Fast 3D inversion of gravity data using Lanczos bidiagonalization method

This paper describes the application of a new inversion method to recover a three-dimensional density model from measured gravity anomalies. To attain this, the survey area is divided into a large number of rectangular prisms in a mesh with unknown densities. The results show that the application of the Lanczos bidiagonalization algorithm in the inversion helps to solve a Tikhonov cost function in a short time. The performance time of the inverse modeling greatly decreases by substituting the forward operator matrix with a matrix of lower dimension. A least-squares QR (LSQR) method is applied to select the best value of a regularization parameter. A Euler deconvolution method was used to avoid the natural trend of gravity structures to concentrate at shallow depth. Finally, the newly developed method was applied to synthetic data to demonstrate its suitability and then to real data from the Bandar Charak region (Hormozgan, south Iran). The 3D gravity inversion results were able to detect the location of the known salt dome (density contrast of −0.2 g/cm3) intrusion in the study area.