A Magnetic-Field-Based Spatial Localization Method for Downhole Tools in Magnetized Casing Environments

In magnetized casing environments, casing-induced magnetic interference can significantly reduce azimuth calculation accuracy and compromise the reliability of downhole tool spatial localization. To address this issue, this study proposes a magnetic-field-based spatial localization method for downhole tools in magnetized casing environments. First, a joint azimuth correction framework is developed. This framework combines ellipse fitting for radial distortion correction, single-axis multi-station analysis (MSA) for axial interference suppression, and a radial basis function neural network (RBFNN) for residual nonlinear error compensation. Subsequently, based on corrected azimuth information, the magnetic field distribution around the magnetized casing is analyzed through theoretical modeling and finite element simulation, and a cosine-type azimuthal response model is established. On this basis, a minimum-residual localization model is constructed to invert the measurement-point height and radial distance. The results show that the proposed correction framework effectively improves azimuth calculation accuracy, with the average RMSE reduced to 0.0371° after RBFNN compensation. In addition, the inverted height and radial distance show good consistency with the experimental values, demonstrating the effectiveness of the proposed localization method. This study provides an effective approach for spatial localization in complex downhole magnetic environments.