Revisit seismic attenuation attributes: Influences of the spectral balancing operation on seismic attenuation analysis
Fangyu Li, Rongchang Liu, Yihuai Lou, Naihao Liu
Abstract
Seismic attenuation analysis is important for seismic processing and quantitative interpretation. Nevertheless, classic quality factor estimation methods make certain assumptions that may be invalid for a given geologic target and seismic volume. For this reason, seismic attenuation attribute analysis, which reduces some of the theoretical assumptions, can serve as a practical alternative in apparent attenuation characterization. Unfortunately, most of the published literature defines seismic attenuation attributes based on a specific source wavelet assumption, such as the Ricker wavelet, rather than wavelets that exhibit the relatively flat spectrum produced by modern data processing workflows. One of the most common processing steps is to spectrally balance the data either explicitly in the frequency domain or implicitly through wavelet shaping deconvolution. If the poststack seismic data have gone through spectral balancing/whitening to improve their seismic resolution, the wavelet would exhibit a flat spectrum instead of a Ricker or Gaussian shape. We have addressed the influence of spectral balancing on seismic attenuation analysis. Our mathematical analysis shows that attenuation attributes are still effective for poststack seismic data after certain types of spectral balancing. More importantly, this analysis explains why seismic attenuation attributes work for real seismic applications with common seismic processing procedures. Synthetic and field data examples validate our conclusions.