Centerless circular array method: Inferring phase velocities of Rayleigh waves in broad wavelength ranges using microtremor records
Centerless circular array method: Inferring phase velocities of Rayleigh waves in broad wavelength ranges using microtremor records
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DOI：
10.1029/2005jb004235
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发表时间：
2006-09
影响因子：
--
通讯作者：
I. Cho;Taku Tada;Y. Shinozaki
中科院分区：
文献类型：
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作者：
I. Cho;Taku Tada;Y. Shinozaki
[1]无中心圆阵（CCA）方法是我们在前期工作中提出的一种微地震勘探算法，它可以通过分析由三个或五个地震传感器组成的阵列在圆周上获得的微地震的垂直分量记录来估计Rayleigh波的相速度。我们已经证实，通过现场测试，我们的CCA方法的适用性阵列上的顺序为几到几百米的半径，并揭示了其显着的高性能在长波长范围内，分辨率上限延伸到几十倍的阵列半径。我们还发明了一种数学模型，能够评估在给定的微动场的信噪比。现场数据的审查证实了我们的假设，噪声是偏置CCA方法的分析结果在长波长范围内的主要因素，其最长的可分辨波长是由信噪比。CCA方法和我们的新方法的信噪比分析相结合的使用提供了一个强大的方法工具，允许一个提取最大的信息，从一个简单的地震阵列获得的微动记录。
[1] The centerless circular array (CCA) method, proposed by ourselves in an earlier work, is an algorithm of microtremor exploration which can be used to estimate phase velocities of Rayleigh waves by analyzing vertical component records of microtremors that are obtained with an array of three or five seismic sensors placed around a circumference. We have confirmed, through field tests, the applicability of our CCA method to arrays on the order of several to several hundred meters in radii and have revealed its remarkably high performance in long-wavelength ranges, the upper resolution limit extending as far as several 10 times the array radius. We have also invented a mathematical model that enables to evaluate signal-to-noise ratios in a given microtremor field. Scrutiny of field data has borne out our hypothesis that noise is the principal factor that biases the analysis results of the CCA method in long-wavelength ranges and that its longest resolvable wavelength is determined by the signal-to-noise ratio. Combined use of the CCA method and our new method of signal-to-noise ratio analysis provides a powerful methodological tool that allows one to extract maximal information from microtremor records obtained with a simple seismic array.