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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对经济和人道主义的破坏性影响，需要在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方面进行先进的研究。在加利福尼亚和其他地质构造地区，人类活动造成的地震风险可能特别严重，这些地区在人口密集的地区有地热、石油和天然气田，并有社会基础设施。该项目综合了新的地震集群识别/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，以提高对与大事件和人为地震相关的地震活动性的理解。该方法的一个显着特性是在不同的时空能量尺度上对数千个地震群进行统一的分析和解释。这些研究量化了地震活动在小时到几十年的时间尺度上的动态，并在空间上从全球分析扩展到具有高质量数据的选定区域的重点研究。该研究在全球、区域和地方尺度上建立了一个综合的地震群类型数据库，如主要地震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，但它是由具有不同类型流变学和载荷的地震活动模型所驱动的，这些模型有助于解释结果。观测与理论相结合的研究有助于从观测结果中提取基本的基础物理信息。本项目开发了改进的人为地震活动探测方法、目录聚类方法，建立了地震聚类与主荷载机制之间的关系，并可为跟踪大地震事件的准备过程提供额外的信号。所开发的工具和结果对了解活跃构造环境、石油、天然气和地热产区的地震活动性和地震危险性分析具有重要影响。