Much of seismic interpretation is based on pattern recognition, such that experienced interpreters are able to extract subtle geologic features that a new interpreter may easily overlook. Seismic pattern recognition is based on the identification of changes in (1) amplitude, (2) phase, (3) frequency, (4) dip, (5) continuity, and (6) reflector configuration. Seismic attributes, which providing quantitative measures that can be subsequently used in risk analysis and data mining, partially automate the pattern recognition problem by extracting key statistical, geometric, or kinematic components of the 3D seismic volume. Early attribute analysis began with recognition of bright spots and quickly moved into the mapping of folds, faults, and channels. Although a novice interpreter may quickly recognize faults and channels on attribute time slices, karst terrains provide more complex patterns. We sought to instruct the attribute expression of a karst terrain in the western part of the Fort Worth Basin, Texas, United States of America. Karst provides a specific expression on almost every attribute. Specifically, karst in the Fort Worth Basin Ellenburger Group exhibits strong dip, negative curvature, low coherence, and a shift to lower frequencies. Geomorphologically, the inferred karst geometries seen in our study areas indicate strong structural control, whereby large-scale karst collapse is associated with faults and where karst lineaments are aligned perpendicularly to faults associated with reflector rotation anomalies.
- Received December 1, 2013.
- Revision received May 8, 2014.
- Accepted May 30, 2014.