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.

地震群是在相对较短的时间内发生在给定区域内发生的地震事件的簇。它们与标准的余震序列（大地震后的一系列小地震）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，触发地震群的最可能的过程是地壳内的流体迁移以及缓慢的断层蠕变事件。在这里，研究人员研究了2008年至2020年间在南加州收集的数据。他们使用了机器学习算法，这些算法允许从地震噪声中提取小地震信号。他们发现了数百个未知的群，持续了6个月至几年。团队现在分析这些新确定的序列，以量化其集体空间和临时模式。一个目标是确定是否存在可推广的特征。另一个目标是表征基础驾驶过程，并记录这些群体发生的频率和频率。该研究旨在为非施加因素在推动地震活动中的作用提供更全面的区域环境。它的结果之一是可公开搜索的高分辨率目录，该目录是南加州最近的地震群。该项目还为一名研究生提供了支持，并向K-12学生和公众提供宣传。它是由NSF地球物理学和地球形式程序资助的。据信，估计群主要由Aseasmic过程驱动。因此，这些序列的空间时间演变编码了独特的信息：故障区域的结构和渗透性结构，负责的无向过程以及断层特性与地震物理学之间的耦合。在这里，研究人员利用了通过深度学习算法的地震监测能力的最新进展。他们表明，在过去的十年中，南加州经历了数百个以前未知的群情节，这些事件持续了数月到几年。这些地震微功能现在用于绘制地震构成中深处的长笛的潜在起源，并量化这些瞬时发作的频率和持续时间。倡议的时机和逮捕微观的时机将系统地检查与最大的区域事件的联系。此外，大量的微功能将用于对故障区域深入的几何，结构和渗透率结构的约束。这些数据对于理解时空中地震群的复杂演变至关重要。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响标准，被视为通过评估而被视为珍贵的支持。