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A source-synchronous filter for uncorrelated receiver traces from a swept-frequency seismic source

机译:源同步滤波器,用于扫频地震源中不相关的接收机迹线

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We have developed a novel algorithm to reduce noise in signals obtained from swept-frequency sources by removing out-of-band external noise sources and distortion caused from unwanted harmonics. The algorithm is designed to condition nonstationary signals for which traditional frequency-domain methods for removing noise have been less effective. The source synchronous filter (SSF) is a time-varying narrow band filter, which is synchronized with the frequency of the source signal at all times. Because the bandwidth of the filter needs to account for the source-to-receiver propagation delay and the sweep rate, SSF works best with slow sweep rates and moveout-adjusted waveforms to compensate for source-receiver delays. The SSF algorithm was applied to data collected during a field test at the University of California Santa Barbara's Garner Valley downhole array site in Southern California. At the site, a 45 kN shaker was mounted on top of a one-story structure and swept from 0 to 10 Hz and back over 60 s (producing useful seismic waves greater than 1.6 Hz). The seismic data were captured with small accelerometer and geophone arrays and with a distributed acoustic sensing array, which is a fiber-optic-based technique for the monitoring of elastic waves. The result of the application of SSF on the field data is a set of undistorted and uncorrelated traces that can be used in different applications, such as measuring phase velocities of surface waves or applying convolution operations with the encoder source function to obtain traveltimes. The results from the SSF were used with a visual phase alignment tool to facilitate developing dispersion curves and as a prefilter to improve the interpretation of the data.
机译:我们已经开发出一种新颖的算法,可通过消除带外外部噪声源和有害谐波引起的失真来减少从扫频源获得的信号中的噪声。该算法旨在处理非平稳信号,对于这些信号,传统的频域去除噪声方法效果较差。源同步滤波器(SSF)是随时间变化的窄带滤波器,它始终与源信号的频率同步。由于滤波器的带宽需要考虑源到接收器的传播延迟和扫描速率,因此SSF在缓慢的扫描速率和经过时差调整后的波形中能最好地工作,以补偿源-接收器的延迟。 SSF算法应用于在加利福尼亚大学圣巴巴拉分校位于南加州的Garner Valley井下阵列现场测试中收集的数据。在现场,将一个45 kN的振动器安装在一层结构的顶部,并从0到10 Hz扫频,然后回扫60 s(产生大于1.6 Hz的有用地震波)。地震数据是通过小型加速度计和地震检波器阵列以及分布式声学传感阵列捕获的,分布式声学传感阵列是基于光纤的弹性波监测技术。在现场数据上应用SSF的结果是一组未失真且不相关的迹线,可以在不同的应用程序中使用这些迹线,例如测量表面波的相速度或使用编码器源函数进行卷积运算以获得传播时间。来自SSF的结果与视觉相位对齐工具一起使用,以促进色散曲线的形成,并作为预过滤器来改善数据的解释。

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