Abstract
The density-based spatial clustering application with noise (DBSCAN) along with the super-virtual refraction interferometry (SVI) are used to pick the first arrivals’ traveltimes. DBSCAN alone suffers if the signal-to-noise ratio (SNR) of the data is poor. To overcome this drawback, SVI is used to enhance the SNR, and then DBSCAN is re-applied. We first use DBSCAN to define an initial muting window for the SVI, then, SVI is used to enhance the SNR of the first arrivals, and finally, we re- apply DBSCAN to pick the final first arrivals’ traveltimes. We showed the result using a synthetic example.
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