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Published July 1, 2020 | Published
Journal Article Open

An array-based receiver function deconvolution method: methodology and application

Abstract

Receiver functions (RFs) estimated on dense arrays have been widely used for the study of Earth structures across multiple scales. However, due to the ill-posedness of deconvolution, RF estimation faces challenges such as non-uniqueness and data overfitting. In this paper, we present an array-based RF deconvolution method in the context of emerging dense arrays. We propose to exploit the wavefield coherency along a dense array by joint inversions of waveforms from multiple events and stations for RFs with a minimum number of phases required by data. The new method can effectively reduce the instability of deconvolution and help retrieve RFs with higher fidelity. We test the algorithm on synthetic waveforms and show that it produces RFs with higher interpretability than those by the conventional RF estimation practice. Then we apply the method to real data from the 2016 Incorporated Research Institutions for Seismology (IRIS) community wavefield experiment in Oklahoma and are able to generate high-resolution RF profiles with only three teleseismic earthquakes recorded by the temporary deployment. This new method should help enhance RF images derived from short-term high-density seismic profiles.

Additional Information

© The Author(s) 2020. Published by Oxford University Press on behalf of The Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) Accepted 2020 March 7. Received 2020 March 7; in original form 2019 June 24. We thank the team of IRIS community wavefield experiment for deployments and making the data readily accessible through IRIS Data services (Anderson et al.2016). We thank Rob Clayton and YoungHee Kim for helpful conversations. We thank Elmer Ruigrok and an anonymous reviewer for providing constructive reviews. This research is financially supported by NSF grant 1722879.

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August 19, 2023
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