Seismic pattern recognition using neural network and tree automaton

We combine neural network and syntactic pattern recognition, and propose a tree automaton system for the recognition of structural seismic patterns in a seismogram. Multilayer perceptron of the neural network is used for the identification of subpatterns, then a tree representation of the structural seismic pattern is constructed. We use three kinds of modified bottom-up structure preserved error correcting tree automata to recognize the tree representation of syntactic pattern, and propose a new top-down error correcting tree automaton to recognize nonstructural preserved seismic pattern. In the experiments, the system is applied to the simulated and the real seismic bright spot patterns. The recognition result can improve seismic interpretation