“…In recent years, deep learning technology has been developed rapidly and applied in various fields. In contrast to traditional model-driven methods, deep learning is data-driven and has been well applied by geophysicists in various branches including end-to-end seismic data denoising (Herrmann and Hennenfent, 2008;Zhang et al, 2017;Yu et al, 2019;Zhu et al, 2019), missing data recovery and reconstruction (Mandelli et al, 2018;Wang et al, 2019;Wang et al, 2020), first arrival picking (Wu et al, 2019a;Hu et al, 2019;Yuan et al, 2020), deeplearning velocity inversion (Araya-Polo et al, 2018;Adler et al, 2019;Cai et al, 2022), deep-learning seismology inversion (Wang et al, 2022) and fault interpretation (Wu et al, 2019c;Wu et al, 2019d;Cunha et al, 2020;Yang et al, 2022).…”