Collaborative Research: Toward understanding spatio-temporal variations of seismic clusters in different environments

合作研究：了解不同环境下地震群的时空变化

基本信息

批准号：
1722561
负责人：
Yehuda Ben-Zion
金额：
$ 24.8万
依托单位：
University of Southern California
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-07-15 至 2022-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1722561&HistoricalAwards=false
关键词：
Collaborative Research Toward understanding spatio

项目摘要

Mitigating the devastating economic and humanitarian impact of natural and human-induced earthquakes requires advanced research on quantification of seismicity patterns, identification of induced seismicity, and improved forecasting ability. The risk posed by human-induced seismicity may be especially acute severe in California and other tectonic regions that operate geothermal, oil, and gas fields in highly populated areas with societal infrastructure. This project synthesizes novel earthquake cluster identification/classification techniques, physical modeling, and high-quality earthquake and geodetic data from different tectonic environments toward improved understanding of seismicity in relation to large events and human-induced earthquakes. A distinguishing property of the approach is uniform analysis and interpretation of thousands of earthquake clusters on different space-time-energy scales. The investigations quantify the dynamics of seismicity on time scales of hours to tens of years, and zoom spatially from worldwide analysis to focused studies of selected regions with high-quality data. The research produces a comprehensive database of cluster styles such as dominant earthquake cluster types and values of their essential parameters, at global, regional, and local scales. The employed approach is intrinsically data-driven, but it is informed and motivated by models of seismicity with different types of rheologies and loadings that help interpreting the results. The combined observational and theoretical studies facilitate extracting fundamental information from the observed results on the basic underlying physics. The project develops improved methods for detecting human-induced seismicity, catalog declustering, establishes relations between earthquake clustering and principal loading mechanisms, and may provide additional signals for tracking the preparation process of large seismic events. The developed tools and results can have significant impact on understanding of seismicity and analysis of seismic hazard in active tectonic environments, oil, gas, and geothermal production areas, and regions containing both.

减轻自然和人为地震造成的破坏性经济和人道主义影响需要对地震活动模式的量化、诱发地震活动的识别和提高预测能力进行深入研究。在加利福尼亚州和其他在拥有社会基础设施的人口稠密地区运营地热、石油和天然气田的构造区域，人为引发的地震活动带来的风险可能尤其严重。该项目综合了新颖的地震群识别/分类技术、物理建模以及来自不同构造环境的高质量地震和大地测量数据，以提高对与大型事件和人为地震相关的地震活动的了解。该方法的一个显着特点是对不同时空能量尺度上的数千个地震群进行统一分析和解释。这些研究在数小时到数十年的时间尺度上量化了地震活动的动态，并在空间上从全球分析扩大到利用高质量数据对选定区域进行重点研究。该研究建立了一个关于全球、区域和地方尺度的集群类型的综合数据库，例如主要地震集群类型及其基本参数值。所采用的方法本质上是数据驱动的，但它受到具有不同类型流变和载荷的地震活动模型的启发和启发，有助于解释结果。观测和理论研究的结合有助于从基本物理学的观测结果中提取基本信息。该项目开发了检测人为地震活动的改进方法、目录分簇、建立地震聚类和主要加载机制之间的关系，并可以为跟踪大型地震事件的准备过程提供额外的信号。开发的工具和结果可以对活动构造环境、石油、天然气和地热生产区域以及同时包含这两种区域的地震活动的理解和地震灾害分析产生重大影响。