Reservoir monitoring is essential to guarantee safe operations for all activities involving the production and injection of fluids into the subsurface, such as hydrocarbon production, gas storage and the exploitation of geothermal reservoirs. For this purpose, microseismic monitoring networks are operated in real time in order to identify and locate any possible seismic events in the vicinity of the reservoir. The goal of this study is to investigate whether the large amount of ambient seismic noise recorded by seismic reservoir monitoring networks can be used to infer a one-dimensional shear-wave velocity profile representative of the area covered by the network. Shear-wave velocities are generally difficult to characterize and constrain, yet they are key to precisely locate seismic events. The adopted workflow consists of three steps: first, the cross-correlation functions between all station pairs are retrieved, using 1 year of continuous data; second, the average group- and phase velocity dispersion curves are extracted; third, a joint group and phase velocity inversion is done. For validation, the obtained average shear-wave velocity profile is compared with a regional model of the area as well as with local shear-wave velocity measurements from a sonic log.

中文翻译：

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由小型水库监测网络记录的地震环境噪声得出的剪切波速度结构

储层监测对于保证涉及地下流体生产和注入的所有活动（例如碳氢化合物生产、天然气储存和地热储层开发）的安全运行至关重要。为此，微震监测网络实时运行，以识别和定位水库附近任何可能的地震事件。本研究的目的是调查地震储层监测网络记录的大量环境地震噪声是否可以用于推断代表网络覆盖区域的一维剪切波速度剖面。剪切波速度通常难以表征和约束，但它们是精确定位地震事件的关键。采用的工作流程包括三个步骤：首先，使用1年的连续数据检索所有站对之间的互相关函数；其次，提取平均群速度和相速度色散曲线；第三，进行联合群和相速度反演。为了进行验证，将获得的平均剪切波速度剖面与该区域的区域模型以及声波测井的局部剪切波速度测量值进行比较。