AD-GRT Deep Learning Waveform Inversion

This paper proposes a novel deep learning-based waveform inversion method that enables rapid and high-precision extraction of nonlinear waveform information from seismic data. To address critical challenges in existing deep learning full waveform inversion (FWI), such as poor network generalization and huge computational cost, we introduce angle-domain generalized Radon transform (AD-GRT). As intermediate data, AD-GRT generated angle-domain gathers are equivalent to the original seismic data. In