Seismic Attributes for the ExplorationistWhat are Seismic Attributes?

"Seismic Attributes are all the information obtained from seismic data, either by direct measurements or by logical or experience based reasoning." (Taner, 2000)

Seismic attributes typically provide information relating to the amplitude, shape, and/or position of the seismic waveform.

Families of Attributes (based on method of generation)

Complex Trace Attributes--The seismic data is treated as an analytic trace, which contains both real and imaginary parts. Various amplitude, phase, and frequency attributes can be calculated. Includes:

Instantaneous Attributes--associated with a point in time Response Attributes--related to a lobe of the energy envelope A(t);

corresponds to anevent, rather than a single time sample

Figure 1. Complex Trace Attributes.

Fourier Attributes--frequency domain attributes obtained through Fourier analysis (e.g., amplitude variation with bandwidth in frequency (avbf), spectral decomposition)

Figure 2. Fourier Attributes.

Time Attributes--related to the vertical position of the waveform in the seismic section (e.g., horizon time picks, isochrons)

Window Attributes--attributes which summarize information from a vertical window of data.

Multi-trace Attributes--attributes calculated using more than one input seismic trace, which provide quantitative information about lateral variations in the seismic data (e.g., coherence, dip/azimuth)

Some representative seismic attributes

Instantaneous Attributes

Envelope Instantaneous Phase Instantaneous Frequency Weighted Average Frequency Apparent Polarity

Response Attributes

Response Amplitude Response Phase Response Frequency Response Length Skewness Rise Time

Frequency Attributes

avbf Spectral Decomposition

Window Attributes

Maximum Absolute Amplitude Time of Maximum Absolute Amplitude Average Absolute Amplitude Sum of Absolute Amplitudes Average Instantaneous Frequency Number of Zero Crossings Largest Peak/Trough Amplitude Difference Largest Peak/Trough Time Difference

Multi-trace Attributes

Coherence Dip/Azimuth

Definitions of selected attributes

Instantaneous Attributes

Figure 3. Instantaneous Attributes.

Response Attributes of shaded area

Response Amplitude: maximum envelopeResponse Phase: value of instantaneous phase at time of maximum envelopeResponse Frequency: value of instantaneous frequency at time of maximum envelope

Figure 4. Response Attributes of shaded area.

Spectral Decomposition

Uses the Fourier transform to calculate the amplitude spectrum of a short time window covering the zone of interest.

The amplitude spectrum is tuned by the geologic units within the analysis window, so that units with different rock properties and/or thickness will exhibit different amplitude responses.

Figure 5. Spectral Decomposition.

Seismic Coherence

Seismic Coherence is a measure of the trace-to-trace similarity of the seismic waveform within a small analysis window.

Figure 6. Seismic Coherence.

What physical information is provided by these attributes?

Envelope--presence of gas (bright spots), thin-bed tuning effects, lithology changesPhase--lateral continuity of reflectors, bedding configurationsFrequency--bed thickness, presence of hydrocarbons, fracture zonesSpectral Decomposition--bed thicknessCoherence--faults, fractures, lateral stratigraphic discontinuities

How can I generate attributes?

Most workstation-based seismic interpretation systems have tools for generating a suite of complex trace attributes. The KINGDOM Suite, a PC-based interpretation system from Seismic Micro-Technology, Inc., was used to generate the attributes for this presentation.

Spectral decomposition is a part of the OpenSEIS processing system, available for Unix and Linux platforms from OpenGeoSolutions.

Coherence CubeTM processing can be obtained from Scott Pickford. There are also several software products available which calculate coherence-type attributes (e.g., Variance Cube fromGeoQuest or PostStack ESP from Landmark).

Methods of interpreting attributes

Identify spatial patterns/trends in attribute data

Cross-sectional view Map view (attributes extracted along horizon or from zone of interest) 3D visualization

Tie attributes to well control using statistical methods (e.g., crossplots)

Automatically analyze multiple attributes (with or without well control)

Geostatistics Principal component analysis Cluster analysis Texture analysis

Example--"D" Sand, Sooner Unit, Colorado

Objectives

Determine "D" sand thickness between well control points.

Identify faults/discontinuities which could be barriers to fluid flow in the reservoir.

Figure 7. "D" Sand Thickness from Wells. A large version of this figure is available.

Sooner 3-D seismic survey

Black horizons delineate seismic reflections corresponding to the top and bottom of the "D" sand. Over most of the 3-D survey area, the "D" sand is below seismic resolution (a "thin bed"). Below seismic resolution, reflections from the top and bottom of the sand maintain a constant temporal separation, which is unrelated to the true sand thickness. Envelope, frequency, and spectral decomposition attributes, which have been used elsewhere to estimate bed thickness, will be examined as potential predictors of "D" sand thickness

Figure 8. Vertical Seismic Section.

The envelope attribute has been calculated for the entire Sooner seismic data volume. A cross-sectional slice through the envelope volume gives a 2-D view of how this attribute varies in time. 3-D visualization can be used to display the spatial distribution of high envelope amplitudes (blue).

