@inproceedings{scholars15541,
             doi = {10.1007/978-981-16-4513-6{$_6$}{$_1$}},
            year = {2021},
            note = {cited By 0; Conference of 6th International Conference on Fundamental and Applied Sciences, ICFAS 2020 ; Conference Date: 13 July 2021 Through 15 July 2021; Conference Code:270909},
           pages = {705--713},
           title = {Gauss-Newton and L-BFGS Methods in{\^A} Full Waveform Inversion (FWI)},
       publisher = {Springer Science and Business Media B.V.},
         journal = {Springer Proceedings in Complexity},
            isbn = {9789811645129},
          author = {Abdul Karim, S. A. and Iqbal, M. and Shafie, A. and Izzatullah, M.},
            issn = {22138684},
        abstract = {Full waveform inversion (FWI) is{\^A} a recent{\^A} powerful method in the area of seismic imaging where it used for reconstructing high-resolution images of the subsurface structure from local measurements of the seismic wavefield. This method consists in minimizing the distance between the predicted and the recorded data. The predicted data are computed as the solution of a wave-propagation problem. In this study, we investigate two algorithms Gauss-Newton{\^A} and L-BFGS{\^A} for solving FWI problems. We compare these algorithms in terms of its robustness and speed of convergence. Also, we implement the Tikhonov regularization{\^A} for assisting convergence. Numerical results show that Gauss-Newton{\^A} method performs better than L-BFGS{\^A} method in terms of convergence of l2 -norm of misfit function gradient since it provides better convergence as well as the quality of high resolution constructed images. Yet, L-BFGS{\^A} outperforms Gauss-Newton{\^A} in terms of computationally efficiency and feasibility for FWI. {\^A}{\copyright} 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123298219&doi=10.1007\%2f978-981-16-4513-6\%5f61&partnerID=40&md5=2b67ce462505cc03ba5141411c6ceeff}
}