3:30 PM - 3:50 PM
[STT50-01] Detecting seismic first arrivals using deep Convolution Neural Networks
Keywords:Detecting seismic first arrivals, Deep learning, Seismic reflection analysis
Our new approach is based on the data transfer through deep Convolution Neural Networks (CNNs). We optimize CNNs model to calculate first arrivals time from seismic data. Manually picked data, few percent of all data, are used as the supervised data during model training.
Compared with previous methods, our method has advantages as follows; (1) robustness against random and impulsive noise, (2) high computationally speed after model trained, (3) broad applicability to picking other signals such as the onset of the S wave. Therefore, our proposed method is suitable for detecting natural earthquakes from existing seismographic network as well as for seismic reflection processing. We present the result of our method applied for the seismic reflection data in land.