Study of 2-D Joint Inversion of Direct Current Resistivity and Audio Magnetotelluric Data Using Adaptive Progressive Mesh Refinement Strategy

Abstract:

The joint inversion of direct currency resistivity data and audio magnetotelluric data under the condition of unstructured triangle mesh is studied. A step-by-step inversion technique is developed,and an adoptive mesh refinement method is studied based on the model sensitivity information. The inversion from coarse mesh to fine mesh reduces the dependence on the stabilizer. Least computational cost of searching regularization factors is required compared with traditional regularization method. The model gradient is calculated by using the least square method.Therefore,the minimum structure stabilizer is established based on unstructured triangle mesh. The cost function is optimized by using the Gauss-Newton method, and the Gauss-Newton system is solved by using the bi-conjugate gradient stable method, aiming to reduce the memory requirement and ensure the stability of inversion. Both the synthetic and field data are inverted.The inversion resolutions show that the joint inversion of the two data sets improve resolutions, and reduce the non-uniqueness of the regularization inversion problem. Joint inversion can get shallow anomalous bodies, which can cause static shift of the audio magnetelluric method.