非常规能源开发过程中流体注入引起的断层滑动

Wei Wu , Dazhao Lu , Derek Elsworth
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引用次数: 10

摘要

在非常规能源(如天然气和地热流体)的开发和生产现场附近,地震活动率的异常增加归因于地下流体注入。许多国家(如中国、韩国和美国)发生的破坏性和危险性地震促使人们做出巨大努力,以了解流体加压时断层滑动行为的复杂性。本研究回顾了注入诱发断层滑动的关键特征,并强调了与非常规能源项目相关的预测和缓解策略。这种能力依赖于对断层的一阶和二阶摩擦和稳定性行为以及流体加压的影响及其在触发抗震、地震和过渡滑移行为中的作用的充分理解和表征。适当的调查和定性方法以及典型的例子,以及我们对预警和缓解的理解方面的科学进步。目前的挑战涉及理解复杂的二阶摩擦行为以及盲断层的位置和特征。这些需求有助于整合从实验室、数值和现场研究中获得的多尺度和多物理数据,为诱发灾害准备和快速启动评估提供关键信息。最后,讨论了有助于提高理解的新兴技术,如数据分析和机器学习,预示着注入诱发地震活动性研究的下一个前沿。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fluid injection-induced fault slip during unconventional energy development: A review

An unusual increase in seismicity rate near the development and production sites of unconventional energy (e.g., natural gas and geothermal fluids) has been attributed to subsurface fluid injection. Damaging and hazardous earthquakes in many countries (e.g., China, South Korea, and the United States) have motivated tremendous effort to understand the complexity of fault slip behaviors in response to fluid pressurization. This study reviews key characteristics of injection-induced fault slip and highlights prediction and mitigation strategies relevant to unconventional energy projects. This capability relies on adequate understanding and characterization of first- and second-order friction and stability behaviors of faults as well as impacts of fluid pressurization and its role in triggering aseismic, seismic, and transitional slip behaviors. Suitable methods of investigation and characterization are noted together with typical examples together with scientific advances in our understanding towards forewarning and mitigation. Present challenges are addressed relating to the understanding of complex second-order friction behaviors and the location and characterization of blind faults. These needs are aided in the integration of multi-scale and multi-physical data obtained from laboratory, numerical, and field studies to offer crucial information for induced hazard preparedness and rapid run-up assessment. Finally, emerging technologies contributing to an improved understanding, such as data analytics and machine learning, are discussed in heralding the next frontier for injection-induced seismicity research.

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