Quantitative characterization and parameter acquisition method for reservoir and seepage space of shale oil reservoir
A technology for quantitative characterization and parameter acquisition, applied in permeability/surface area analysis, measurement devices, surface/boundary effects, etc., to achieve process controllable and representative effects
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Embodiment 1
[0042] A method for quantitative characterization and parameter acquisition of shale oil reservoir storage and seepage space, such as figure 1 shown, including the following steps,
[0043] S1. Obtain the image information of the real core of the shale reservoir in the target area, and process it to obtain numerical information; process the numerical information to obtain the statistical characteristics of the microscopic pore structure of the storage and seepage space.
[0044] In this embodiment, the image information is acquired by a scanning electron microscope imaging method, and an SEM image of the target rock core is obtained. After the SEM image of the target core is obtained, the image information is numerically processed to obtain numerical information, that is, the image information of the real core is binarized by the maximum inter-class error method to obtain numerical information.
[0045] The maximum inter-class error method divides the image into two parts, th...
specific Embodiment approach
[0073] In this example, the middle and lower Jurassic Qianer Member shale oil reservoir cores in northern Sichuan are selected to provide a specific implementation method for quantitative characterization of shale oil reservoir storage and seepage space and parameter acquisition method, including the following steps:
[0074] (1) Select the shale core in the target area and interval, scan it with a scanning electron microscope and obtain the required image.
[0075] (2) Using MATLAB software, the maximum between-class variance method is used to numerically process the SEM image of the core to obtain the statistical characteristics, that is, the distribution characteristics of the pore structure and pore morphology. Figure 4 The results shown.
[0076] (3) Determine the number of three-dimensional grids that need to generate the porous medium model as 200×200×200, the resolution is 25nm / pixel, and the porosity is 11%. Based on the four-parameter random growth model, the porou...
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