42 research outputs found
Zenodo Collection: Estimation of best-fitting force, moment tensor, and depth for the 2022 Hunga-Tonga submarine volcanic eruption
No full textThis Zenodo collection contains figures and results from grid searches used to estimate point source parameters (force or moment tensor) for the main seismic subevent of the 2022 Hunga-Tonga submarine volcanic eruption. The collection includes misfit maps and waveform fits for the best-fitting force or moment tensor, as well as MTUQ weight files and a zipped version of the MTUQ code. These results were obtained using various software tools, including MTUQ, Axisem, Instaseis, Syngine, Obspy, GMT, and PyGMT. The collection was prepared for a manuscript in review for Geophysical Journal International.This project was supported by Air Force Research Laboratory contract HQ0034-20-F-0284 funded through the UAF Geophysical Detection of Nuclear Proliferation (GDNP) University Affiliated Research Center (UARC). We thank Ryan Modrak for his contributions and core work on the MTUQ software
SPECFEM/specfem2d: SPECFEM2D v8.0.0
No full textNew in SPECFEM2D 8.0.0:
GPU support
axisymmetric 2.5D simulations
various code improvements
many thanks for all your contributions to this version:
Etienne Bachmann, Alexis Bottero, Bryant Chow, Paul Cristini, Rene Gassmoeller, Michael Gineste, Felix Halpaap, Dimitri Komatitsch, Matthieu Lefebvre, Qiancheng Liu, Qinya Liu, Zhaolun Liu, David Luet, Ryan Modrak, Christina Morency, Daniel Peter, Eric Rosenkrantz, Herurisa Rusmanugroho, Elliott Sales de Andrade, Eduardo Valero Cano, Zhinan Xie, Zhendong Zhan
Reply to “Comment on ‘Multievent Explosive Seismic Source for the 2022 M_w 6.3 Hunga Tonga Submarine Volcanic Eruption’ by Julien Thurin, Carl Tape, and Ryan Modrak” by Fred F. Pollitz, Ricardo Garza‐Giron, and Thorne Lay
No full textEstimation of best-fitting force, moment tensor, and depth for the 2022 Hunga-Tonga submarine volcanic eruption: Misfit plots in model parameter space
No full textSupporting documents for the correction of the publication Multi‐Event Explosive Seismic Source for the 2022 Mw 6.3 Hunga Tonga Submarine Volcanic Eruption, published in The Seismic Record (https://doi.org/10.1785/0320220027).This project was supported by Air Force Research Laboratory contract HQ0034-20-F-0284 funded through the UAF Geophysical Detection of Nuclear Proliferation (GDNP) University Affiliated Research Center (UARC)
SPECFEM/specfem3d: SPECFEM3D v4.0.0
No full textNew in SPECFEM3D 4.0.0:
various code improvements (fault solver, FK/DSM/AxiSEM coupling, gravity perturbations, energy integrals)
inverse problem module
parallel heuristic mesh decomposer
ADIOS2 file I/O support
ASDF seismogram output
HIP GPU support
many thanks for all your contributions to this version:
Rafael Almada, Jean-Paul Ampuero, Etienne Bachmann, Kangchen Bai, Stephen Beller, Jordan Bishop, Alexis Bottero, Emanuele Casarotti, Clement Durochat, Rene Gassmoeller, Hom Nath Gharti, Leopold Grinberg, Aakash Gupta, Foivos Karakostas, Dimitri Komatitsch, Qinya Liu, Geordie McBain, Ryan Modrak, Vadim Monteiller, Masaru Nagaso, Elif Oral, Daniel Peter, Elliott Sales de Andrade, James Smith, Carl Tape, Eduardo Valero Cano, Huihui Weng, Zhinan Xi
Acoustic and Elastic Waveform Inversion Best Practices
No full textReaching the global minimum of a waveform misfit function requires careful choices about the nonlinear optimization, preconditioning and regularization methods underlying an inversion. Because waveform inversion problems are susceptible to erratic convergence, one or two test cases are not enough to reliably inform such decisions. We identify best practices instead using two global, one regional and four near-surface acoustic test problems. To obtain meaningful quantitative comparisons, we carry out hundreds acoustic inversions, varying one aspect of the implementation at a time.
Comparing nonlinear optimization algorithms, we find that L-BFGS provides computational savings over nonlinear conjugate gradient methods in a wide variety of test cases. Comparing preconditioners, we show that a new diagonal scaling derived from the adjoint of the forward operator provides better performance than two conventional preconditioning schemes. Comparing regularization strategies, we find that projection, convolution, Tikhonov regularization, and total variation regularization are effective in different contexts. Besides these issues, reliability and efficiency in waveform inversion depend on close numerical attention and care. Implementation details have a strong effect on computational cost, regardless of the chosen material parameterization or nonlinear optimization algorithm.
Building on the acoustic inversion results, we carry out elastic experiments with four test problems, three objective functions, and four material parameterizations. The choice of parameterization for isotropic elastic media is found to be more complicated than previous studies suggests, with ``wavespeed-like'' parameters performing well with phase-based objective functions and Lam\'{e} parameters performing well with amplitude-based objective functions. Reliability and efficiency can be even harder to achieve in transversely isotropic elastic inversions because rotation angle parameters describing fast-axis direction are difficult to recover. Using Voigt or Chen-Tromp parameters avoids the need to include rotation angles explicitly and provides an effective strategy for anisotropic inversion.
The need for flexible and portable workflow management tools for seismic inversion also poses a major challenge. In a final chapter, the software used to the carry out the above experiments is described and instructions for reproducing experimental results are given
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Seismic waveform inversion best practices: regional, global and exploration test cases
No full textReaching the global minimum of a waveform misfit function requires careful choices about the nonlinear optimization, preconditioning and regularization methods underlying an inversion. Because waveform inversion problems are susceptible to erratic convergence associated with strong nonlinearity, one or two test cases are not enough to reliably inform such decisions. We identify best practices, instead, using four seismic near-surface problems, one regional problem and two global problems. To make meaningful quantitative comparisons between methods, we carry out hundreds of inversions, varying one aspect of the implementation at a time. Comparing nonlinear optimization algorithms, we find that limited-memory BFGS provides computational savings over nonlinear conjugate gradient methods in a wide range of test cases. Comparing preconditioners, we show that a new diagonal scaling derived from the adjoint of the forward operator provides better performance than two conventional preconditioning schemes. Comparing regularization strategies, we find that projection, convolution, Tikhonov regularization and total variation regularization are effective in different contexts. Besides questions of one strategy or another, reliability and efficiency in waveform inversion depend on close numerical attention and care. Implementation details involving the line search and restart conditions have a strong effect on computational cost, regardless of the chosen nonlinear optimization algorithm
