Affiliation:
1. King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia.(corresponding author);
2. Formerly KAUST; presently at the University of Calgary, Alberta, Canada..
Abstract
Accurate identification and picking of P- and S-wave arrivals is important in earthquake and exploration seismology. Often, existing algorithms are lacking in automation, multiphase classification and picking, as well as performance accuracy. We have developed a new fully automated four-step workflow for efficient classification and picking of P- and S-wave arrival times on microseismic data sets. First, time intervals with possible arrivals on waveform recordings are identified using the fuzzy c-means clustering algorithm. Second, these intervals are classified as corresponding to P-, S-, or unidentified waves using the polarization attributes of the waveforms contained within. Third, the P-, S-, and unidentified-waves arrival times are picked using the Akaike information criterion picker on the corresponding intervals. Fourth, unidentified waves are classified as P or S based on the arrivals moveouts. The application of the workflow on synthetic and real microseismic data sets indicates that it yields accurate arrival picks for high and low signal-to-noise ratio waveforms.
Funder
King Abdullah University of Science and Technology
Publisher
Society of Exploration Geophysicists
Subject
Geochemistry and Petrology,Geophysics
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