Automated Detection of Dynamic Earthquake Triggering by the High‐Frequency Power Integral Ratio. Issue 22 (29th November 2019) - Yun, Naidan; Zhou, Shiyong; Yang, Hongfeng; Yue, Han; Zhao, Li
Abstract: Dynamic earthquake triggering can be used to investigate the responses of faults to stress disturbances. We develop a new method to detect dynamic triggering by estimating high‐frequency energy change before and during teleseismic waves using the HIgh‐Frequency power Integral ratio (HiFi). Our method is able to identify local events independent of earthquake catalog or subjective judgements. The significance in energy change is evaluated by a statistical analysis of the background ratio in a large number of days, which can suppress the influence of noise and variations in the background seismicity and yield a confidence level of dynamic triggering (0–1). We apply the HiFi method to the Geysers Geothermal Field in California, and the results are largely consistent with previous reports from the β statistic. By comparing the results of HiFi and β statistic, we select a confidence level range of 0.918–0.947 as the optimum threshold to identify dynamic triggering in the region. Plain Language Summary: Dynamic triggering is related to dynamic stress change caused by the passage of teleseismic waves and represents one of the earthquake interactions critical to advancing our understanding of earthquake physics. It can be used to investigate the responses of faults to the stress disturbance so as to monitor the temporal variation in stress status. However, the physical processes of earthquake triggering are still in debate, which require systematic analysis of large amounts of data. Widely used methods to detect dynamic triggering are often time‐consuming and depend on local earthquake catalogs or subjective judgements for event identification. We develop a new automatic method to detect dynamic triggering by directly comparing the high‐frequency energies before and during the teleseismic waves. Moreover, we suppress the influence of noise and variations in the background seismicity and provide confidence levels for dynamic triggering. We apply our method to the Geysers Geothermal Field, and a comparison with previous results demonstrates its effectiveness. Key Points: Develop a new automatic method to detect dynamic triggering and evaluate its confidence level Influence of noise and variations in the background seismicity can be suppressed Effectiveness of the new method is demonstrated by applying to the Geysers Geothermal Field