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Deconvolution enhanced direction of arrival estimation using one- and three-component seismic arrays applied to ocean induced microseisms

Citation

Gal, M and Reading, AM and Ellingsen, SP and Koper, KD and Burlacu, R and Gibbons, SJ, Deconvolution enhanced direction of arrival estimation using one- and three-component seismic arrays applied to ocean induced microseisms, Geophysical Journal International, 206, (1) pp. 345-359. ISSN 0956-540X (2016) [Refereed Article]


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Copyright Statement

Copyright 2016 The Authors. Published by Oxford University Press on behalf of The Royal Astronomical Society.

DOI: doi:10.1093/gji/ggw150

Abstract

Microseisms in the period of 2-10 seconds are generated in deep oceans and near coastal regions. It is common for microseisms from multiple sources to arrive at the same time at a given seismometer. It is therefore desirable to be able to measure multiple slowness vectors accurately. Popular ways to estimate the direction of arrival of ocean induced microseisms are the conventional (fk) or adaptive (Capon) beamformer. These techniques give robust estimates, but are limited in their resolution capabilities and hence do not always detect all arrivals. One of the limiting factors in determining direction of arrival with seismic arrays is the array response, which can strongly influence the estimation of weaker sources. In this work, we aim to improve the resolution for weaker sources and evaluate the performance of two deconvolution algorithms, Richardson-Lucy deconvolution and a new implementation of CLEAN-PSF. The algorithms are tested with 3 arrays of different aperture (ASAR, WRA and NORSAR) using 1 month of real data each and compared with the conventional approaches. We find an improvement over conventional methods from both algorithms and the best performance with CLEAN-PSF. We then extend the CLEAN-PSF framework to 3 components and evaluate 1 year of data from the Pilbara Seismic Array (PSAR) in north-west Australia. The 3 component CLEAN-PSF analysis is capable in resolving a previously undetected Sn phase.

Item Details

Item Type:Refereed Article
Keywords:time-series analysis, numerical solutions, computational seismology
Research Division:Earth Sciences
Research Group:Geophysics
Research Field:Seismology and Seismic Exploration
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Earth Sciences
Author:Gal, M (Mr Martin Gal)
Author:Reading, AM (Professor Anya Reading)
Author:Ellingsen, SP (Professor Simon Ellingsen)
ID Code:109803
Year Published:2016
Funding Support:Australian Research Council (DP150101005)
Web of Science® Times Cited:4
Deposited By:Earth Sciences
Deposited On:2016-07-04
Last Modified:2017-10-25
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