In more recent work (Hampson et al, 2000), neural networks were used to predict log properties from the complete 3D seismic volume, using each log sample over the zone of interest in the training phase. They applied the RBFN to averaged intervals from log data and the corresponding averaged intervals from the 3D seismic data volumes which were tied by these logs. The use of the radial basis function neural network (RBFN) for the seismic-guided estimation of log properties was first discussed by Ronen et al.
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