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.

减轻自然和人类引起的地震的毁灭性经济和人道主义影响需要对量化模式的量化，鉴定诱导的地震性以及提高预测能力的高级研究。在加利福尼亚州和其他具有社会基础设施高度人口的地热，石油和天然气场的构造区域，人类引起的地震性带来的风险可能特别严重。该项目综合了新的地震簇识别/分类技术，物理建模以及从不同构造环境的高质量地震和地震数据，以提高对大事件和人类引起的地震的地震性的理解。该方法的区别特性是对不同时空能量尺度上数千个地震簇的统一分析和解释。该研究量化了在数十年的时间尺度上量化地震性的动力学，并在空间上从全球分析到对具有高质量数据的选定区域的重点研究。该研究构成了集群样式的全面数据库，例如在全球，区域和本地尺度上，其基本参数的主要地震群集类型和值。使用的方法是内在数据驱动的，但它是由具有不同类型的流变和负载的地震性模型来理解和动机的，可以帮助解释结果。合并的观测和理论研究促进了从观察到的基本基础物理学的结果中提取基本信息。该项目开发了改进的方法，用于检测人类引起的地震性，目录清理，建立地震聚类和主负载机制之间的关系，并可能提供其他信号来跟踪大型地震事件的准备过程。开发的工具和结果可能会对对主动构造环境，石油，天然气和地热生产区域以及包含两者的区域的地震性危害的地震性和分析产生重大影响。