Simultaneous-shot inversion for PDE-constrained optimization problems with missing data
Title | Simultaneous-shot inversion for PDE-constrained optimization problems with missing data |
Publication Type | Journal Article |
Year of Publication | 2018 |
Authors | Michelle Liu, Rajiv Kumar, Eldad Haber, Aleksandr Y. Aravkin |
Journal | Inverse Problems |
Volume | 35 |
Pagination | 025003 |
Keywords | Full-waveform inversion, low-rank interpolation, Optimization |
Abstract | Stochastic optimization is key to efficient inversion in PDE-constrained optimization. Using `simultaneous shots', or random superposition of source terms, works very well in simple acquisition geometries where all sources see all receivers, but this rarely occurs in practice. We develop an approach that interpolates data to an ideal acquisition geometry while solving the inverse problem using simultaneous shots. The approach is formulated as a joint inverse problem, combining ideas from low-rank interpolation with full-waveform inversion. Results using synthetic experiments illustrate the flexibility and efficiency of the approach. |
Notes | (Inverse Problems) |
URL | https://slim.gatech.edu/Publications/Public/Journals/InverseProblems/2018/liu2018ssi/liu2018ssi.pdf |
DOI | 10.1088/1361-6420/aaf317 |
Citation Key | liu2018ssi |