ADAPTING PIPELINE ARCHITECTURES TO TRACK DEVELOPING AFTERSHOCK SEQUENCES AND RECURRENT EXPLOSIONS

Pattern detectors (e.g., correlation, subspace, and matched field detectors) fuse the signal detection and source identification processes into a single operation. The organization of repeating waveforms for efficient analyst interpretation may result in significant gains in productivity when analyzing extensive aftershock sequences and explosions from repeating sources. Under current practice, pattern detectors run entirely independently of the pipeline signal detectors and the preparation and supervision of pattern detectors is relatively labor-intensive. It is the aim of this two-year study to investigate algorithms for adapting processing pipelines to create and supervise pattern detectors semi-automatically for incoming multi-channel data streams. A functional model of an operational detection pipeline is being constructed with extensions that create and manage pattern detectors under a variety of spawning policies. The system is being tested on two aftershock sequences: that for the 8 October 2005, M=7.6, Kashmir earthquake and that for the 23 October 2011, M=7.1, Eastern Turkey event. Both cases are representative of challenging aftershock sequences given the vast numbers of events and relatively large source regions. Pattern detectors that are coherent over multiple arrays and 3-component stations can constitute exquisitely sensitive detectors that increase the detection capability greatly for events in the immediate geographical vicinity of the master events. An alternative strategy would be to operate pattern detectors coherently over single arrays or other limited subsets of sensors, and combine the results incoherently across the complete network. This alternative strategy may allow a greater geographical region to be covered by given templates. The merits and limitations of the two strategies are being investigated for a range of different case studies. For correlation detectors on single arrays the validity of detections can be assessed by performing f-k analysis on single-channel detection statistic traces, eliminating enormous numbers of false alarms and allowing a significant reduction in the detection threshold. Policies for triggering and spawning of correlation detectors are being studied extensively. The simplest trigger is using an STA/LTA detector on an array beam steered towards the slowness of anticipated first P-wave arrival from the source region considered, with the classification of the detected phase being confirmed using classical f-k analysis. This strategy is reinforced significantly when considering multiple observing stations. Considering only detections which are confirmed on multiple stations, with limits on the time-delays determined by the dimensions of the source region, will lead to fewer detectors generated by false triggers. The most promising triggering algorithm considered so far is the single phase empirical matched field detector (EMFD). This narrow frequency band approach mitigates the effects of, and indeed exploits, the scattering which frequently confounds classical array processing. Correlation detectors using a waveform template from the main event are frequently very unsuccessful at detecting large number of aftershocks, since large spectral differences between the main shock and aftershocks may lead to significantly different waveforms. The empirical matched field processing recognizes the characteristic spatial structure of the incoming wavefronts over the array aperture in each of many narrow frequency bands and this appears to be a more stable characteristic of a given source region than the temporal structure of the waveforms on each sensor. For both the Turkey and Kashmir sequences, the EMFD readily detects many very low signal-to-noise ratio (SNR) signals which are all confirmed by stations in the vicinity of the source region to correspond to real events in the sequences.