CWT -> Peak Frequency, Peak Magnitude, Peak Phase, Peak Magnitude Above Average, Roughness, Range Trimmed Mean Magnitude, and Slope
The statistical summary attributes (i.e., Bandwidth, Reconstructed Data, Mean Frequency, Peak Frequency, Peak Magnitude, Peak Magnitude Above Average, Peak Phase, Modeled, Residual, Roughness, Range Trimmed Mean Magnitude, Slope) generated by the Continuous Wavelet Transform (CWT) can also help in the interpretation of anomalies associated with reservoirs or other zones of interest (AASPI Documentation; Zhang, 2010).
The statistical summary attributes can be also useful for providing more information sensitive to stratigraphy or reservoir physical properties (Chopra and Marfurt, 2007). Attribute results can be analyzed in different ways, from a plan view, vertical transects, or draped over a horizon display.
Recommended color palette:
For the statistical summary attributes a divergent color scheme is suggested. The midpoint color is white to emphasize the progression outward two different hues. In the examples below, the hues were set to light blue and yellow to better highlight geologic features. Or even, a grayscale gradient color scheme is suggested. The color progression could begin with white (to highlight useful geological features) and finish with black (to denote shadow areas), or vice-versa. We suggest using the histogram of values to guide setting color value thresholds.
Recommended color palette:
For the Peak Phase attribute, a cyclic color scheme is suggested. In this color palette, the hues wrap around so that the red follows purple. A specific color is assigned to different phase ranges, so then the display can be used to infer the continuity of seismic events. We suggest using the histogram of values to guide setting color value thresholds.
Computation: The statistical summary attributes are additional outputs of the spectral decomposition based on Complex Matching Pursuit (refer to Spectral Decomp-> CWT -> Spectral Magnitude, Spectral Phase, Spectral Voice Components, and Spectral Shape (Ridge) attributes description section). Prior to computing these summary attributes, the amplitude volume (time or depth domain) is spectrally whitened to account for changes in the source wavelet with depth and a non-flat source spectrum. Thereafter, the output volume shows a relatively flat spectrum bound by two tails (see Figure 2). Following this behavior, the statistical summary attributes are generated.
- AASPI documentation, http://mcee.ou.edu/aaspi/documentation/Spectral_Attributes-spec_cwt.pdf
- Chopra, S. and K. J. Marfurt, 2007, Seismic attributes for prospect identification and reservoir characterization: SEG Geophysical development series, 11, 123 – 151.
- Zhang, K., 2010, Seismic attribute analysis of unconventional reservoirs, and stratigraphic features: PhD Thesis, University of Oklahoma.