Partitioning local seismogram wavefields using continuous wavelet transform methods for IRIS wavefield experiment arrays

Abstract

SUMMARY We applied nonlinear thresholding and scale–time gating in the continuous wavelet transform (CWT) domain to denoise, identify and characterize seismic phases contained in gradiometer and phased array waveforms of four seismic events recorded during the 2016 Incorporated Research Institutions of Seismology Wavefields Experiment in northern Oklahoma. A dense, 80-element three component phased array was subset from the linear array deployments to examine background noise, waveform coherence and seismic wave composition for local explosion and earthquake waveforms. CWT techniques were also used to significantly improve gradiometery analyses for data recorded by the geodetic array subexperiment. We observed as much as two orders of magnitude gain in the data signal-to-noise ratio. We also saw improvement in array beam quality after denoising the seismic data. Using the signal partitioning technique, we were able to extract and identify many phases based on their positions on the scale–time plane. CWT denoising and wavefield decomposition techniques also improved gradiometry analysis results from the 112-element geodetic array (also called the gradiometer) since waves could be separated before the computation of wave attributes. The operations of removing noise and gating out signal phases improved signal coherence across array records and provided clear P wave onsets on horizontal records, which can mitigate phase picking error and resulting event location uncertainty.