Geological Engineering Commons^™

Classification Of Teleseismic Shear Wave Splitting Measurements: A Convolutional Neural Network Approach, Yanwei Zhang, Stephen S. Gao

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Shear wave splitting (SWS) analysis is widely used to provide critical constraints on crustal and mantle structure and dynamic models. In order to obtain reliable splitting measurements, an essential step is to visually verify all the measurements to reject problematic measurements, a task that is increasingly time consuming due to the exponential increase in the amount of data. In this study, we utilized a convolutional neural network (CNN) based method to automatically select reliable SWS measurements. The CNN was trained by human-verified teleseismic SWS measurements and tested using synthetic SWS measurements. Application of the trained CNN to broadband seismic data …