Underground human activities, such as mining, shale gas, and oil exploitation, waste-water disposal, or geothermal plants, can cause earthquakes; therefore, they are monitored by local seismic networks. An ideal seismic network has a triangulated grid, with spacing equal twice the minimal depth and no associated industry noise. In real cases, the network sensitivity is biased by stations placed near noisy roads, factories, or in a private garden, none located at optimal nodes. The sensitivity is also a function of the detection algorithm type and setting. The goal of this case study is to suggest a work-flow for network sensitivity calculation in case of no seismic activity. In other words: how small are the earthquakes that such seismic networks would detect if they were present? Such network sensitivity is a function of stations noise level, station-source geometry, and setting of the detection algorithm. A brief theory and work-flow description is followed by two real-case demonstrations from Czech Republic, Europe: first, a proof-test on a well-studied seismically active area of West Bohemia/Vogtland and second, an application to an uprising geothermal project in Litoměřice, where no seismic activity was detected in years of monitoring.

地下人类活动，如采矿、页岩气和石油开采、废水处理或地热发电厂，可能引发地震；因此，它们由当地地震台网监测。理想的地震网络具有三角网格，其间距等于最小深度的两倍，并且没有相关的工业噪音。在实际情况中，网络敏感性会因靠近嘈杂的道路、工厂或私人花园的站点而出现偏差，而没有一个站点位于最佳节点。灵敏度也是检测算法类型和设置的函数。本案例研究的目的是提出无地震活动情况下网络灵敏度计算的工作流程。换句话说：如果地震存在的话，这样的地震网络能够检测到的地震有多小？这种网络灵敏度是站点噪声水平的函数，站源几何形状以及检测算法的设置。在简要的理论和工作流程描述之后，是来自欧洲捷克共和国的两个真实案例演示：首先，对西波希米亚/沃格特兰的一个经过充分研究的地震活跃地区进行了验证测试，其次是在利托梅日采的一个崛起的地热项目中的应用，该项目在多年的监测中没有检测到地震活动。