CN113484215A - Sandstone reservoir microscopic pore analysis system based on geological cause - Google Patents
Sandstone reservoir microscopic pore analysis system based on geological cause Download PDFInfo
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Abstract
The invention discloses a geological cause-based sandstone reservoir microscopic pore analysis system which comprises a rock stratum analysis unit, a sound wave analysis unit, an information analysis unit, a pore permeation test unit and an information repository unit, wherein the rock stratum analysis unit is in communication connection with the information analysis unit, the sound wave analysis unit is in communication connection with the information analysis unit, the information analysis unit is in communication connection with the information repository unit, and the pore permeation test unit is in communication connection with the information analysis unit. According to the invention, the information is compared through the rock stratum analysis unit according to the local geological cause, so that the acquisition speed of the information such as the characteristics, the structure, the configuration relation and the like of the rock stratum is increased, the acquisition difficulty of the information is reduced, and manpower and material resources are saved.
Description
Technical Field
The invention relates to the field of geological analysis, in particular to a system for analyzing micro pores of a sandstone reservoir based on geological causes.
Background
A formation that can store and percolate fluids is called a formation in which a reservoir is able to store and percolate hydrocarbons and must have storage space (porosity) and some connectivity of the storage space (permeability). The sandstone reservoir is a deep high-pressure low-permeability sandstone reservoir with high sandstone content in rock, belongs to the category of low-permeability reservoirs, and is different from the conventional low-permeability reservoirs. The great change of the formation pressure in the oil reservoir development causes the change of the pore structure and the physical property, and the oil field development effect is influenced. The knowledge of the microscopic pore throat characteristics of the reservoir is the key to the development of the oil reservoir.
At present, a constant-speed mercury pressing machine and a high-pressure mercury pressing machine are generally used for testing and analyzing rock strata, information such as characteristics, structures, configuration relations and the like among the layers of the sandstone rock strata cannot be known exactly, satisfactory results cannot be achieved, and when reservoir classification analysis is carried out, multiple complex experiments are needed to confirm the structure of the sandstone reservoir, so that a large amount of time is wasted.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: at present, when the analysis of the sandstone reservoir pores is carried out, information such as characteristics, structures, configuration relations and the like among layers of the sandstone reservoir cannot be known exactly, and a plurality of complicated experiments are often needed to confirm the structure of the sandstone reservoir, so that a large amount of time is wasted.
The invention solves the technical problems by the following technical scheme, and the invention provides a sandstone reservoir microscopic pore analysis system based on geological causes, which comprises a rock stratum analysis unit, a sound wave analysis unit, an information analysis unit, a pore permeation test unit and an information repository unit, wherein the rock stratum analysis unit is in communication connection with the information analysis unit, the sound wave analysis unit is in communication connection with the information analysis unit, the information analysis unit is in communication connection with the information repository unit, and the pore permeation test unit is in communication connection with the information analysis unit;
the rock stratum analyzing unit comprises an image shooting module, an image recognition module, an image verification module, an image detail amplification and interception module, an image analyzing and processing module, an image information storage module, a characteristic comparison module and an image deep learning module;
the sound wave analysis unit comprises a sound wave generation module, a first sound wave receiving module, a second sound wave receiving module, a sound wave analysis module, a sound wave information storage module, a sound wave characteristic comparison module and a sound wave information characteristic deep learning module;
the information analysis unit comprises a crack characteristic determination module, a pore throat characteristic determination module, an information integration module, an information splitting module and a temporary information storage module;
the hole seepage test unit comprises a microscopic module, a hole seepage experiment module, a data recording module and a test precision confirmation module, wherein the hole seepage experiment module is in communication connection with the data recording module, the microscopic module is in communication connection with the data recording module, and the data recording module is in communication connection with the test precision confirmation module;
the information repository unit comprises a storage module, an information extraction module, an information recording module, an information encryption module and an information decryption module.
