Algorithms and Julia software for FWI with multiple constraints
| Title | Algorithms and Julia software for FWI with multiple constraints |
| Publication Type | Presentation |
| Year of Publication | 2017 |
| Authors | Bas Peters, Felix J. Herrmann |
| Keywords | Presentation, SINBAD, SINBADFALL2017, SLIM |
| Abstract | We present a framework to add multiple convex and non-convex constraints to nonlinear inverse problems, specifically FWI. The constraints mitigate problems related to noisy data, artifacts arising from working with very few simultaneous sources, inaccurate starting models and using approximate physical forward models. Compared to earlier work at SLIM, the current framework is algorithmically simpler and computationally more efficient. We show examples where the model estimation is improved when we use very limited prior knowledge directly as constraints. We also present the software implementation in Julia and how it is used together with other software that compute data-misfit values and gradients w.r.t. the model parameters. |
| URL | https://slim.gatech.edu/Publications/Public/Conferences/SINBAD/2017/Fall/peters2017SINBADFaaj/peters2017SINBADFaaj.pdf |
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| Citation Key | peters2017SINBADFaaj |