The optimal attributes change depending on the target so the workflow can be quite laborious. The traditional workflow usually involves inputting seismic attributes generated from the poststack seismic data and requires human input and expertise in their generation and selection. Neural networks have been used for some time in geophysics to quantitatively predict elastic and rock properties from the seismic and well data.
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