Similar Event Catalog

The increased microseismicity rates resulting from the San Simeon M6.5 and Parkfield M6 events and the increased interest in even smaller events in the SAFOD target zone have required new thinking on how to detect and catalog microearthquakes recorded by the HRSN. One action taken to help address this problem has been to integrate HRSN data streams into the NCSN event detection and automated cataloging process (described below). This approach has been successful at discriminating small events in the local Parkfield area from other types of event detections and for providing automated locations of a significantly increased number of small events in the local area (approx. double that of the NCSN network alone). However, the rate of local events from the HRSN sensitized NCSN catalog is still only catching about 1/2 the number of local events previously cataloged by the HRSN, and waveforms for the small events are not typically made available. In addition, unlike the previous HRSN catalog, the additional events added by the NCSN-HRSN integration are not reviewed by an analyst, nor do they generally have magnitude determinations associated with them. In some cases, the selection rules used for the integrated catalog also result in exclusion of events that are otherwise included by the NCSN.

These limitations severely hamper efforts relying on similar and characteristically repeating microearthquakes. They also reduce the effectiveness of research relying on numerous very small magnitude events in the SAFOD zone (e.g. for targeting the SAFOD targets). To help overcome these limitations, we have continued our efforts to develop an automated similar event cataloging scheme based on cross-correlation and pattern scanning of the continuous HRSN data now being archived. The method uses a small number of reference events whose waveforms, picks, locations, and magnitudes have been accurately determined, and it automatically detects, picks, locates and determines magnitudes for events similar to the reference event to the level of accuracy and precision that only relative event analysis can bring.

The similar event detection is also remarkably insensitive to the magnitude of the reference event used, allowing similar events ranging over several magnitude units to be fully cataloged using a single reference event. It also does a remarkably good job even when seismic energy from multiple events is superposed. Once a cluster of similar events has been cataloged, it is a relatively straightforward process to identify characteristically repeating microearthquake sequences within the cluster (frequently a single similar event "cluster" will contain several sequences of repeating events).

Application of the method using two of the SAFOD target events as references is illustrated in Figure 3.14. One reference event is a member of the so-called Hawaii sequence (HI), and one is from the San Francisco sequence (SF), and their magnitudes are $\sim$ 2.1 and 1.8 (respectively). These events were scanned through 5 years of continuous data, and 110 other events occurring within the target region were identified and fully cataloged to high precision. Their magnitudes ranged down to magnitude -1.4 Ml, and in addition to the SAFOD target sequence from which the reference was derived, several other repeating sequences within the 150m zone were also identified (5 of which had not previously been known to exist).

This high level of precision and low magnitude completeness has already proven useful to SAFOD for helping to delineate and constrain the active fault structure in the target zone. It has also proven vital for helping to resolve a long-standing debate in the seismologic community regarding the stress-drop scaling issues (Dreger et al., 2007).

The automated cataloging procedure for similar events is still being refined to capture even smaller events and events over a larger area, as well as for increased processing speed. Eventually, a composite catalog of similar event groups from throughout the HRSN coverage zone is planned.

The approach also holds promise in other applications where automated and precise monitoring of bursts of seismic activity to very low magnitudes is desirable (e.g. in aftershock zones or in volcanic regions) or where automated updates of preexisting repeating sequences and their associated deep slip estimates are desired.