AN EVALUATION OF GENERALIZED LIKELIHOOD RATIO OUTLIER DETECTION TO IDENTIFICATION OF SEISMIC EVENTS IN WESTERN CHINA

The generalized likelihood ratio outlier detection technique for seism ic event identification is evaluated using synthetic test data and fre quency-dependent P-g/L-g measurements from wester China. For most seis mic stations that are to be part of the proposed International Monitor ing System (IMS) for the Comprehensive Test Ban Treaty (CTBT), there w ill be few or no nuclear explosions in the magnitude range of interest (e.g., m(b) < 4) on which to base an event-identification system usin g traditional classification techniques. Outlier detection is a reason able alternative approach to the seismic discrimination problem when n o calibration explosions are available. Distance-corrected P-g/L-g dat a in seven different frequency hands ranging from 0.5 to 8 Hz from the Chinese Digital Seismic Station WMQ are used to evaluate the techniqu e. The data are collected from 157 known earthquakes, 215 unknown even ts (presumed earthquakes and possibly some industrial explosions), and 18 known nuclear explosions (1 from the Chinese Lop Nor test site and 17 from the East Kazakh test site). A feature selection technique is used to find the best combination of discriminants to use for outlier detection. Good discrimination performance is found by combining a low -frequency (0.5 to 1 Hz) P-g/L-g ratio with high-frequency ratios (e.g . 2 to 4 and 4 to 8 Hz). Although the low-frequency ratio does not dis criminate between earthquakes and nuclear explosions well by itself, i t can be effectively combined with the high-frequency discriminants. B ased on the tests with real and synthetic data, the outlier detection technique appears to be an effective approach to seismic monitoring in uncalibrated regions.