Summary
Seismic attributes are routinely used to assist for seismic interpretation and reservoir characterization. The more commonly used geometric attributes include 1) reflector dipazimuth, 2) coherence, and 3) curvature. Most publications seismic attributes were used in time-migrated data. While interpreting seismic attributes such as coherence on depth migrated data requires a slightly different perspective. First, the samples are meters or feet rather than as milliseconds. Second, Fourier Transform is necessary during the estimation of seismic attributes. They are computed as cycles/km (or alternatively as cycles/1000 ft) rather than as cycles/s or Hertz, with the dominant wavenumber decreasing with increasing velocities at depth. Third, we conventionally use a constant user-defined window to calculate those attribute, while the constant window size is not capable to handle layers with different thickness at the same time, the complexity of structure in seismic data makes it invalid, especially for the depth migrated data.
In this paper we proposed a workflow to estimate the seismic attributes using a self-adaptive window size by integrating the result from seismic spectrum analysis. We test our algorithm on both time and depth migrated data from an oilfield of East China.
