Seismological Processing of Six Degree-of-Freedom Ground-Motion Data.

gyroscope ring laser rotation seismic exploration seismic tomography seismology

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
03 Dec 2020
Historique:
received: 05 10 2020
revised: 27 11 2020
accepted: 01 12 2020
entrez: 8 12 2020
pubmed: 9 12 2020
medline: 9 12 2020
Statut: epublish

Résumé

Recent progress in rotational sensor technology has made it possible to directly measure rotational ground-motion induced by seismic waves. When combined with conventional inertial seismometer recordings, the new sensors allow one to locally observe six degrees of freedom (6DOF) of ground-motion, composed of three orthogonal components of translational motion and three orthogonal components of rotational motion. The applications of such 6DOF measurements are manifold-ranging from wavefield characterization, separation, and reconstruction to the reduction of non-uniqueness in seismic inverse problems-and have the potential to revolutionize the way seismic data are acquired and processed. However, the seismological community has yet to embrace rotational ground-motion as a new observable. The aim of this paper is to give a high-level introduction into the field of 6DOF seismology using illustrative examples and to summarize recent progress made in this relatively young field. It is intended for readers with a general background in seismology. In order to illustrate the seismological value of rotational ground-motion data, we provide the first-ever 6DOF processing example of a teleseismic earthquake recorded on a multicomponent ring laser observatory and demonstrate how wave parameters (phase velocity, propagation direction, and ellipticity angle) and wave types of multiple phases can be automatically estimated using single-station 6DOF processing tools. Python codes to reproduce this processing example are provided in an accompanying Jupyter notebook.

Identifiants

pubmed: 33287180
pii: s20236904
doi: 10.3390/s20236904
pmc: PMC7731287
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Horizon 2020
ID : 821881

Références

Sensors (Basel). 2013 Apr 08;13(4):4581-97
pubmed: 23567526
Sensors (Basel). 2020 Aug 20;20(17):
pubmed: 32825371
Appl Opt. 1995 Aug 20;34(24):5375-85
pubmed: 21060358
Rev Sci Instrum. 2010 Aug;81(8):084501
pubmed: 20815619
Phys Rev Lett. 2020 Jul 17;125(3):033605
pubmed: 32745436
Science. 2017 Apr 21;356(6335):236-238
pubmed: 28428378

Auteurs

David Sollberger (D)

Institute of Geophysics, ETH Zürich, 8092 Zürich, Switzerland.

Heiner Igel (H)

LMU, 80333 Munich, Germany.

Cedric Schmelzbach (C)

Institute of Geophysics, ETH Zürich, 8092 Zürich, Switzerland.

Pascal Edme (P)

Institute of Geophysics, ETH Zürich, 8092 Zürich, Switzerland.

Dirk-Jan van Manen (DJ)

Institute of Geophysics, ETH Zürich, 8092 Zürich, Switzerland.

Shihao Yuan (S)

LMU, 80333 Munich, Germany.

Ulrich Schreiber (U)

Geodätisches Observatorium Wettzell, TUM, 93444 Bad Kötzting, Germany.

Johan O A Robertsson (JOA)

Institute of Geophysics, ETH Zürich, 8092 Zürich, Switzerland.

Classifications MeSH