Abstract: To address the issues of insufficient spatial structure representation and low image accuracy in traditional two-dimensional wellbore imaging technology, this paper proposes a three-dimensional wellbore imaging method based on point cloud conversion and grid reconstruction using standardized logging data. Firstly, based on a three-dimensional point cloud conversion method, a three-dimensional coordinate mapping model for logging data is constructed, mapping radial measurement values and depth information to a three-dimensional coordinate system, redefining the data structure, and achieving standardized representation of logging data. Then, the point cloud data is corrected and optimized in conjunction with wellbore trajectory parameters. Through the spherical linear interpolation algorithm (Slerp) and grid algorithms, high-precision three-dimensional imaging of the wellbore spatial structure is realized. Finally, using the actual measurement data of Well X in the Ordos Basin as an example, imaging inversion verification and comparison experiments were conducted. The results show that the proposed method outperforms traditional methods in both three-dimensional structure restoration accuracy and imaging efficiency. Compared with the convex hull method and ball-pivoting algorithm (BPA) used in traditional point cloud three-dimensional imaging, the imaging time is reduced by 34.5% and 57.8%, respectively, and the grid imaging completeness is increased to 98.6%, improving by 6.9 and 27.9 percentage points, respectively. This method can more accurately reflect the wellbore morphology and deformation characteristics, providing an efficient and reliable technical approach for three-dimensional imaging of complex wellbore structures and downhole condition assessment.