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Crustal Structure From Waveform Inverstion of Shear-Coupled PL

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Conference paper

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One strategy for discriminating between explosions and natural events depends on accurate determinations of event locations, including focal depths. If a seismic event could be reliably determined to have a focal depth greater than a few kilometers, one could be confident that the event is not an explosion. But to determine focal depths accurately, one must first have a fairly accurate model of the crustal structure in the vicinity of the event. Unfortunately, sufficiently accurate models do not exist for many regions of interest to the nuclear explosion monitoring community. Our previous work focused on developing and evaluating strategies for locating events using a single three-component seismic station velocity models were obtained via crustal receiver function modeling, and waveform correlation methods were used to determine focal depths for which synthetics fit the data best. However, for an event at a regional distance from a given station, the sampling provided by the teleseismic phases used for receiver functions is not ideal. These waves tend to approach the station at a steep angle, sampling just a narrow cone beneath the station. Better sampling is provided by shear-coupled PL SPL phases, which sample the crust over 1000 km or more as they approach the station. This sampling provides a better lateral average of the crust and more closely resembles the sampling of phases emanating from seismic events at regional distances. Our current research centers on modeling SPL phases using a novel modeling algorithm that uses the reflectivity method to compute synthetic seismograms while holding deeper portions of the mantle fixed, in terms of pre-computed and stored reflectivity and transmission matrices. Layers of the crust and upper mantle are allowed to vary over broad ranges and the entire algorithm is powered by a variant of simulated annealing, a global optimization method.

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  • Seismology
  • Seismic Detection and Detectors

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