Method and system for automatically identifying different mineral pores of shale
A technology for automatic identification and shale, applied in character and pattern recognition, acquisition/recognition of microscopic objects, analysis of suspensions and porous materials, etc. It can solve the problems of different processing results, errors, cumbersome steps, etc.
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Embodiment 1
[0097] figure 1 It is a flow chart of the method for automatic identification of different mineral pores of shale in Example 1 of the present invention.
[0098] see figure 1 , the method for automatic recognition of different mineral pores of mud shale of the embodiment, comprising:
[0099] Step S1: Obtain the grayscale image of the mud shale scanning electron microscope.
[0100] Step S2: Determine the inorganic mineral pore map and the kerogen region map of the SEM grayscale map of the mud shale.
[0101] The step S2 specifically includes:
[0102] 1) Counting the number of pixels of each gray value in the SEM gray image of the mud shale to obtain a relationship curve of the number of pixels changing with the gray value.
[0103] 2) Determine the gray value corresponding to the highest point of the organic matter peak, the gray value corresponding to the highest point of the main mineral peak, the gray value and the peak width corresponding to the bright mineral peak i...
Embodiment 2
[0152] The method for automatic recognition of different mineral pores of mud shale in this embodiment includes:
[0153] Step 1: Use a scanning electron microscope to obtain a scanning electron microscope image of the mud shale and use an energy spectrometer to obtain an energy spectrum mineral distribution map corresponding to the grayscale image of the mud shale scanning electron microscope. Convert the mud shale scanning electron microscope image into an 8-bit grayscale image, count the number of pixels in each grayscale of 0 to 255 in the mud shale scanning electron microscope grayscale image, and draw the variation of the number of pixels with the grayscale relationship curve, see figure 2 , in the relationship curve composed of multiple points, each scatter point represents the number of pixels corresponding to a gray value.
[0154] Step 2: Use the Gaussian peak fitting method to fit the relationship curve obtained in step 1 to obtain a fitting curve, from which the ...
Embodiment 3
[0180] The present invention also provides an automatic recognition system for different mineral pores of mud shale, Figure 16 It is a schematic structural diagram of an automatic identification system for different mineral pores of mud shale in Example 3 of the present invention. see figure 1 , The automatic recognition system for different mineral pores of mud shale includes:
[0181] The image acquisition module 1601 is configured to acquire the grayscale image of the mud shale scanning electron microscope.
[0182] The first determining module 1602 is configured to determine the inorganic mineral pore map and the kerogen region map of the grayscale image of the scanning electron microscope of the mud shale.
[0183] The expansion module 1603 is configured to perform an expansion operation on the inorganic mineral pore map to obtain the expanded inorganic mineral pore map.
[0184]The second determination module 1604 is configured to compare the inorganic mineral pore m...
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