A Dual‐Parameter Regularization Method for Electrical Conductivity Imaging

Abstract

AbstractThis paper presents a dual‐parameter regularization method with a term that has a second order regularization operator. The optimal value of the regularization parameter is determined by applying the L‐curve criterion, the discrepancy principle and generalized cross‐validation. The validity and superiority of the proposed method is verified by numerical simulations of the theoretical model with truncated singular value decomposition, conjugate gradient, and standard‐form Tikhonov regularizations. The results are of very high precision and stable against random data noise. Finally, we apply the proposed method to geophysical inversion problems in electrical conductivity imaging. The imaging results suggest that the proposed method improves the imaging quality and fidelity. This further validates that, when it is applied to geophysical inversion problems, the proposed method improves the stability of inversion, reduces the possible multiplicity of solutions, and enhances computation speed.