[17] Runhai Feng, Niels Balling, and Dario Grana. Lithofacies classification of a geothermal reservoir in denmark and its facies-dependent porosity estimation from seismic inversion. Geothermics, 87:101854, 2020.
[18] Hui Li, Jing Lin, Baohai Wu, Jinghuai Gao, and Naihao Liu. Elastic properties estimation from prestack seismic data using ggcnns and application on tight sandstone reservoir characterization. IEEE Transactions on Geoscience and Remote Sensing, 60:1-21, 2021.
[19] Eugenia Rojas, Thomas L. Davis, Michael Batzle, Manika Prasad, and Reinaldo J. Michelena.  $\mathrm{V_p - V_s}$  ratio sensitivity to pressure, fluid, and lithology changes in tight gas sandstones. In SEG Technical Program Expanded Abstracts 2005, pages 1401-1404, 2005.
[20] Pinbo Ding, Ding Wang, Guidong Di, and Xiangyang Li. Investigation of the effects of fracture orientation and saturation on the vp/vs ratio and their implications. Rock Mechanics and Rock Engineering, 52:3293-3304, 2019.
[21] J. Sun, X. Wei, and X. Chen. Fluid identification in tight sandstone reservoirs based on a new rock physics model. Journal of Geophysics and Engineering, 13(4):526-535, 07 2016.
[22] WA Mulder and R-E Plessix. Exploring some issues in acoustic full waveform inversion. Geophysical Prospecting, 56(6):827-841, 2008.
[23] Stéphane Operto, Yaser Gholami, Vincent Prieux, Alessandra Ribodetti, R Brossier, L Metivier, and Jean Virieux. A guided tour of multiparameter full-waveform inversion with multicomponent data: From theory to practice. The leading edge, 32(9):1040-1054, 2013.
[24] Zhen-dong Zhang and Tariq Alkhalifah. High-resolution reservoir characterization using deep learning-aided elastic full-waveform inversion: The north sea field data examplemlefwi. Geophysics, 85(4):WA137-WA146, 2020.
[25] Arnab Dhara and Mrinal Sen. Elastic-adjointnet: A physics-guided deep autoencoder to overcome crosstalk effects in multiparameter full-waveform inversion. In SEG/AAPG International Meeting for Applied Geoscience & Energy. OnePetro, 2022.
[26] Yulang Wu, George A McMechan, and Yanfei Wang. Cnn-based gradient-free multiparameter reflection full-waveform inversion. In First International Meeting for Applied Geoscience & Energy, pages 1369-1373. Society of Exploration Geophysicists, 2021.
[27] Linan Xu, Zhaoqi Gao, Sichao Hu, Jinghuai Gao, and Zongben Xu. Simultaneous inversion for reflectivity and q using nonstationary seismic data with deep-learning-based decoupling. IEEE Transactions on Geoscience and Remote Sensing, 60:1-15, 2022.
[28] Tianze Zhang, Kristopher A Innanen, Jian Sun, and Daniel O Trad. Numerical analysis of a deep learning formulation of multi-parameter elastic full waveform inversion. In SEG International Exposition and Annual Meeting. OnePetro, 2020.
[29] Jiashun Yao, Michael Warner, and Yanghua Wang. Regularization of anisotropic full-waveform inversion with multiple parameters by adversarial neural networks. Geophysics, 88(1):R95–R103, 2023.
[30] Chengyuan Deng, Shihang Feng, Hanchen Wang, Xitong Zhang, Peng Jin, Yinan Feng, Qili Zeng, Yinpeng Chen, and Youzuo Lin. Openfwi: Large-scale multi-structural benchmark datasets for full waveform inversion. Advances in Neural Information Processing Systems, 35:6007–6020, 2022.
[31] Yue Wu and Youzuo Lin. InversionNet: An efficient and accurate data-driven full waveform inversion. IEEE Transactions on Computational Imaging, 6:419-433, 2019.
[32] Zhongping Zhang and Youzuo Lin. Data-driven seismic waveform inversion: A study on the robustness and generalization. IEEE Transactions on Geoscience and Remote sensing, 58(10):6900-6913, 2020.
[33] Yinan Feng, Yinpeng Chen, Peng Jin, Shihang Feng, Zicheng Liu, and Youzuo Lin. Simplifying full waveform inversion via domain-independent self-supervised learning. arXiv preprint arXiv:2305.13314, 2023.