Preferably, the operation process of the formation analysis unit is as follows:
s1: firstly, shooting the most obvious position of a stratum fault through the image shooting module, observing different reservoir fault conditions when shooting a fault plane, shooting one group of images in one time period, wherein the number of each group of images is 10, and the interval time is 10min, and shooting 5 groups of images in total;
s2: randomly extracting 10 images from the image shooting module to form a new group, and identifying the most obvious image of the stratum fault through the image identification module;
s3: verifying the image identified in the step S2 with the image in the step S1 by the image verification module;
s4: secondly, performing detail amplification and interception of each stratum fault on the image obtained in the step S2 through the image detail amplification and interception module, setting the number of stratum faults as N, and adding the extracted identification for the second time before the name data of the image to form a group of detail amplification images, wherein the number of the stratum faults is N-1;
s5: performing M times, wherein M is more than or equal to 3, transmitting the obtained M groups of images into the image analysis processing module for processing operation, and transmitting the images into the image information storage module for storage;
s6: analyzing one image with the largest difference of pixel points in each group of images through the image analysis processing module, and rejecting the image;
s7: extracting all images with the similarity exceeding a preset value in the image information storage module from the image information storage module through image similarity information, and comparing the extracted images with the shot images by using the characteristic comparison module so as to confirm the type of each rock layer;
s8: under the condition that corresponding data cannot be obtained by using the characteristic comparison module, manual detection is carried out, and deep learning is carried out in the image deep learning module.
Preferably, the specific processing procedure of the image similarity information is as follows:
s11: setting a first pixel from the left bottom of the image as a coordinate origin, setting the horizontal direction as an X axis and the vertical direction as a Y axis, positioning each pixel point in the image, wherein the coordinates of the pixel point are (X, Y);
s12: selecting coordinate axes of pixel points of the first contrast image and the second contrast image in an S11 mode, determining the color of the pixel points by using RGB color numbers, and setting the color numbers as Z, so that each pixel point is [ (X, Y) Z ];
s13: if [ (X1, Y1) Z1] is the same as [ (X2, Y2) Z2], it means that the first and second contrast images have the same color at the point of (X, Y), and the similarity between two points is 100%;
s14: when the colors of the first contrast image and the second contrast image are different at a certain point (X, Y), comparing the colors around the pixel point, and comparing [ (X, Y) Z ] with 8 surrounding pixel points: { [ (X, Y) Zn ], [ (X +1, Y) Zn ], [ (X-1, Y) Zn ], [ (X, Y +1) Zn ], [ (X, Y-1) Zn ], [ (X +1, Y +1) Zn ], [ (X +1, Y-1) Zn ], [ (X-1, Y +1) Zn ] }, selecting pixel points with the same Zn and Z, marking the similarity of two pixel points corresponding to (X, Y) of the first contrast image and the second contrast image as 50%, and marking the similarity of two pixel points corresponding to (X, Y) of the first contrast image and the second contrast image as 0% if no same pixel points exist;
s15: and after all pixels are compared, taking the average of the similarity of loudness points of all the same coordinate axes of the first contrast image and the second contrast image to position the similarity of the whole image.
Preferably, the specific processing procedure of the acoustic wave analysis unit is as follows:
s111: the sound wave generation module is used for emitting sound waves of different frequency bands, the sound waves last for 2s in sequence, and the sound wave emission time interval is 3min every two times;
s112: performing a sound wave receiving operation using the first sound wave receiving module and a second sound wave receiving module;
s113: storing the sound waves received by the first sound wave receiving module and the second sound wave receiving module each time by using a sound wave information storage module;
s114: comparing the sound wave signals received by the first sound wave receiving module and the second sound wave receiving module through the sound wave characteristic comparison module;
s115: and finally, analyzing the two groups of sound waves through the sound wave analyzing module, performing deep learning by using the sound wave information characteristic deep learning module, and expanding a database in the sound wave information storage module.
Preferably, the specific treatment process of the pore permeation test unit is as follows:
s1111: shooting and observing the rock stratum through a microscopic module, and selecting a proper sample to perform a pore-permeation experiment;
s1112: carrying out a pore permeation experiment on the sample at the selected position through a pore permeation experiment module;
s1113: recording data by using a data recording module;
s1114: and after the recording is finished, detecting each item of data of the experiment by using the test precision confirmation module.
Preferably, the specific processing procedure of the information repository unit is as follows:
s11111: various information is transmitted into the information recording module, and the data is encrypted through the information encryption module;
s11112: after encryption is finished, transmitting the encrypted data to a storage module for storage, wherein the storage module contains geological cause information and can be called by the sound wave analysis module;
s11113: after the required extraction data is extracted from the storage module, the decryption is carried out through the information decryption module.
Preferably, the image recognition module is in communication connection with the image verification module, the image detail amplification and interception module is in communication connection with the image recognition module, the image detail amplification and interception module is in communication connection with the image verification module, the image detail amplification and interception module is in communication connection with the image analysis processing module, the image information storage module is in communication connection with the image analysis processing module, and the image information storage module is in communication connection with the image detail amplification and interception module.
