Abstract
Many methods for automatic seismic event picking have been proposed over the years. All fully automatic methods lackrobustness. Given that present-day machines can at best mimichuman picking procedures, it is hardly surprising that they will failwhen things get tough. Attenuation, sensor coupling variations, random scattering in the overburden and the competition ofmultiple arrivals for a given time slot all complicate the task ofdesigning a robust picking machine. In this paper, we set out thearchitecture of a semi-automatic seismic event recognition system, in which robustness is achieved by allowing an observer to train themachine interactively both to accomplish a given event recognitiontask and to cope with variations in the nature of that task. Theevent-recognition task itself is accomplished by moving fromconventional envelope threshold detection to phase sensitivewindowed cross-correlation. The art of enhancing the precision oftime picking lies in supervising the transition between the two asrising signal-to-noise levels permit. The scheme has been used ona standard PC to extract arrival times from full waveform soniclogs, reflection and tomographic in-mine borehole radar surveys, and 3D seismic reflection surveys for coal mining.
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