Source-encoded waveform inversion in the Northern Hemisphere

• Published in: Geophysical Journal International
• Main Authors: Cui, Congyue, Bachmann, Etienne, Peter, Daniel, Liu, Zhaolun, Tromp, Jeroen
• Other Authors: Earth Science, and Engineering, King Abdullah University of Science and Technology , Saudi Arabia, Physical Science and Engineering (PSE) Division, Earth Science and Engineering Program, Extreme Computing Research Center, Department of Geosciences, Princeton University , USA, Program in Applied & Computational Mathematics, Princeton University , USA
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Oxford University Press (OUP) 2023
• Subjects: Arctic; Arctic Ocean; Laplace; Iceland
• Online Access: http://hdl.handle.net/10754/694682; https://doi.org/10.1093/gji/ggad363

We use source-encoded waveform inversion to image Earth’s Northern Hemisphere. The encoding method is based on measurements of Laplace coefficients of stationary wavefields. By assigning to each event a unique frequency, we compute Fréchet derivatives for all events simultaneously based on one ‘super’ forward and one ‘super’ adjoint simulation for a small fraction of the computational cost of classical waveform inversion with the same dataset. No cross-talk noise is introduced in the process, and the method does not require all events to be recorded by all stations. Starting from global model GLAD_M25, we performed 100 conjugate gradient iterations using a dataset consisting of 786 earthquakes recorded by 9,846 stations. Synthetic inversion tests show that we achieve good convergence based on this dataset, and we see a consistent misfit reduction during the inversion. The new model, named SE100, has much higher spatial resolution than GLAD_M25, revealing details of the Yellowstone and Iceland hotspots, subduction beneath the Western United States, and the upper mantle structure beneath the Arctic Ocean. The comments of Kai Wang and two anonymous reviewers helped to improve an earlier version of the manuscript. We thank Frederik J. Simons for helpful suggestions and discussions, and Stephen Beller for implementing a Laplacian smoother in SPECFEM3D GLOBE. Parallel programs were run on computers provided by the Princeton Institute for Computational Science and Engineering (PICSciE). This research was partially supported by NSF grant 2244661 and used resources from the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. Figures 14 and 15 were plotted with SphGLLTools (Ciardelli et al. 2022) using ETOPO 2022 (NOAA National Centers for Environmental Information 2022) as a background image. Observed seismograms in this study were downloaded from IRIS (iris.edu) and ORFEUS ...