Seismic waveform inversion best practices: regional, global and exploration test cases. Issue 3 (17th June 2016)

• Record Type: Journal Article
• Authors: Modrak, Ryan; Tromp, Jeroen
• Is Part Of: Geophysical journal international. Volume 206:Issue 3(2016:Sep.)
• Page Start: 1864
• Page End: 1889
• Publication Date: 2016-06-17
• Subjects: Inverse theory -- Numerical approximations and analysis -- Computational seismology; Geophysics -- Periodicals; 550
• DOI: 10.1093/gji/ggw202
• Languages: English
• ISSNs: 0956-540X

Abstract

Abstract: Reaching 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.