Large-scale gravity and gravity gradient joint inversion method based on BTTB matrix compression

The utilization of joint inversion techniques with gravity and gravity gradient data yields a more comprehensive and distinctive revelation of the subsurface density structure. However, this approach also poses challenges related to substantial computational requirements, slow convergence, and high memory demands. To tackle these issues, this study employs the Block Toeplitz-Toeplitz Block structured sensitivity matrix compression and a two-dimensional fast Fourier transform for achieving rapid forward modeling of both gravity and gravity gradient data. While ensuring inversion accuracy, this expeditious forward modeling method is integrated into the inversion algorithm. Research findings indicate a significant enhancement in the capability to handle extensive datasets and an improvement in the speed of inversion computations.