Figure 9. Cross-sectional view and 3-D visualization.

A map view shows how the envelope attribute varies laterally along the horizon corresponding to the top of "D" sand. This view is used to identify spatial patterns

in the envelope amplitude which may correspond to changes in sand thickness. In general, higher envelope amplitudes correspond to thicker sands.

Figure 10. Envelope Attribute extracted along top "D" sand horizon. Black contours of "D" sand thickness based on well data. A large version of this figure is available.

A map of instantaneous frequency extracted along the horizon corresponding to the top of "D" sand. In general, lower frequencies correspond to thicker sands.

Figure 11. Instantaneous frequency extracted along top "D" sand horizon. Black contours of "D" sand thickness based on well data. A large version of this figure is available.

Spectral Decomposition--Selected frequency slices from the spectral decomposition of a 50 ms window centered on the "D" sand. Of these slices, the 30 Hz slice appears to be the best at imaging "D" sand thickness.

Figure 12. Spectral Decomposition--50 ms window centered on "D" sand. Black contours of "D" sand thickness based on well data. A large version of this figure is available.

A more detailed analysis of the spectral decomposition shows that 29 Hz is the best frequency for imaging "D" sand thickness.

Figure 13. Spectral Decomposition--29 Hz--50 ms window centered on "D" sand. Black contours of "D" sand thickness based on well data. A large version of this figure is available.

Crossplots of attributes versus "D" sand thickness give a quantitative estimate of the relationship between each attribute and sand thickness. Because the "D" sand is a thin bed, the seismic isochron does not indicate true bed thickness. Instantaneous frequency and envelope both show a gross correlation to "D" sand thickness, but there is a large amount of scatter in the data. The 29 Hz component of the spectral decomposition gives the best fit to "D" sand thickness.

Figure 14. Crossplots of attribute versus "D" sand thickness.

Instantaneous phase and coherence, extracted along the "D" sand horizon, are examined for discontinuities/faults which may indicate reservoir flow boundaries.

Figure 15. Instantaneous phase. A large version of this figure is available.

NE-trending linear discontinuities in the northern portion of the survey area are visible on the coherence slice.

Figure 16. Coherence. A large version of this figure is available.

Sooner 3-D Summary

The 29 Hz Spectral Decomposition slice is the best single attribute for predicting "D" sand thickness.

A set of linear discontinuities in the northern part of the Sooner 3-D survey is best imaged on the Coherence map. These discontinuities may be faults, and are potential reservoir flow boundaries.

Conclusions

Attributes reveal information which is not readily apparent in the raw seismic data

Dozens of seismic attributes can be calculated using a variety of software packages

Attributes may be interpreted singly or using multi-attribute analysis tools

Different attributes reflect different physical properties of the underlying rock system

Acknowledgments

Access to The KINGDOM Suite software and the Sooner 3-D seismic data set was provided by Seismic Micro-Technology, Inc.

Suggested Readings

Bahorich, M. S., and S. L. Farmer, 1995, 3-D seismic coherency for faults and stratigraphic features: The Leading Edge, v. 14, p. 1053-1058.

Bodine, J. H., 1986, Waveform analysis with seismic attributes, Oil & Gas Journal, v. 84, June 9, p. 59-63.

Gersztenkorn, A., and K. J. Marfurt, 1999, Eigenstructure based coherence computations as an aid to 3-D structural and stratigraphic mapping: Geophysics, v. 64, p. 1468-1479.

Marfurt, K. J., R. L. Kirlin, S. L. Farmer, and M. S. Bahorich, 1998, 3-D seismic attributes using a running window semblance-based algorithm: Geophysics, v. 63, p. 1150-1165.

Marfurt, K. J., and R. L. Kirlin, 2001, Narrow-band spectral analysis and thin-bed tuning: Geophysics, v. 66, p. 1274-1283.

Nissen, S. E., 2000, Interpretive aspects of seismic coherence and related multi-trace attributes, Kansas Geological Survey Open File Report 2000-84: Available Online

Partyka, G., 2001, Seismic thickness estimation: three approaches, pros and cons, 71st Ann. Internat. Mtg: Soc. of Expl. Geophys., p. 503-506.

Partyka, G., J. Gridley, and J. Lopez, 1999, Interpretational applications of spectral decomposition in reservoir characterization: The Leading Edge, v. 18, p. 353-360.

Sippel, M. A., R. W. Pritchett, and B. A. Hardage, 1996, Integrated reservoir management to maximize oil recovery from a fluvial-estuarine reservoir: A case study of the Sooner Unit, Colorado, in Johnson, K. S. (ed.), Deltaic Reservoirs in the Southern Midcontinent, 1993 symposium: Oklahoma Geological Survey Circular 98, p. 288-292.

Taner, M. T., F. Koehler, and R. E. Sheriff, 1979, Complex seismic trace analysis: Geophysics, v. 44, p. 1041-1063.

Taner, M. T., 2000, Attributes revisited: Available Online