Ground-motion prediction models for induced earthquakes in the Groningen gas field, the Netherlands
File(s)Bommer et al 2022_Groningen GMPEs.pdf (9.5 MB)
Published version
Author(s)
Type
Journal Article
Abstract
Small-magnitude earthquakes induced by gas production in the Groningen field in the Netherlands have prompted the development of seismic risk models that serve both to estimate the impact of these events and to explore the efficacy of different risk mitigation strategies. A core element of the risk modelling is ground-motion prediction models (GMPM) derived from an extensive database of recordings obtained from a dense network of accelerographs installed in the field. For the verification of damage claims, an empirical GMPM for peak ground velocity (PGV) has been developed, which predicts horizontal PGV as a function of local magnitude, ML; hypocentral distance, Rhyp; and the time-averaged shear-wave velocity over the upper 30 m, VS30. For modelling the risk due to potential induced and triggered earthquakes of larger magnitude, a GMPM for response spectral accelerations has been developed from regressions on the outputs from finite-rupture simulations of motions at a deeply buried rock horizon. The GMPM for rock motions is coupled with a zonation map defining frequency-dependent non-linear amplification factors to obtain estimates of surface motions in the region of thick deposits of soft soils. The GMPM for spectral accelerations is formulated within a logic-tree framework to capture the epistemic uncertainty associated with extrapolation from recordings of events of ML ≤ 3.6 to much larger magnitudes.
Date Issued
2022-12
Date Acceptance
2022-10-21
Citation
Journal of Seismology, 2022, 26 (6), pp.1157-1184
ISSN
1383-4649
Publisher
Springer Science and Business Media LLC
Start Page
1157
End Page
1184
Journal / Book Title
Journal of Seismology
Volume
26
Issue
6
Copyright Statement
© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
https://link.springer.com/article/10.1007/s10950-022-10120-w
Publication Status
Published
Date Publish Online
2022-11-07