从诱发地震群周围的高分辨率原位 Vp/Vs 估计值推断岩石强度和断层激活情况

M. Roth, A. Verdecchia, Rebecca M. Harrington, Yajing Liu
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摘要

与水力压裂相关的流体注入/抽取活动会诱发地震。诱发地震的常见机制包括孔隙压力升高、孔弹性应力变化以及通过非地震滑动造成的断层加载。然而,它们之间的相对影响仍是一个未决问题。估算地下岩石属性,如孔隙压力分布、裂缝密度和断裂几何形状,有助于量化流体-岩石相互作用与断层激活之间的因果关系。在地震频发与工业活动相关的地区,如加拿大西部沉积盆地,通过间接测量推断岩石属性可能是一种可行的策略,有助于识别易发生破坏的薄弱结构。在此,我们对不列颠哥伦比亚省东北部基斯卡蒂纳乌地区的 34 个诱发地震群的 Vp/Vs 进行了现场估算。我们估计九个地震群的 Vp/Vs 发生了高达 ±4.5% 的重大变化,这些地震群通常与高注入量地区有关。Vp/Vs的时空变化主要较小,这表明孔隙压力的增加在引发地震中起次要作用。与此相反,在流体饱和的多孔介质中,断裂长宽比减小,流体含量增加,与处理压力历史相一致的计算岩石力学模型能更好地解释观测结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inferring rock strength and fault activation from high-resolution in situ Vp/Vs estimates surrounding induced earthquake clusters
Fluid injection/extraction activity related to hydraulic fracturing can induce earthquakes. Common mechanisms attributed to induced earthquakes include elevated pore pressure, poroelastic stress change, and fault loading through aseismic slip. However, their relative influence is still an open question. Estimating subsurface rock properties, such as pore pressure distribution, crack density, and fracture geometry can help quantify the causal relationship between fluid-rock interaction and fault activation. Inferring rock properties by means of indirect measurement may be a viable strategy to help identify weak structures susceptible to failure in regions where increased seismicity correlates with industrial activity, such as the Western Canada Sedimentary Basin. Here we present in situ estimates of Vp/Vs for 34 induced earthquake clusters in the Kiskatinaw area in northeast British Columbia. We estimate significant changes of up to ±4.5% for nine clusters generally associated with areas of high injection volume. Predominantly small spatiotemporal Vp/Vs variations suggest pore pressure increase plays a secondary role in initiating earthquakes. In contrast, computational rock mechanical models that invoke a decreasing fracture aspect ratio and increasing fluid content in a fluid-saturated porous medium that are consistent with the treatment pressure history better explain the observations.
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