Skeletons and fractals - a statistical approach to deep crustal seismic data processing and interpretation

摘要

Coherent seismic reflection events are identified using seismic skeletonization, an automatic pattern recognition technique in which waveforms are parameterized such that the attributes of each event are identified and stored in a relational database, or 'event file'. This new approach to seismic interpretation allows statistical analyses of the attributes including estimation of scaling laws for reflectivity observed on deep seismic data, and development of new filtering techniques based on characteristics such as dip and reflection event length. Applications of the technique to deep crustal reflection data sets from the Alberta Basement Transect of the LITHOPROBE project assist interpretation in areas that lack surface outcrop or other means of relating reflections from the deep crust to the surface. (C) 1998 Elsevier Science B.V. All rights reserved. [References: 13]