Multi-window spectrum analysis of Búzios oil field PSDM seismic data applied to frequency attenuation study

Abstract

The intrinsic attenuation is often quantified using the inverse quality factor Q. Methods to estimate Q are mainly based on time domain or frequency domain and sensitive to amplitude and/or frequency band variations. In this sense, noise, signal artifacts or processing steps can alter the amplitude, frequency content and the waveform, what may lead to inaccurate calculations of Q. A way to better understand the frequency band variation in seismic data and verify patterns or problems occurring in the signal frequency band is performing layered or window-by-window spectrum analysis. This work describes a multi-window spectrum analysis method used to better understand the frequency attenuation process as the seismic wave travels through the sediments from the sea bottom down to the reservoir depths in a 3D Kirchhoff Pre-Stack Depth Migrated (PSDM) seismic data from Búzios oil field. To perform the spectral analysis in frequency domain, the PSDM volume was converted to time domain using the same interval velocity volume used to depth-migrate the data. The variation of frequency band as the signal propagates through the sediment package was analyzed dividing the studied crossline sections in 13 layers of 200 ms each, from sea bottom down to the base of pre-salt reservoir formations. The results suggest that most part of higher frequency loss has been occurred in post-salt package. This may be an indication of significant viscoelastic behavior or strong stratigraphic filtering of this interval. Sequentially, higher frequency content is lost slowly from salt top down to the last layer located inside pre-salt formation. Very slight frequency spectrum variation below salt top indicates elastic behavior of the salt formation and underling pre-salt formation in this interval. The spectrum analysis method proposed here has shown to be useful and efficient to identify intervals of different attenuation patterns in seismic data. Additionally, the frequency band study produced by our spectrum analysis can be used to quality-control Q-factor estimation computed by different methods.