Abstract
We investigate the applicability of an array-conditioned deconvolution
technique, developed for analysing borehole seismic exploration data,
to teleseismic receiver functions and data pre-processing steps for
scattered wavefield imaging. This multichannel deconvolution technique
constructs an approximate inverse filter to the estimated source
signature by solving an overdetermined set of deconvolution equations,
using an array of receivers detecting a common source. We find that
this technique improves the efficiency and automation of receiver
function calculation and data pre-processing workflow. We apply this
technique to synthetic experiments and to teleseismic data recorded
in a dense array in northern Canada. Our results show that this optimal
deconvolution automatically determines and subsequently attenuates
the noise from data, enhancing P-to-S converted phases in seismograms
with various noise levels. In this context, the array-conditioned
deconvolution presents a new, effective and automatic means for processing
large amounts of array data, as it does not require any ad-hoc regularization;
the regularization is achieved naturally by using the noise present
in the array itself.
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