Abstract:In core image analysis, Lowresolution core images can display a larger fields of view and have better global representation, but cannot accurately characterize the lowscale information; Whilehighresolution core images can accurately represent the lowscale information of the core,but usually only show a smaller field of view. In order to comprehensively analysis different core images in high and low resolution, An algorithm is proposed based on simulated annealing to reconstruct lowresolution 3D core image into highresolution 3D core with highresolution twodimensional (2D) core image being the constraint information. For a given highresolution 2D core image, the lowresolution 3D core image is first interpolated to unify the length of the any two points, the pore distribution in the 2D core image is counted, and the small pores in the highresolution 2D image are retained as a training image. In the fusion reconstruction process, the largesize pores in the lowresolution 3D core are set as hard data, and the autocorrelation function is used as the objective function to reconstruct the smallsized pores. The experimental results show that the fusion reconstruction algorithm proposed in the paper can reconstruct the lowresolution core into a highresolution core structure, and the fusion reconstruction results are effective and accurate.