Vibroseis deconvolution: A comparison of pre and post correlation vibroseis deconvolution data in real noisy data

Vibroseis is a source used commonly for inland seismic exploration. This non-destructive source is often usedin urban areas with strong environmental noise. The main goal of seismic data processing is to increase thesignal/noise ratio where a determinant step is deconvolution. Vibroseis seismic data do not meet the basicminimum-phase assumption for the application of spiking and predictive deconvolution, therefore varioustechniques, such as phase shift, are applied to the data, to be able to successfully perform deconvolution ofvibroseis data.This work analyzes the application of deconvolution techniques before and after cross-correlation on a real dataset acquired for high resolution prospection of deep aquifers. In particular, we compare pre-correlation spikingand predictive deconvolution with Wiener filtering and with post-correlation time variant spectral whiteningdeconvolution. The main result is that at small offsets, post cross-correlation spectral whitening deconvolutionand pre-correlation spiking deconvolution yield comparable results, while for large offsets the best result isobtained by applying a pre-cross-correlation predictive deconvolution.