In this study, we present an application of textural analysis to 3D seismic volumes. Specifically, we combine image textural analysis with a neural network classification to quantitatively map seismic facies in three-dimensional data. Key advantages of this approach are:

Finally, we extend our textural analysis-based seismic facies classification technique to interpretation of AVO attribute volumes, such as “A + B” (AVO intercept + gradient), to reduce the inherent nonuniqueness of seismic facies to geologic and lithologic facies, and simplify the facies analysis of complex, mixed-impedance reservoirs.

Seismic facies analysis is a powerful qualitative technique used in stratigraphic analysis from seismic...

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