Neural network estimate of seismic velocities and resistivity of rocks from electromagnetic and seismic sounding data

Abstract

The neural network estimates of seismic P- and S-wave velocities from electrical resistivity of the rocks and, vice versa, resistivity estimates from seismic velocities are presented. It is shown that, depending on the ratio between the volumes of the known data and the data to be reconstructed, the accuracy of the estimates of the P- and S-wave velocities ranges within 1–4 and 4–6%, respectively. The logarithmic resistivity is estimated from seismic P- and S-velocities as accurately as up to 15–17%. In all cases, the biggest errors are obtained when the estimates are based on correlated data.