For nuclear explosion seismic monitoring, major aftershock sequences can be a significant problem because each event must be analyzed. Fortunately, the high degree of waveform similarity expected within aftershock sequences offers a way to more quickly and robustly process these events than is possible using traditional methods (e.g., short‐term average/long‐term average detection).
We explore how waveform correlation can be incorporated into an automated event detection system to improve both the timeliness and the quality of the resultant bulletin. With our Waveform Correlation Detector we processed three aftershock sequences: the 1994 Northridge earthquake, the 2005 Kashmir earthquake, and the 2008 Wenchuan earthquake. Our system compared incoming waveform data to a library of known master events and identified incoming waveform data that correlated well with a master event as a repeating event. We break down our results to show how many master events found matches, the distribution in family size, and the effect of distance and fault characteristics on the results. Between 24% and 92% of the events in each sequence were recognized as similar events.