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首页> 外文期刊>Izvestiya. Physics of the solid earth >Neural network estimate of seismic velocities and resistivity of rocks from electromagnetic and seismic sounding data
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Neural network estimate of seismic velocities and resistivity of rocks from electromagnetic and seismic sounding data

机译:基于电磁和地震测深数据的神经网络估计地震速度和岩石电阻率

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摘要

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.
机译:提出了根据岩石电阻率对地震P波和S波速度进行神经网络估计的方法,反之亦然,提出了根据地震速度对电阻率的估计方法。结果表明,根据已知数据量与要重建的数据之间的比率,P波和S波速度的估计精度分别在1-4%和4-6%之间。对数电阻率是根据地震P速度和S速度估算的,精确度高达15-17%。在所有情况下,当估计值基于相关数据时,都会获得最大的误差。

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