Abstract

Seismic interpretation is based on the identification of reflector configuration and continuity, with coherent reflectors having a distinct amplitude, frequency, and phase. Skilled interpreters may classify reflector configurations as parallel, converging, truncated, or hummocky, and use their expertise to identify stratigraphic packages and unconformities. In principal, a given pattern can be explicitly defined as a combination of waveform and reflector configuration properties, although such “clustering” is often done subconsciously. Computer-assisted classification of seismic attribute volumes builds on the same concepts. Seismic attributes not only quantify characteristics of the seismic reflection events, but also measure aspects of reflector configurations. The Mississippi Lime resource play of northern Oklahoma and southern Kansas provides a particularly challenging problem. Instead of defining the facies stratigraphically, we need to define them either diagenetically (tight limestone, stratified limestone and nonporous chert, and highly porous tripolitic chert) or structurally (fractured versus unfractured chert and limestone). Using a 3D seismic survey acquired in Osage County Oklahoma, we use Kohonen self-organizing maps to classify different diagenetically altered facies of the Mississippi Lime play. The 256 prototype vectors (potential clusters) reduce to only three or four distinct “natural” clusters. We use ground truth of seismic facies seen on horizontal image logs to fix three average attribute data vectors near the well locations, resulting in three “known” facies, and do a minimum Euclidean distance supervised classification. The predicted clusters correlate well to the poststack impedance inversion result.

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