The interpretation of magnetic anomalies by 3D inversion: A case study from Central Iran

• From a hydrocarbon exploration viewpoint, the study area has been highly recommended as a target area in Iran.
• Role of magnetic data inversion in reconstructing a high magnetic susceptibility subsurface highlighted.
• The algorithm is usable in magnetic data inversion and interpretation.

The thick sedimentary units in Central Iran contain structures that form oil traps and are underlain by a basaltic layer which is amenable for study using its magnetic susceptibility. The study and modeling of such sedimentary structures provide valuable exploratory information. In this study, we locate and interpret an underground magnetic susceptibility interface using 3D non-linear inverse modeling of magnetic data to make a better judgment in the context of hydrocarbon existence. The 3D structure is reconstructed by making it equal to a number of side by side rectangular hexahedrons or prisms and calculating their thicknesses such that the bottoms of the prisms are corresponding to the magnetic susceptibility interface. By one of the most important mathematical tool in computational science, Taylor series, the non-linear problem changes to a linear problem near to initial model. In many inverse problems, we often need to invert large size matrices. To find the inverse of these matrices we use Singular Value Decomposition (SVD) method. The algorithm by an iterative method comparing model response with actual data will modify the initial guess of model parameters. The efficiency of the method and subprograms, programmed in MATLAB, has been shown by inverse modeling of free noise and noise-contaminated synthetic data. Finally, we inverted magnetic field data from Garmsar area in Central Iran which the results were acceptable.