Singularity exponent from wavelet-based multiscale analysis:A new seismic attribute
LI Chun-Feng~1, Christopher Liner~21 State Laboratory of Marine Geology, Tongji University, Shanghai 200092, China2 Department of Geosciences, University of Tulsa, Tulsa, OK 74104-3189, USA
Seismic interpretation is traditionally based on reflection or amplitude. However, amplitude can also disguise the true nature of subsurface geology and blur stratigraphy boundaries. In many cases important information is carried by singularities that are not necessarily associated to a certain amplitude pattern. We present the Hlder exponent (α) as a new seismic attribute which captures locations and strengths of irregularities in data. The Hlder exponent (α) is a measure of singularity strength defined at or around a point. Higher α indicates a higher degree of regularity. We demonstrate that α is a natural attribute for delineating stratigraphy boundaries due to its excellent ability in detecting detailed geologic features from seismic data. We test our concept and wavelet-based multiscale analyzing algorithm on both synthetic and seismic data, and show that α improves our ability in the delineation of stratigraphy layers that would be otherwise vague in the original amplitude display. α has the potential to bring a major breakthrough in seismic data interpretation.