Conglomerate pore structure characterization method based on CT three-dimensional data volume
A pore structure, three-dimensional data technology, applied in permeability/surface area analysis, suspension and porous material analysis, measurement devices, etc. And other issues
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Embodiment 1
[0053] Example 1: See Figure 1 to Figure 17 , a conglomerate pore structure characterization method based on CT three-dimensional data volume in this embodiment, comprising the following steps: S1: Select a conglomerate sample with a diameter of 8 mm-100 mm, and perform three-dimensional scanning on the selected conglomerate to obtain The two-dimensional grayscale image of the conglomerate sample and the three-dimensional digital core data volume; S2: image processing on the two-dimensional grayscale image, eliminating image noise and enhancing the details of pores in the image; S3: using the interactive threshold segmentation method to image the The first extraction of the pore structure between sand and gravel particles; S4: Using the method of top-bottom hat transformation to stretch the foreground and background grayscale of the grayscale image, highlighting the details of weak structural pores in the conglomerate grayscale image Information, the secondary extraction of p...
Embodiment 2
[0055] Embodiment 2: In this embodiment, in step S1, the apparent structure of the conglomerate samples is observed, and representative conglomerate samples that meet the analysis requirements are selected. Based on the principle that the sample size is larger than the diameter of the largest gravel, conglomerate samples with a diameter of 8mm-100mm can be selected. In step S1 of this embodiment, it also includes three-dimensional scanning of the selected conglomerate samples using a CT scanning system. data body. In step S2 of this embodiment, in view of the various types of noise existing in the grayscale image of the conglomerate sample in its scanning environment, the grayscale image is processed by median filtering to eliminate the noise existing in the image, so that the grayscale image becomes It is clearer, and at the same time, it can better preserve the details and edge information of the image.
Embodiment 3
[0056] Embodiment 3: In this embodiment, in step S3, the interactive threshold segmentation method is used to extract the pore structure for the first time, starting from the gray level of the two-dimensional grayscale image, the gray level of all pixels is compared with the threshold value and then Select an appropriate threshold to extract most of the pore structures that are easy to extract, and try to avoid overflow of pore volume during extraction. In step S4 of this embodiment, the method of combining top-down hat transformation is used to further stretch the foreground and background grayscale of the grayscale image, highlighting the details of weak structural pores in the grayscale image of conglomerate, and to play a role in correcting grayscale. degree of image enhancement.
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