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General Comments 

Table 1 defines terms used in seismic attribute analysis today. The explosion of potentially useful attributes requires seismic interpreters to keep current and to have the most effective, efficient “fit for purpose” work flows. One important aspect of these work flows is “starting with the end in mind.” For example, if amplitudes or wide azimuths are critical, the seismic acquisition and processing for those SAs should be optimized.  

Unfortunately, the potential for abusing seismic attributes also has increased. One common abuse of seismic attributes often occurs “because it’s there.” Interpreters today have access to many SAs on their workstations but often have very little time to understand these attributes properly, model them, and correctly correlate them with ground truth and the principles of physics.  

Be wary of pretty SAs that are not well understood. This can damage your credibility while tarnishing the true potential of SAs. Don’t expect your workstation to pop out the solution.  Be wary of “black box” answers. Instead, commit the resources to correlate, model, and understand your SAs and what they can and cannot do.  

Workstations now make it very easy to generate, for example, the third derivative of the instantaneous phase or the second derivative of instantaneous frequency. Even if this SA correlates with ground truth somehow, will you understand it or trust its significance?  

Another abused shortcut often sounds like: “Just give me the one attribute that solves my problem.” In some unusual areas, interpreters have been able to succeed using only a single attribute interpretation. However, I have not yet found an area where a single attribute provides the optimum answer.  

Note in Figure 2 how none of the four attributes alone shows the sand channel very well – but when they are combined, the result is both quantitatively and areally more accurate than any individual attribute. This example shows the dramatic potential of SAs for lithology prediction. We add value by using experience to improve estimates of reservoir properties from seismic (RPFS), reducing risk and helping to quantify uncertainty.  

Therefore, avoid grabbing the first attribute or attributes that seem to work. Instead, develop a robust, efficient work flow that quickly considers many of the most promising attributes and objectively correlates them with seismically scaled and corrected ground truth. Then model these attributes to understand and optimally guide the SA combination to estimate the reservoir properties best and quantify the uncertainty of those estimates.  

There is also a real danger of using too many SAs to “over-fit” the data. With unlimited attributes – and therefore unlimited degrees of freedom  – statistical accidents will occur. The critical step is testing for significance – for example, by blindly dropping one well or zone at a time. The number of attributes ideal for reservoir property estimation typically varies from two to four, depending on the area, data, and objective.

Case History Example 

Despite the pitfalls in seismic attribute analysis (SAA), there are many successful examples of predicting RPFS. For example, consider Figure 2: It is often important and valuable to define the 3-D extent of a channel or sand body. Figure 2 shows an example of combining four 3-D attribute volumes along with the appropriate well information to predict lithology.  

Once you have optimized your SAA workflow, it can dramatically improve property and risk estimates. Robust work flows have been developed on data sets around the world, in clastic and carbonate environments, onshore and offshore. The accuracy of estimates varies with location, data quality, and objectives.  

The speed and accuracy of reservoir modeling and simulation have also been improved using RPFS estimates and associated uncertainty cubes.

Recommendations 

• Keep up-to-date on seismic attributes, SA analysis, and work flows.

• Edit and scale well data to ensure appropriate ground truth ties to the seismic, including positioning, scaling, wavelet and phase issues.

• Understand the physics and significance of SAs by forward modeling. For example, testing the sensitivity to varying thickness or fluid substitution.

• Avoid known abuses or pitfalls, including (a) assuming well data is ground truth; (b) sloppy ties; (c) “because it’s there”; (d) black boxes; (e) endless SA derivatives; (f) single attribute obsession; (g) over-fitting; and (h) not blind testing for significance.

• Determine the most useful SAs, input cubes, and SAA methods for your objectives, and how accurate your RPFS estimates are.

• Optimize your critical SAs, when appropriate, by acquiring/processing 3-D seismic proactively.

• Communicate uncertainty via uncertainty cubes. 

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