Abstract：In view of the issue of seismic data inversion in depth domain,the paper presented the method for inversion of lithologic parameters driven by neural network.The inversion method is non-linear and is driven by data as well as don’t need any determinate operator,among which the data-driven scheme is finished by structural-risk-minimized neural network.During the operation of inversion,the logging data and seismic data are usually taken as training samples,among which the seismic data in uphole receiver are taken as input and logging data as output,the inversion mapping relation transformed from seismic data to logging data is obtained when network learning is finished and the gained data are used for lithologic interpretation.The paper showed the effectiveness of the method by theoretic models and inversion cases of lithologic parameters of seismic prestack depth migration data.
