8 部分台站衰减变化Δt*的长期变化与走时变化dt的正相关性红色曲线为走时变化dt, 蓝色曲线为衰减变化Δt*

Fig. 8 The positive correlation between the long-term variation of attenuation change Δt* with the travel time change dt at some stations.

图9 2015年7月—2022年1月ZDY27台的同震及震后变化 SAT为地表气温变化值, SAP为地表气压变化值, dt为走时变化值, Δt*为衰减变化值

Fig. 9 Co-seismic and post seismic changes of Δt* from ZDY27 platform from July 2015 to January 2022.

图10 2019年1月—2022年1月ZDY27台Δt*的同震及震后变化

Fig. 10 Co-seismic and post seismic changes of Δt* from ZDY27 platform from January 2019 to January 2022.

图11 ZDY22台叠加波形、频谱及振幅和主频随时间的变化 a ZDY22台2017年1月5日叠加波形(带通滤波2~10Hz), 红色虚线为气枪信号振幅最小值; b ZDY22台2017年1月5日的叠加波形频谱, 红色虚线为主频对应的频率值; c 2017年1月—2020年6月ZDY22台气枪信号振幅最小值随时间的变化; d 2017年1月—2020年6月ZDY22台的主频随时间的变化

Fig. 11 The superimposed waveform, spectra, amplitude, and dominant frequency of ZDY22 platform over time.

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