Seismic Tomography Beneath the Western United States Using a Joint Body Wave-Surface Wave Inversion Algorithm

Wednesday, 17 December 2014
Eva Marie Golos1, Robert D van der Hilst1, Huajian Yao2, Haijiang Zhang3, Hongjian Fang3 and Scott A Burdick1, (1)Massachusetts Institute of Technology, Cambridge, MA, United States, (2)USTC University of Science and Technology of China, Laboratory of Seismology and Physics of Earth's Interior, Hefei, China, (3)University of Science and Technology of China, Hefei, China
Enormous strides have recently been made in the creation of high-resolution, high-quality models of spatial variations in seismic velocity, due to increased computational capacity and to projects such as USArray Transportable Array network that provide high-density passive seismic data. Such tomography models are essential for our understanding of the local and regional geology, for determining tectonic and geologic histories, and for constraining other geophysical investigations.

Many previous investigations have utilized USArray data, and the general seismic velocity structure of the mantle beneath the United States is complicated but now well-established (e.g. Roth et al., 2008; Burdick et al., 2013), making it an ideal region for testing new methods. The eastern and central parts are seismically quiet and generally exhibit uniformly fast seismic propagation speeds, while the western portion of the country is tectonically active with a more complicated and depth-varying seismic signature.

We determine seismic velocities in the mantle beneath the western United States using a new joint inversion algorithm (Zhang et al., 2014). Traditional tomography methods such as surface wave dispersion or body wave travel-time tomography are often regarded as very disparate approaches, each subject to limitations due to inherent properties of the data used. Rather than considering surface and body wave phases separately, we solve both problems simultaneously in a single inversion. The new algorithm implements a direct inversion of surface dispersion data (Fang et al., 2014), which can be incorporated into the body wave travel-time inversion. Furthermore, the velocity models are solved in the wavelet domain, which addresses the perpetual challenge of uneven raypath coverage by taking advantage of the multiscale properties of wavelet representations (Fang and Zhang, 2014). The preliminary results presented here use both body wave arrival times (from the EHB and ISC bulletins, as well as the USArray dataset) and surface wave dispersion measurements (from Ekstrom et al., 2013) to determine the S and P wave velocity structure of the mantle beneath the western US at various depths.