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: NSF, Department of Energy
• Format: Article in Journal/Newspaper
• Language: English
• Published: Oxford University Press (OUP) 2023
• Subjects: Arctic; Arctic Ocean; Laplace; Iceland
• Online Access: http://dx.doi.org/10.1093/gji/ggad363; https://academic.oup.com/gji/advance-article-pdf/doi/10.1093/gji/ggad363/51724014/ggad363.pdf; https://academic.oup.com/gji/article-pdf/235/3/2305/53347684/ggad363.pdf

SUMMARY 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 data set. 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 data set consisting of 786 earthquakes recorded by 9846 stations. Synthetic inversion tests show that we achieve good convergence based on this data set, 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.