Full waveform inversion (FWI) is one of the most challenging procedures to obtain quantitative information of the subsurface. For elastic inversions, when both compressional and shear velocities have to be inverted, the algorithmic issue becomes also a computational challenge due to the high cost related to modelling elastic rather than acoustic waves. This shortcoming has been moderately mitigated by using high-performance computing to accelerate 3D elastic FWI kernels. Nevertheless, there is room in the FWI workflows for obtaining large speedups at the cost of proper grid pre-processing and data decimation techniques. In the present work, we show how by making full use of frequency-adapted grids, composite shot lists and a novel dynamic offset control strategy, we can reduce by several orders of magnitude the compute time while improving the convergence of the method in the studied cases, regardless of the forward and adjoint compute kernels used.

The authors thank REPSOL for the permission to publish the present research and for funding through the AURORA project. J. Kormann also thankfully acknowledges the computer resources, technical expertise and assistance provided by the Barcelona Supercomputing Center - Centro Nacional de Supercomputacti ´on together with the Spanish Supercomputing Network (RES) through grant FI-2014-2-0009. This project has received funding from the European Union’s Horizon 2020, research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 644202. The research leading to these results has received funding from the European Union’s Horizon 2020 Programme (2014–2020) and from the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP) under the HPC4E Project (www.hpc4e.eu), grant agreement no. 689772.We further want to thank the Editor Clint N. Dawson for his help, and Andreas Fichtner and an anonymous reviewer for their comments and suggestions to improve the manuscript.

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