Databset for Efficient 3-D forward modeling and mixed norm inversion of the vertical gravity gradient with application to the Vinton salt dome

Inversion of the gravity
gradient data is widely adopted to construct 3-D density models. However, this
inversion usually suffers from non-uniqueness and has a limited resolution in
depth. This study introduces an effective inversion method for interpreting
gravity gradient data based on the mixed L1 and L2 norm regularization. We also
apply an efficient forward modeling algorithm to the inversion, which has many
time-consuming iterations. Equivalence relations in the sensitivity matrix are
employed to reduce the storage and computation time. In addition, a 2-D
discrete convolution algorithm is used to reduce the repetitive calculation in
the forward modeling. The numerical examples demonstrate that the computational
efficiency is increased by about three orders of magnitude compared with the
traditional forward method. Furthermore, compared to traditional single-norm
inversion, the vertical gradient inversion with the mixed L1 and L2 norm
regularization has a higher depth resolution. Finally, we apply the method to
the inversion of the airborne gravity gradiometry data over the Vinton Dome,
southern Louisiana.