| 四川盐源盆地短周期密集台阵背景噪声分布特征分析 |
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| 引用本文： | 田原,瞿辰,王伟涛,于常青,李丽.四川盐源盆地短周期密集台阵背景噪声分布特征分析[J].地球物理学报,2020,63(6):2248-2261. |
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| 作者姓名： | 田原 瞿辰 王伟涛 于常青 李丽 |
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| 作者单位： | 1. 中国地震局地球物理研究所, 北京 100081;
2. 中国地质科学院地质研究所, 北京 100037 |
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| 基金项目： | 受国家重点研发计划（2018YFC1503200），中国地震局地球物理研究所基本科研业务费专项（DQJB18B26），国家自然科学基金（41474114），国家自然科学基金（41761134096），中国地质调查项目（DD20190059，DD20160028）共同资助. |
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| 摘 要： | 短周期密集台阵的高频背景噪声互相关函数(NCF)是探查地球浅层精细结构的重要数据.然而高频背景噪声成分复杂且容易分布不均,分析其对NCF信号提取的影响,有助于获取可靠成像结果.本文基于布设于川滇地区盐源盆地的209个短周期台站组成的盐源台阵,利用密集台阵的噪声水平评估以及基于NCF的相干噪声分析两种方法,分析了其记录到的噪声波场特征及其对NCF的影响.结果表明,盐源台阵的整体噪声水平呈现北低南高的不均匀分布,高频噪声水平的强弱受控于当地的人类活动,亦受到浅部松散沉积层的影响.台阵垂直分量NCF中主要信号为基阶Rayleigh波,且产生该信号的相干噪声源的优势方位在不同频带具有较大区别:0.3～0.5Hz的噪声源强度较强且随时间变化较为稳定,主要能量来自台阵的南侧;0.5～1Hz的相干噪声源强度较低,有两个优势方向,其中较强的一个来自于台阵南侧,可能与0.3～0.5 Hz的噪声同源,较弱的一个来自于台阵北偏东方向;1～1.5Hz的背景噪声有四个较弱的优势方向,在台阵的不同区域有不同的优势方向,可能受到不同的局部噪声源的控制.垂向NCF中Rayleigh波的信噪比主要受控于波场的复杂程度,台阵南部受人文活动及沉积层影响,噪声水平较高,且由于盆山边缘复杂的反射、散射作用,其NCF波形复杂,信噪比偏低.受高频噪声源分布不均与及复杂地质结构的共同影响,盐源台阵的高频NCF中的信号复杂,后续对面波频散特征的提取应充分考虑噪声源对NCF的影响以获取可靠结果.
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| 关 键 词： | 密集台阵 背景噪声互相关函数 噪声源 功率谱密度 信噪比 |
| 收稿时间： | 2019-02-19 |
Characteristics of the ambient noise distribution recorded by the dense seismic array in the Yanyuan Basin,Sichuan Province |
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| TIAN Yuan,QU Chen,WANG WeiTao,YU ChangQing,LI Li.Characteristics of the ambient noise distribution recorded by the dense seismic array in the Yanyuan Basin,Sichuan Province[J].Chinese Journal of Geophysics,2020,63(6):2248-2261. |
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| Authors: | TIAN Yuan QU Chen WANG WeiTao YU ChangQing LI Li |
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| Institution: | 1. Institute of Geophysics, China Earthquake Administration, Beijing 100081, China;
2. Institute of Geology, Chinese Academy of Geological Science, Beijing 100037, China |
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| Abstract: | High-frequency ambient noise correlation function (NCF) is important for investigating near-surface structures of the earth. Due to the complex origin and uneven distribution of high frequency noise sources, analyzing the influence of source distribution on NCF would help us get more reliable tomography results. Based on data from a 209-station dense array deployed in the Yanyuan Basin, we analyze the characteristics of the ambient noise wave field and its influence on the NCF employing two methods: station noise level estimation based on the ambient noise field and coherent noise source estimation based on NCF. Results show that the overall noise level of the array is relatively low in the north and high in the south. The high-noise-level region is highly correlated with the distribution of the local human activity as well as unconsolidated sediments. The main surface wave signal of vertical component NCF is fundamental mode Rayleigh waves, but the directional distribution of the coherent noise source generating Rayleigh waves varies greatly among different periods. At 0.3~0.5 Hz, stable ambient noise power mainly comes from south of the array. At 0.5~1 Hz, the SNR of NCF is much lower than that at 0.3~0.5 Hz. The noise source field has two azimuthal maxima: the stronger one coming from the south, which is consistent with that at 0.3~0.5 Hz, and the weaker one coming from northeast. The directional distribution of the noise source at 1~1.5 Hz might correlate with the local noise source, which shows four weak azimuthal maxima and varies in different sub-regions among the whole array. The SNR of Rayleigh wave is controlled by the complexity of the noise wave field. The stations in the southern part of Yanyuan Array have relatively high noise level, and the scattering and reflecting wave field associated with the basin boundary might increase the complexity of the wave field and simultaneously decrease the SNR of NCFs. Due to the uneven distribution of interference noise sources and complex geological structure of the study area, the high frequency NCFs of Yanyuan Array might contain inevitable precursors and coda waves that would contaminate the recognition of Rayleigh waves, which we must take into full consideration when extracting dispersion data in further research. |
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| Keywords: | Dense array Ambient noise cross-correlation function Noise source Power spectrum density Signal-to-noise ratio (SNR) |
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