Coherence Attribute Applications on Seismic Data in Various Guises

Abstract

The iconic coherence attribute is very useful for geologic feature imaging such as faults, deltas, submarine canyons, karst collapse, mass transport complexes, and more. Besides its preconditioning, the interpretation of discrete stratigraphic features on seismic data is also limited by its bandwidth, where in general the data with higher bandwidth yields crisper features than data with lower bandwidth. Some form of spectral balancing applied to the seismic amplitude data can help in achieving such an objective, so that coherence run on spectrally balanced seismic data yields a better definition of the geologic features of interest. The quality of the generated coherence attribute is also dependent in part on the algorithm employed for its computation. In the eigenstructure decomposition procedure for coherence computation, spectral balancing equalizes each contribution to the covariance matrix, and thus yields crisper features on coherence displays. There are other ways to modify the spectrum of the input data in addition to simple spectral balancing, including the amplitude-volume technique (AVT), taking the derivative of the input amplitude, spectral bluing, and thin-bed spectral inversion. We compare some of those techniques, and show their added value in seismic interpretation.

We run energy ratio coherence on input seismic data, and a number of other versions that we generate in terms of voice components obtained by using continuous wavelet transform method of spectral decomposition, spectral balanced version obtained by using thin-bed reflectivity inversion, and AVT attributes. Our comparison of the equivalent time slice displays from the coherence volumes allows us to infer, (a) coherence on spectrally balanced input seismic data yields better lineament detail, (b) coherence on voice components highlights the discontinuities at different frequencies that show better definition, which can be helpful for their interpretation, (c) multispectral coherence displays show crisper definition of lineaments and so are useful, (d) coherence run on the versions of the data discussed above after AVT shows superior definition of lineaments and hence we recommend should be used in their interpretation.

AAPG Datapages/Search and Discovery Article #90323 ©2018 AAPG Annual Convention and Exhibition, Salt Lake City, Utah, May 20-23, 2018