Abstract: To address the problems of strong nonlinearity between ultra-deep azimuthal electromagnetic look-ahead logging signals and geological parameters, high inversion difficulty, and immature related algorithms, a regularization inversion method is proposed for rapidly extracting formation resistivity and interface parameters. First, through theoretical analysis, the influence of the regularization factor on the iterative process is clarified, and a regularization factor selection algorithm is designed to restrict the model iteration amount within a preset upper limit, thereby enhancing algorithm stability. Then, the effect of the initial model on the iteration is analyzed, and an initial model database is constructed to achieve rapid selection of initial models. Finally, based on two-layer and multi-layer models, rapid inversion of look-ahead resistivity curtain graphs is generated. The results demonstrate that the regularization inversion algorithm can accurately and rapidly invert formation resistivity and boundary information, with good stability. The proposed inversion algorithm lays a theoretical foundation for the future processing of ultra-deep azimuthal electromagnetic measurements for look-ahead.