Application of neural networks modeling for interpretation of acoustic logging traces
© M.A. Lasarenko, O.A. Gerasimenko, 2015
The neural networks are proposed for application as a method for automatic P and S waves onset time-picking on sonic logging.
The neural network models of acoustic emission preceding phase onset are trained and used to discriminate noise and desired
signal, the last one being packets of longitudinal and transversal waves. The given algorithm is easily adapted to existing systems
and is able to provide both processing of logging tracks in online regime and high productivity of archive materials interpretation.
Key words: neural network modeling, acoustic logging, wave arrival time, adaptive threshold level, longitudinal and transversal waves.