Uncertainty reduction of stress tensor inversion with data-driven catalogue selection
- The selection of earthquake focal mechanisms (FMs) for stress tensor inversion (STI) is commonly done on a spatial basis, that is, hypocentres. However, this selection approach may include data that are undesired, for example, by mixing events that are caused by different stress tensors when for the STI a single stress tensor is assumed. Due to the significant increase of FM data in the past decades, objective data-driven data selection is feasible, allowing more refined FM catalogues that avoid these issues and provide data weights for the STI routines. We present the application of angular classification with expectation-maximization (ACE) as a tool for data selection. ACE identifies clusters of FM without a priori information. The identified clusters can be used for the classification of the style-of-faulting and as weights of the FM data. We demonstrate that ACE effectively selects data that can be associated with a single stress tensor. Two application examples are given for weighted STI from South America. We use the resultingThe selection of earthquake focal mechanisms (FMs) for stress tensor inversion (STI) is commonly done on a spatial basis, that is, hypocentres. However, this selection approach may include data that are undesired, for example, by mixing events that are caused by different stress tensors when for the STI a single stress tensor is assumed. Due to the significant increase of FM data in the past decades, objective data-driven data selection is feasible, allowing more refined FM catalogues that avoid these issues and provide data weights for the STI routines. We present the application of angular classification with expectation-maximization (ACE) as a tool for data selection. ACE identifies clusters of FM without a priori information. The identified clusters can be used for the classification of the style-of-faulting and as weights of the FM data. We demonstrate that ACE effectively selects data that can be associated with a single stress tensor. Two application examples are given for weighted STI from South America. We use the resulting clusters and weights as a priori information for an STI for these regions and show that uncertainties of the stress tensor estimates are reduced significantly.…
Verfasserangaben: | Sebastian von SpechtORCiDGND, Oliver HeidbachORCiDGND, Fabrice Pierre CottonORCiDGND, Arno ZangORCiDGND |
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DOI: | https://doi.org/10.1093/gji/ggy240 |
ISSN: | 0956-540X |
ISSN: | 1365-246X |
Titel des übergeordneten Werks (Englisch): | Geophysical journal international |
Verlag: | Oxford Univ. Press |
Verlagsort: | Oxford |
Publikationstyp: | Wissenschaftlicher Artikel |
Sprache: | Englisch |
Datum der Erstveröffentlichung: | 19.06.2018 |
Erscheinungsjahr: | 2018 |
Datum der Freischaltung: | 15.10.2021 |
Freies Schlagwort / Tag: | Inverse Theory; Kinematics of crustal; Seismicity; Statistical Methods; mantle deformation; tectonics |
Band: | 214 |
Ausgabe: | 3 |
Seitenanzahl: | 14 |
Erste Seite: | 2250 |
Letzte Seite: | 2263 |
Organisationseinheiten: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften |
DDC-Klassifikation: | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften |
Peer Review: | Referiert |
Publikationsweg: | Open Access / Green Open-Access |