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Microswarms: a lens into fault structure and aseismic processes deep in Southern California’s crust

微群：了解南加州地壳深处的断层结构和地震过程的镜头

基本信息

批准号：
2034167
负责人：
Zachary Ross
金额：
$ 34.22万
依托单位：
California Institute of Technology
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-05-15 至 2025-04-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2034167&HistoricalAwards=false
关键词：
Microswarms lens into fault structure

项目摘要

Earthquake swarms are clusters of seismic events occurring in a given area within a relatively short period of time. They are distinct from standard aftershock sequences – series of small earthquakes following large earthquakes - in that they appear to be driven by non-tectonic factors. Recent analysis suggests that the most likely processes triggering earthquake swarms are fluid migration within Earth’s crust, and slow fault creep events. Here, the researchers examined data collected across Southern California between 2008 and 2020. They used machine learning algorithms which allow extracting small earthquake signals from the seismic noise. They discovered hundreds of unknown swarms that lasted 6 months to several years in duration. The team now analyze these newly identified sequences to quantify their collective spatial and temporal patterns. One goal is to identify if there are generalizable characteristics. Another goal is to characterize the underlying driving processes and document where and how often these swarms occur. The study aims to provide a more comprehensive regional context for the role of non-tectonic factors in driving earthquake activity. One of its outcomes is a publicly searchable high-resolution catalog of recent earthquake swarms in Southern California. The project also provide support for one graduate student and outreach to K-12 students and the public. It is funded by both NSF Geophysics and Geoinformatics programs.Earthquake swarms are believed to be driven mainly by aseismic processes. The spatiotemporal evolution of these sequences therefore encodes unique information: the structural and permeability architecture of fault zones, the aseismic processes responsible, and the coupling between fault properties and earthquake physics. Here, the researchers leveraged recent advances in earthquake monitoring capabilities with deep learning algorithms. They showed that during the last decade, Southern California has experienced hundreds of previously unknown swarm episodes that persist for months to years. These earthquake microswarms are now used to map the potential origins of fluids deep within the seismogenic crust and to quantify the frequency and duration of these transient episodes. The timing of the initiation and arrest of microswarms will be examined systematically for connections to the largest regional events. Furthermore, the large collection of microswarms will be used to provide constraints on the geometrical, structural, and permeability architecture of the fault zones at depth. These data are critical to understanding the complex evolution of earthquake swarms in space and time.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

震群是在相对较短的时间内发生在给定地区的地震事件的集群。它们与标准的余震序列（大地震之后的一系列小地震）不同，因为它们似乎是由非构造因素驱动的。最近的分析表明，最有可能触发地震群的过程是地壳内的流体迁移和缓慢的断层蠕动事件。在这里，研究人员检查了2008年至2020年期间在南加州收集的数据。他们使用机器学习算法，可以从地震噪声中提取小地震信号。他们发现了数百个持续6个月至数年的未知虫群。研究小组现在分析这些新发现的序列，以量化它们的集体空间和时间模式。一个目标是确定是否有可推广的特征。另一个目标是描述潜在的驱动过程，并记录这些群集发生的位置和频率。该研究旨在为非构造因素在驱动地震活动中的作用提供更全面的区域背景。其成果之一是一个可公开搜索的南加州最近地震群的高分辨率目录。该项目还为一名研究生提供支持，并向K-12学生和公众推广。它由美国国家科学基金会地球物理学和地球信息学项目资助。因此，这些序列的时空演化编码独特的信息：断裂带的结构和渗透性架构，负责的地震过程，以及断层性质和地震物理之间的耦合。在这里，研究人员利用深度学习算法在地震监测能力方面的最新进展。他们表明，在过去的十年中，南加州经历了数百次以前未知的蜂群事件，持续数月至数年。这些地震微群现在被用来映射潜在的起源流体深内的孕震地壳和量化的频率和持续时间，这些短暂的插曲。将系统地审查微群的开始和停止的时间，以确定与最大的区域事件的联系。此外，大量的微群将用于提供对断层带深度的几何、结构和渗透率架构的约束。这些数据对于理解地震群在空间和时间上的复杂演变至关重要。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。