Research on seismic background noise in the Eastern Subbasin of the South China Sea
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摘要:
背景噪声的强弱是影响地震台站观测的一个重要因素。获取背景噪声的分布特征对评估海底地震仪记录数据质量及对数据的降噪处理均具有重要的指示意义。利用概率密度函数方法获取台站数据的功率谱密度的概率分布特征并与全球背景噪声高值模型和低值模型进行对比是研究台站周围环境背景噪声水平的有利手段。本研究基于南海大规模的被动源海底地震仪台阵长期观测实验的部分数据，利用概率密度函数方法研究了南海的背景噪声。首先，在全频段上对背景噪声进行了分析，并与其他台站做了对比，发现海洋的背景噪声在微震段和低频段大于高值模型且在全频带上远大于陆基台站的背景噪声，这表明海底地震仪数据质量并不高；其次，对观测过程中出现的地震事件以及其他典型信号的概率密度分布进行了归纳总结，发现远震事件、近震事件和数据丢失现象分别具有不同的优势频段和特征，这对后续滤波处理和质量检查具有重要指示意义；最后，研究了背景噪声的时间变化特征，发现台风是导致微震段时间变化的主要原因。
Abstract:The intensity of background noise is an important factor that affects the observation of seismic stations. Acquiring the characteristics of the background noise is of great significance to the evaluation of the quality of the data recorded by the Ocean Bottom Seismometer (OBS) and the noise reduction of the recorded data. Using the Probability Density Function (PDF) method to obtain the probability distribution characteristics of the Power Spectral Density (PSD) of the recorded data and comparing them with the results of new high-noise model (NHNM) and new low-noise model (NLNM) is a favorable method to research the background noise level around the station. Based on the long-term observation data of a large-scale passive source OBS array in the South China Sea (SCS), the background noise in the SCS is studied by using the PDF method. Firstly, the background noise in the whole frequency band is analyzed and compared with that from other stations. It is found that the background noise in the ocean is greater than the NHNM in the microseisms and low frequency band, and far greater than the background noise of the land-based station in the whole frequency band, which indicates that the data quality of the OBS is poor. Secondly, the probability density distribution of the earthquakes and other signals in the observation process is summarized, and it is found that the teleseismic, near earthquake and data dropout signal have different dominant frequency bands respectively, which has important significance for subsequent filtering processing and quality inspection. Finally, the time variation characteristics of background noise are studied, and it is found that typhoon is the main cause of time variation in microseisms period.
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图 8 远震事件、近震事件和数据丢失现象的功率谱密度的概率密度函数分布图其中，上图为远震事件；中图为近震事件；下图代表数据丢失信号；两条蓝色实线分别代表全球背景噪声高值和全球背景噪声低值；黑色实线代表众数值。
Figure 8.
图 9 台站HY15和HY17的背景噪声功率谱密度的时间变化图其中上面3幅图为台站HY15，下面3幅图为台站HY17，从左到右分别为垂直分量、水平分量1、水平分量2。
Figure 9.
表 1 南海东部次海盆台站布放资料
Table 1. The deployment data of OBS
台站编号 东经 北纬 水深/m 台站型号 HY15 117°32′ 16°30′ 3753 Guralp CMG-40T HY16 118°12′ 16°27′ 3920 Guralp CMG-40T HY17 118°48′ 16°12′ 3870 Guralp CMG-40T 
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