3-D seismic tracking with probabilistic data association

Abstract

Abstract In this paper, a new approach to the problem of tracking a seismic event through a 3-D data set is presented. The method under consideration was originally developed for tracking targets in a cluttered environment and uses Probabilistic Data Association (PDA) to assess the probability of each return being the correct return. This theory has been modified for use in seismic event tracking, which unlike target tracking, is a static problem, and this new approach has been tested on both real and synthetic 3-D data sets. The tracker successfully picks out the chosen horizon in both the synthetic and real 3-D data sets. The accuracy of the 3-D tracker may be improved by tracking through the data set in two perpendicular directions and correlating the results. Results show that it is also possible to include a diagonal track in the correlation.