Spectral Balancing of Seismic Data Using Spectral Decomposition

Abstract

The interpretation of discrete stratigraphic features on seismic data is limited by both its bandwidth and its signal-to-noise ratio. Unfortunately, well resolved reflections from the top and base of subtle stratigraphic geologic boundaries occur only for thick features imaged by broad band data. Seismically thin stratigraphic features approaching a quarter wavelength thickness give rise to composite or “tuned” seismic reflections. Different spectral decomposition methods provide an effective way of examining the seismic response of stratigraphic geologic features in terms of spectral components and so help in the interpretation. The phase components help with the interpretation of the discontinuity features as well as stratigraphic features such as onlap, offlap, and erosional unconformities. In this study we first illustrate the applications of a newer attribute derived during spectral decomposition, called voice components, in terms of more accurate interpretation of the subsurface features. We follow this by describing an amplitude-friendly method for spectral balancing, which enhances the frequency content of the data and at the same time preserves the geologic tuning features and amplitudes. Spectral decomposition of seismic data that are spectrally balanced and interpreted in terms of the voice components leads to more accurate definition of the features of interest. We demonstrate some of these applications and in particular the detailed definition of faults and fractures. Such discontinuity information can be interpreted better on coherence attribute displays in the zone of interest. Coherence attribute computation performed on spectral decomposition after spectral balancing yields higher detail with regard to the faults and fractures or other discontinuity features such as channels, reefs, etc.

AAPG Datapages/Search and Discovery Article #90259 ©2016 AAPG Annual Convention and Exhibition, Calgary, Alberta, Canada, June 19-22, 2016