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Porous medium super dimensional reconstruction method based on learning

A technology of porous media and three-dimensional images, applied in image data processing, instrumentation, calculation, etc., can solve the problems of long reconstruction time of multi-point geostatistical algorithms, differences in statistical features, and inaccurate morphological features of reference images.

Active Publication Date: 2016-09-21
SICHUAN UNIV
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Problems solved by technology

Usually, these algorithms have different degrees of defects: the reconstruction results of the simulated annealing algorithm are not accurate enough to describe the morphological characteristics of the reference image, the multi-point geostatistical algorithm takes a long time to reconstruct, and the statistical characteristics are different from the reference image

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  • Porous medium super dimensional reconstruction method based on learning
  • Porous medium super dimensional reconstruction method based on learning
  • Porous medium super dimensional reconstruction method based on learning

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Embodiment

[0049] In order to make the learning-based porous medium hyperdimensional reconstruction method of the present invention easier to understand and close to real applications, the following selects 128 original CT image sequences as the training set and uses the sampling strategy at intervals to establish a dictionary. According to the established dictionary The image is reconstructed by layer-by-layer reconstruction, the neighborhood matching strategy of pixel values ​​in the reconstruction process, and the operation process of a series of processes such as pixel value filling by block matching on the basis of the reconstruction results are described as a whole.

[0050] The specific operation steps are as follows:

[0051] (1) Select 128 original CT image sequences of real rock samples as the training set. The CT sequences and their three-dimensional structures are as follows: figure 1 shown. The selected CT image sequence should be complete, so that the established dictionar...

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Abstract

The invention relates to a porous medium super dimensional reconstruction method based on learning. Based on a three-dimensional modeling problem of a porous medium two-dimensional image, a learning method in super resolution reconstruction is introduced in porous medium three-dimensional reconstruction by the porous medium super dimensional reconstruction method, and a dictionary from a single image to a three-dimensional structure is established, and then a super dimensional concept is proposed. The porous medium super dimensional reconstruction method is characterized in that an original CT image sequence is selected, and is used as a training set; the super dimensional reconstruction method is used to establish the dictionary from every two-dimensional image layer of the original three-dimensional CT sequence to the three-dimensional structure of the corresponding positions of five CT image layers including the above mentioned layer by using the super dimensional reconstruction method. Based on the original reference image, a matched three-dimensional structure is searched in the established training set, and the super dimensional reconstruction is realized. A good explanation is provided for a real porous medium microstructure by the reconstructed three-dimensional microstructure, which can be used for the researching of the porous medium microstructure electrical characteristics and the porous flow characteristic, and has the practical value.

Description

technical field [0001] The invention relates to a three-dimensional modeling method based on two-dimensional images, in particular to a learning-based hyperdimensional reconstruction method of porous media, belonging to the technical field of three-dimensional image reconstruction. Background technique [0002] Many industrial applications involve the problems of porous media, such as the development of low and ultra-low permeability oil and gas fields, the utilization of groundwater, the exploitation of gas beds, and the preparation of metal materials, etc. Accurate three-dimensional reconstruction of porous media, and on this basis extract the pore network in the media, and animate the flow of fluid in the media pores, which can not only help people to quickly and conveniently determine the relevant physical parameters of porous media through computer experiments, but also for It is also very helpful to study the influence of the spatial structure of porous media on pore f...

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Application Information

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IPC IPC(8): G06T3/40
CPCG06T3/4053
Inventor 滕奇志何小海李洋李征骥王正勇吴晓红
Owner SICHUAN UNIV
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