Automatic estimation of the regularization parameter in 2D focusing gravity inversion: application of the method to the Safo manganese mine in the northwest of Iran

We investigate the use of Tikhonov regularization with the minimum support stabilizer for underdetermined 2D inversion of gravity data. This stabilizer produces models with non-smooth properties which is useful for identifying geologic structures with sharp boundaries. A very important aspect of using Tikhonov regularization is the choice of the regularization parameter that controls the trade-off between the data fidelity and the stabilizing functional. The L-curve and generalized cross-validation techniques, which only require the relative sizes of the uncertainties in the observations, are considered. Both criteria are applied in an iterative process; at each iteration a value for the regularization parameter is estimated. Suitable values for the regularization parameter are successfully determined in both cases for synthetic, but practically relevant, examples. Whenever the geologic situation permits, it is easier and more efficient to model the subsurface with a 2D algorithm, rather than to apply a full 3D approach. Then, because the problem is smaller it is appropriate to use the generalized singular value decomposition to solve the problem efficiently. The method is applied to a profile of gravity data acquired over the Safo mining camp in Maku, Iran, which is well known for manganese ores. The presented results demonstrate success in reconstructing the geometry and density distribution of the subsurface source.