Abstract:Research purposes : In the study of magneto telluric inversion methods,models and observational data are generally non-linear, limited and noisy observation data makes the inversion results non-unique, approximate geophysical modeling theory and lack of priori information makes it difficult to solve the problem of global convergence and convergence efficiency simultaneously by all inversion methods. A stable solution of the ill-posed inverse problem can be obtained by utilizing the regularization methods in the objective function. Therefore,it is particularly important to find a suitable dimensional regularization inversion method.
Research conclusions:(1)Solving large scale linear equation of inverse problem,the damped Gauss-Newton algorithm was adopted,which can improve local convergence of Gauss-Newton method. Through the synthetic model simulation, the inversion results based on damped Gauss-Newton algorithm truly reflected the ge。-electrical parameters of the model and accurately showed the depth and size of the abnormal body,So the inversion algorithm has been proven to be effective.(2)Compared with the actual observation data, whether the apparent resistivity data predicted or the impedance phase data,are basically consistent. So the inversion algorithm is accuracy for the applying in two- dimensional magneto telluric data interpretation.(3)Using GCV method can effectively determine the optimum regularization parameter, the ill-posed problem is transformed into well-posed problem for solving , keeping the balance between the data objective function and the objective function constrained by model,the model variance and the image resolution can achieve the best compromise. (4) The inversion method is suitable for two-dimensional magneto telluric forward modeling under the condition of approximate level terrain and can be used to analysis two-dimensional magneto telluric data in the field of railways,highway or other engineering survey.
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