Abstract: It is difficult to measure the deformation of oil and gas strings affected by the ground movement for a long time. In order to solve this problem, an inversion algorithm for extrusion deformation estimation of oil and gas strings based on pulsed eddy current was studied, and an extrusion deformation estimation method of oil and gas strings based on AICRBF was put forward. In the method, the AIC-based polynomial fitting optimization algorithm for deformation of oil and gas strings and RBF-based polynomial parameter estimation model were included. The pulsed eddy current signals of the different extrusion sections of the string were tested, the deformation polynomial function was obtained, and the minimum arm length of the extrusion section was quantified to estimate the degree of deformation. As shown by the experimental results, the AIC-RBF algorithm has smaller quantization error, better stability and faster quantization speed than the traditional RBF neural network algorithm and BP neural network algorithm, capable of satisfying the requirement of accurate quantization of the extrusion degree of oil and gas strings.