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Evolution of statistical earthquake models to account for measurement errors and dependence.

统计地震模型的演变以考虑测量误差和依赖性。

基本信息

批准号：
2753579
负责人：
金额：
--
依托单位：
Lancaster University
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2022
资助国家：
英国
起止时间：
2022 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2753579
关键词：
Evolution statistical earthquake models account

项目摘要

Numerous strategies have been proposed and developed to lower CO2 emissions within the environment. Carbon Capture and Storage (CCS) systems have been identified as one of the most effective strategies. To enable a safe growth of such geological formations, any dangers over the linked induced seismic activity should first be evaluated. This evaluation requires extending existing approaches for assessing the potential hazards of tectonic earthquakes and human-induced earthquakes. Specifically, our research aims to enhance existing statistical models, such as stochastic point process models (ETAS models) and extreme value methods, commonly used in earthquake analysis, incorporating features overlooked in current approaches. For instance, our research challenges assumptions about earthquake records and covariate information, investigating the effects of assumed independence in aftershock magnitudes.Another novel aspect of our project involves accounting for measurement errors in both point process and extreme value methods, recognising the error properties of earthquake magnitudes, time and locations inferred from sensor network vibrations. Within this research project, we use historical earthquake catalogues. We aim to explore how these strong assumptions affect results and incorporate related studies of uncertainties and dependence in seismicity modelling.Industrial partner: Shell.

已经提出和开发了许多战略来降低环境中的CO2排放。碳捕获和储存（CCS）系统已被确定为最有效的战略之一。为了使这种地质构造能够安全生长，应首先评估与诱发地震活动有关的任何危险。这一评价需要扩大现有的方法，以评估潜在的危险，构造地震和人为地震。具体而言，我们的研究旨在增强现有的统计模型，如随机点过程模型（ETAS模型）和极值方法，通常用于地震分析，结合当前方法中忽略的功能。例如，我们的研究挑战了地震记录和协变量信息的假设，调查了假设独立性对余震震级的影响。我们项目的另一个新方面涉及到点过程和极值方法中的测量误差，识别从传感器网络振动推断的地震震级，时间和位置的误差特性。在这个研究项目中，我们使用历史地震目录。我们的目标是探索这些强有力的假设如何影响结果，并将不确定性和相关性的相关研究纳入地震活动性建模中。