CMG Research: Experiments Aimed at Improving Global Seismic Tomography

Arizona State University, Scottsdale AZ

Investigators

Abstract

0222327 Garnero The purpose of this proposed research is to employ two methods from the field of applied mathematics to seismic tomography; each is focused on the goal of improved imaging of spatial data. This work is a collaborative effort between geophysicist Ed Garnero and two applied mathematicians, Anne Gelb and Rosie Renaut. This effort will train two graduate students in a cross-disciplinary approach between the fields of applied math and seismology. While 3D images of Earth's mantle have come in clearer focus over the last 25 years, many challenges remain, most notably because of incomplete data coverage. Inversions of seismic data require smoothing and damping that effectively blurs resulting images. The investigators are motivated to better resolve the gradients and shapes of seismic velocity heterogeneity since they relate to temperature and/or compositional changes in Earth's interior. The project will employ the following two methods. (1) Data reprocessing and inversion methods: deconvolution methods will be used to intelligently preprocess differential travel time computations. Inversion may also be improved by regularization through a total variation type penalty term. (2) Image reconstruction methods: apply the Gegenbauer reconstruction method for high resolution post-processing reconstruction, which has proven effective for removing Gibbs oscillations without compromising the finer image features even near jump discontinuities in other applications, such as magnetic resonance imaging. The tasks can be summarized as follows. (1) Pre-inversion processing: travel time series cleanup evaluated for blind and knowledge-based deconvolution, approximated from structural models of the Earth's interior. (2) Inversion experiments: determine effectiveness of a total variation regularization model, particularly in conjunction with the impact on post-inversion processing. (3) Post-inversion processing: sharpen images through removal of artifacts with the Gegenbauer reconstruction method. (4) Assess solution images with data: data from geographical regions with best data coverage will be analyzed and modeled to test solution structures.