Adaptive direct sampling core 3D reconstruction algorithm

Abstract:

The direct sampling algorithm has certain difficulties in practical application because it introduces a number of parameters that need to be manually adjusted during the reconstruction process. Aiming at this problem, an adaptive direct sampling core threedimensional (3D) reconstruction algorithm is proposed. the image is first reconstructed step by step with threelevel grid. Secondly, Gaussian weighting is used to improve the accuracy of pattern match. Then, according to the conditional data points of the data event to be matched, the pattern search range is adaptively selected, and the center point of the minimum distance pattern is assigned to the point to be simulated. Finally, the proposed algorithm and the traditional direct sampling algorithm are used to perform 3D reconstruction for multiple reservoir core images respectively. The effectiveness of the adaptive direct sampling core 3D reconstruction algorithm is demonstrated by comparing the difference between the reconstruction result and the real structure in the statistical distribution and pore structure.