Toward the Systematic Counting of Small Volcanic Seismic Events

One of the primary challenges facing modern volcano observatories is mining small signals from massive data streams in a consistent fashion (particularly seismic.) One such parameter is the number of earthquakes detected by a single seismic station - so called helicorder counts because they were traditionally performed by eye using paper helicorder records. While this measure is simplistic compared to reviewed located events, it has the advantage of being straight forward to implement and robust to network changes. At several volcanoes in the Aleutian arc, helicorder counts provide one of the few consistent multi-decade monitoring tools. As part of an NSF-supported REU (research experience for undergraduates) summer internship, we have developed an automated and expanded approach to helicorder counts with the goal of replacing and systematizing the current process. The challenge is to efficiently weed out non-volcanic signals which are easy recognized by eye (communications noise, calibration pulses, telelseismic and regional earthquakes). To do this, we use a simple event detector and several filtered data representations to measure basic parameters of each detected event including the duration, the dominant frequency, the maximum amplitude, and the impulsiveness of the first arrival. These parameters can then be used to identify and discard typical non-volcanic sources including communications noise, regional earthquakes and calibration pulses. We demonstrate the technique on several types of recent volcanic behavior observed at the Alaska Volcano Observatory.