An array-based receiver function deconvolution method: methodology and application. Issue 1 (14th March 2020)

• Record Type: Journal Article
• Authors: Zhong, Minyan; Zhan, Zhongwen
• Is Part Of: Geophysical journal international. Volume 222:Issue 1(2020)
• Page Start: 1
• Page End: 14
• Publication Date: 2020-03-14
• Subjects: Joint inversion -- Time-series analysis -- Computational seismology; Geophysics -- Periodicals; 550
• DOI: 10.1093/gji/ggaa113
• Languages: English
• ISSNs: 0956-540X

Abstract

SUMMARY: 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.