25.1 Definition and history

When seismic processing is complete, we are left with a dense 3D matrix of numbers representing the migrated data volume. This is the amplitude data that primary interpretation deals with to extract structural and stratigraphic information as outlined in earlier chapters. But there are infinitely many ways to derive secondary quantities from the primary data cube. We could take, for instance, the signed logarithm of every sample value, or the cosine, or some signed fractional power. Or we could do a root-mean-square windowed average throughout the data, or the cross correlation of every trace with its neighbors, and so on. Each operation derives a new volume as large as the amplitude volume. All of these examples would be termed attributes.

As a working definition, we can say that seismic attributes are specific quantities of geometric, kinematic, dynamic, or statistical features derived from seismic data. Such attributes are used to visually enhance or isolate features of interest. They may also be calibrated to well control for reservoir property prediction. Note that attributes can lead to reservoir property estimates, but these properties are not themselves considered attributes.

Attributes are a relative new-comer in seismic data analysis, arriving only in the early 1970s in the form of complex trace analysis ^[173]. But this was arrival in name only. A vast array of procedures had been developed in data processing that could, and would, later be applied to interpretation problems. These included cross correlation, convolution, semblance, coherency, and many...