Abstract
Summary The inversion of gravitational data due to the ill-posed nature of the problem is of importance. To cope with this problem and better estimation of the physical parameters, some kinds of regularization and optimization approaches have been proposed. However, providing an integrated method for inversion is demanding. In this study, we performed a 3D inversion methodology based on graph theory which delineates the skeleton of a subsurface body. Our approach is based on the equidistance function stabilizer with genetic algorithm optimization. Also, we introduced a weighting term in data misfit function using noise level estimation. The algorithm includes an effective method for selecting the regularization parameter. Finally, A MATLAB package for 3D inversion of gravity data using the graph theory approach is developed during this study. We performed some numerical examples for both synthetic and real data. The results indicate applicability and high performance of the proposed approach.
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