Seismic sequence attribute map (SSAM)

Digital Imaging and Deconvolution: The ABCs of Seismic Exploration and Processing

Series	Geophysical References Series
Title	Digital Imaging and Deconvolution: The ABCs of Seismic Exploration and Processing
Author	Enders A. Robinson and Sven Treitel
Chapter	12
DOI	http://dx.doi.org/10.1190/1.9781560801610
ISBN	9781560801481
Store	SEG Online Store

In sequence stratigraphy, it is recognized that seismic data contain useful stratigraphic information. Often, however, extracting such qualitative information is tedious. Sometimes it requires entire teams of interpreters to perform the analysis. Nevertheless, a great deal of quantitative information pertaining to sequence stratigraphy lies hidden in the data. Bahorich and Bridges (1992) and Bahorich (1993) proposed the seismic sequence attribute map (SSAM).

The SSAM represents a quick yet robust technique for extracting quantitative seismic information that then can be related to stratigraphy. The technique invokes calculating the seismic attribute between identified sequence boundaries, taking the average attributes along the vertical lines between the two boundaries, and displaying those averages in map form. For example, the average amplitude of a sequence can be calculated between two digitized horizons and displayed as a map.

Seismic sequence attribute mapping involves reading digital seismic data into a computer, using various statistical computations to summarize the data between two defined time or depth boundaries, and presenting those data in map form. Subtle patterns in those statistics might not be apparent on individual seismic lines but often can become clear when viewed in map form. Furthermore, such subtle changes can provide the key to understanding lithology or fluid content — information that is critical to successful exploration or exploitation.

Seismic sequence attribute maps represent summarized zones of seismic data presented in map form. Attributes that can be used include amplitude, frequency, phase lead, frequency slope, amplitude decay, frequency decay, dip, stratigraphic dip, signal-to-noise ratio, and trace similarity. For example, a sequence trace similarity map can be generated by reading in an interval of seismic data on multiple seismic lines, crosscorrelating adjacent traces, measuring the covariance, and displaying the covariance as a map (Figure 4).

Figure 4.  A seismic sequence attribute map (SSAM).

Figure 5.  A flowchart of the SSAM method.

How is the SSAM generated? To generate an average envelope-amplitude map, we start by loading the envelope-amplitude data into the workstation, along with interpreted sequence boundaries. Next, we delineate the upper and lower boundaries of the sequence of interest on the seismic data. Then we estimate the average envelope amplitude along the vertical lines within the sequence boundaries. Finally, we can contour the resulting average envelope-amplitude horizon to produce a map of the average envelope-amplitude variation within a sequence (Figure 5).

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Table of Contents (book)

Also in this chapter

• Interpretive processing
• Seismic attributes
• Instantaneous attributes
• Coherence cube (C3)
• SSAM and C3
• Appendix L: Design of Hilbert transforms
• Appendix M: Exercises

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