School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA.
Seismological Laboratory, California Institute of Technology, Pasadena, CA, USA.
Sci Rep. 2018 Jan 26;8(1):1646. doi: 10.1038/s41598-018-19728-w.
We develop a novel method for seismic event detection that can be applied to large-N arrays. The method is based on a new detection function named local similarity, which quantifies the signal consistency between the examined station and its nearest neighbors. Using the 5200-station Long Beach nodal array, we demonstrate that stacked local similarity functions can be used to detect seismic events with amplitudes near or below noise levels. We apply the method to one-week continuous data around the 03/11/2011 Mw 9.1 Tohoku-Oki earthquake, to detect local and distant events. In the 5-10 Hz range, we detect various events of natural and anthropogenic origins, but without a clear increase in local seismicity during and following the surface waves of the Tohoku-Oki mainshock. In the 1-Hz low-pass-filtered range, we detect numerous events, likely representing aftershocks from the Tohoku-Oki mainshock region. This high-resolution detection technique can be applied to both ultra-dense and regular array recordings for monitoring ultra-weak micro-seismicity and detecting unusual seismic events in noisy environments.
我们开发了一种新的地震事件检测方法，可应用于大 N 阵列。该方法基于一种新的检测函数，名为局部相似性，它量化了被检测站与其最近邻之间的信号一致性。使用 5200 个站的长滩节点阵列，我们证明了堆叠的局部相似性函数可用于检测幅度接近或低于噪声水平的地震事件。我们将该方法应用于 2011 年 3 月 11 日 Mw9.1 日本东北地震前后一周的连续数据，以检测本地和远程事件。在 5-10 Hz 范围内，我们检测到各种自然和人为来源的事件，但在东北主震的面波期间和之后，本地地震活动没有明显增加。在 1 Hz 低通滤波范围内，我们检测到许多事件，可能代表东北主震区的余震。这种高分辨率检测技术可应用于超密集和常规阵列记录，用于监测极微弱的微震活动，并在嘈杂环境中检测异常地震事件。
