Interevent-time distribution and aftershock frequency in non-stationary induced seismicity

Abstract 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...

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Autores principales:	Richard A. J. Post, Matthias A. J. Michels, Jean-Paul Ampuero, Thibault Candela, Peter A. Fokker, Jan-Diederik van Wees, Remco W. van der Hofstad, Edwin R. van den Heuvel
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/839d9ba1e14c4c3e88c2a11c81156406
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spelling	oai:doaj.org-article:839d9ba1e14c4c3e88c2a11c811564062021-12-02T14:26:54ZInterevent-time distribution and aftershock frequency in non-stationary induced seismicity10.1038/s41598-021-82803-22045-2322https://doaj.org/article/839d9ba1e14c4c3e88c2a11c811564062021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82803-2https://doaj.org/toc/2045-2322Abstract 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.Richard A. J. PostMatthias A. J. MichelsJean-Paul AmpueroThibault CandelaPeter A. FokkerJan-Diederik van WeesRemco W. van der HofstadEdwin R. van den HeuvelNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Richard A. J. Post Matthias A. J. Michels Jean-Paul Ampuero Thibault Candela Peter A. Fokker Jan-Diederik van Wees Remco W. van der Hofstad Edwin R. van den Heuvel Interevent-time distribution and aftershock frequency in non-stationary induced seismicity
description	Abstract 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.
format	article
author	Richard A. J. Post Matthias A. J. Michels Jean-Paul Ampuero Thibault Candela Peter A. Fokker Jan-Diederik van Wees Remco W. van der Hofstad Edwin R. van den Heuvel
author_facet	Richard A. J. Post Matthias A. J. Michels Jean-Paul Ampuero Thibault Candela Peter A. Fokker Jan-Diederik van Wees Remco W. van der Hofstad Edwin R. van den Heuvel
author_sort	Richard A. J. Post
title	Interevent-time distribution and aftershock frequency in non-stationary induced seismicity
title_short	Interevent-time distribution and aftershock frequency in non-stationary induced seismicity
title_full	Interevent-time distribution and aftershock frequency in non-stationary induced seismicity
title_fullStr	Interevent-time distribution and aftershock frequency in non-stationary induced seismicity
title_full_unstemmed	Interevent-time distribution and aftershock frequency in non-stationary induced seismicity
title_sort	interevent-time distribution and aftershock frequency in non-stationary induced seismicity
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/839d9ba1e14c4c3e88c2a11c81156406
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Interevent-time distribution and aftershock frequency in non-stationary induced seismicity

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