Method for the automated editing of seismic traces using an adaptive

Abstract

An adaptive, or neural, network and a method of operating the same is disclosed which is particularly adapted for performing seismic trace editing for seismic shot records. The adaptive network is first trained according to the generalized delta rule. The disclosed training method includes backpropagation is performed according to the worst case error trace, including adjustment of the learning and momentum factors to increase as the worst case error decreases. Slow convergence regions are detected, and methods applied to escape such regions including restoration of previously trimmed dormant links, renormalization of the weighting factor values, and the addition of new network layers with links between nodes that skip the hidden layer. After the training of the network, data corresponding to a Discrete Fast Fourier Transform of each trace, and to certain other attributes of the trace and adjacent traces thereto, are presented to the network. The network classifies the trace as good or noisy according to the inputs thereto, and to the weighting factors therewithin, such classification useful for ignoring noisy traces in subsequent data analysis. The analysis may be repeated for all of the traces in the shot record, and in multiple shot records.