Extending SALSA3D: Adding Secondary Phases to a Global 3D P-Velocity Model for Improved Seismic Event Location
Abstract:The SALSA3D (SAndia LoS Alamos 3D) global three-dimensional P-velocity tomography model of the Earth’s crust and mantle has been shown to significantly improve seismic event location accuracy and precision, compared to standard 1D and 2/2.5D models. This improvement has been demonstrated using data from the International Monitoring System (IMS), a sparse, global seismic network. In relocation tests using the IMS network and a set of seismic events with ground truth (GT) levels of 5 km or better, over 80% of the defining arrivals are regional Pn (15%) or teleseismic P phases (65.1%). There is a small percentage of phases that requires a model that supports secondary phase prediction. We plan to update the SALSA3D model to include an S-velocity component as well as an updated P-velocity model using secondary compressional phases.
Our model is derived from the latest version of the GT catalog of travel-time picks assembled by Los Alamos National Laboratory. The model is represented using the triangular tessellation system described by Ballard et al. (2009), which incorporates variable resolution in both the geographic and radial dimensions. For our starting model, we use a simplified layer crustal model derived from the Crust 1.0 model, overlying a uniform ak135 mantle. Sufficient damping is used to reduce velocity adjustments so that ray path changes between iterations are small. We obtain proper model smoothness by using progressive grid refinement, refining the grid only in areas where it is warranted by the available data. Our approach produces a smooth, multi-resolution model with node density appropriate to both ray coverage and the velocity gradients required by the data.
We compare the travel-time prediction and location capabilities of the updated SALSA3D model to standard 1D and 2/2.5D models via location tests on a global event set with GT of 5 km or better. We compare location results using a subset of these events that have a significant number of phases with which to produce random realizations of actual arrival data. In addition, further tests will involve using GT5 or better events and their arrivals specifically for the IMS network, to test the use of a 3D model on an operational network intended for explosion monitoring.