Efficient selective filtering of seismic data using multiscale decomposition

Seismic signal processing is an important task in geophysics sounding and represents a permanent challenge in petroleum exploration. Although seismograms could in principle give us a picture of a geological structure, they are very contaminated by spurious signals and the ground roll noise is a strongly undesired signal present in the seismograms - it does not carry physical information about the deep geological structures. This fact demands a big effort in developing new filtering methodologies. Using discrete wavelet transform, an efficient filtering for suppression of the ground roll is presented. In this method, seismic data is decomposed in multiple scales. We can remove the noise as a surgical operation in each scale, just from the regions where they are present or strong, allowing us to preserve the maximum of relevant information.