Post Richard A J, Michels Matthias A J, Ampuero Jean-Paul, Candela Thibault, Fokker Peter A, van Wees Jan-Diederik, Hofstad Remco W van der, Heuvel Edwin R van den
Department of Mathematics and Computer Science, Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands.
Institute for Complex Molecular Systems, Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands.
Sci Rep. 2021 Feb 11;11(1):3540. doi: 10.1038/s41598-021-82803-2.
The initial footprint of an earthquake can be extended considerably by triggering of clustered aftershocks. Such earthquake-earthquake interactions have been studied extensively for data-rich, stationary natural seismicity. Induced seismicity, however, is intrinsically inhomogeneous in time and space and may have a limited catalog of events; this may hamper the distinction between human-induced background events and triggered aftershocks. Here we introduce a novel Gamma Accelerated-Failure-Time model for efficiently analyzing interevent-time distributions in such cases. It addresses the spatiotemporal variation and quantifies, per event, the probability of each event to have been triggered. Distentangling the obscuring aftershocks from the background events is a crucial step to better understand the causal relationship between operational parameters and non-stationary induced seismicity. Applied to the Groningen gas field in the North of the Netherlands, our model elucidates geological and operational drivers of seismicity and has been used to test for aftershock triggering. We find that the hazard rate in Groningen is indeed enhanced after each event and conclude that aftershock triggering cannot be ignored. In particular we find that the non-stationary interevent-time distribution is well described by our Gamma model. This model suggests that 27.0(± 8.5)% of the recorded events in the Groningen field can be attributed to triggering.
地震的初始影响范围可通过触发成群的余震而显著扩大。对于数据丰富的平稳天然地震活动，这种地震-地震相互作用已得到广泛研究。然而，诱发地震活动在时间和空间上本质上是不均匀的，且事件目录可能有限；这可能会妨碍区分人为诱发的背景事件和触发的余震。在此，我们引入一种新颖的伽马加速失效时间模型，用于有效分析此类情况下的事件间隔时间分布。它考虑了时空变化，并针对每个事件量化其被触发的概率。将模糊的余震与背景事件区分开来是更好理解操作参数与非平稳诱发地震活动之间因果关系的关键一步。应用于荷兰北部的格罗宁根气田，我们的模型阐明了地震活动的地质和操作驱动因素，并已用于测试余震触发情况。我们发现格罗宁根的危险率在每次事件后确实有所提高，并得出余震触发不能被忽视的结论。特别是，我们发现非平稳的事件间隔时间分布可以很好地用我们的伽马模型来描述。该模型表明，格罗宁根气田记录的事件中有27.0(±8.5)%可归因于触发。