Preferably, sound wave generation module and first sound wave receiving module communication connection, sound wave generation module and second sound wave receiving module communication connection, first sound wave receiving module compares module communication connection with the sound wave characteristics, second sound wave receiving module compares module communication connection with the sound wave characteristics, the sound wave characteristics compares module and sound wave analysis module communication connection, sound wave analysis module and sound wave information characteristics degree of deep learning module communication connection, sound wave analysis module and sound wave information storage module communication connection, sound wave information storage module and sound wave information characteristics degree of deep learning module communication connection.
Preferably, the fracture characteristic determination module is in communication connection with the information integration module, the pore throat characteristic determination module is in communication connection with the information integration module, the information integration module is in communication connection with the temporary information storage module, and the temporary information storage module is in communication connection with the information splitting module.
Preferably, the information recording module is in communication connection with the information encryption module, the information encryption module is in communication connection with the storage module, the storage module is in communication connection with the information extraction module, and the information extraction module is in communication connection with the information decryption module.
Compared with the prior art, the invention has the following advantages:
1. the invention firstly takes the image of the most easily found fault of the rock stratum through the image taking module, then compares the taken image with the local geological image information in the storage module, then intercepts and amplifies the places with the same details and different details through the image detail amplifying and intercepting module, then transmits the obtained image to the image analyzing and processing module for processing operation, extracts all the images with the similarity exceeding the preset value in the image information storage module from the image information storage module through the image similarity information, and uses the characteristic comparison module to compare the taken image with the taken image so as to obtain the information of the features, the structures, the configuration relations and the like of the rock stratum, and compares the image information according to the local geological causes, thereby quickening the acquisition speed of the information of the features, the structures, the configuration relations and the like of the rock stratum and reducing the acquisition difficulty of the information, manpower and material resources are saved;
2. according to the invention, the sound wave generating module in the sound wave analyzing unit is used for sending out sound waves, the data obtained by the first sound wave receiving module and the second sound wave receiving module are compared, the average value of the two groups of data is taken, the sound waves are analyzed by the sound wave analyzing module, the information such as the characteristics, the structure and the configuration relation of the rock stratum is further confirmed, and the accuracy and the reliability of the data can be improved;
3. according to the invention, the CCMC encryption is carried out on the data received by the information recording module through the information encryption module in the information repository unit, so that the situation that geological data is stolen can be effectively prevented, and the labor achievement of Chinese science and technology personnel is effectively protected.
Drawings
FIG. 1 is an overall system block diagram of the present invention.
Fig. 2 is a system block diagram of a formation resolution unit of the present invention.
Fig. 3 is a system block diagram of the acoustic wave analyzing unit of the present invention.
Fig. 4 is a system block diagram of an information analysis unit of the present invention.
FIG. 5 is a system block diagram of a pore penetration test unit of the present invention.
Fig. 6 is a system block diagram of an information repository unit of the present invention.
Detailed Description
The following examples are given for the detailed implementation and specific operation of the present invention, but the scope of the present invention is not limited to the following examples.
As shown in fig. 1 to 6, the present embodiment provides a technical solution: a sandstone reservoir microscopic pore analysis system based on geological causes comprises a rock stratum analysis unit, a sound wave analysis unit, an information analysis unit, a pore-permeability test unit and an information repository unit, wherein the rock stratum analysis unit is in communication connection with the information analysis unit;
the rock stratum analyzing unit comprises an image shooting module, an image recognition module, an image verification module, an image detail amplifying and intercepting module and an image analyzing and processing module, wherein the image information storage module, a characteristic comparison module and an image deep learning module are connected in a communication mode;
the sound wave analysis unit comprises a sound wave generation module, a first sound wave receiving module, a second sound wave receiving module, a sound wave analysis module, a sound wave information storage module, a sound wave characteristic comparison module and a sound wave information characteristic deep learning module, wherein the sound wave generation module is in communication connection with the first sound wave receiving module, the sound wave generation module is in communication connection with the second sound wave receiving module, the first sound wave receiving module is in communication connection with the sound wave characteristic comparison module, the second sound wave receiving module is in communication connection with the sound wave characteristic comparison module, the sound wave characteristic comparison module is in communication connection with the sound wave analysis module, the sound wave analysis module is in communication connection with the sound wave information deep learning module, the sound wave analysis module is in communication connection with the sound wave information storage module, and the sound wave information storage module is in communication connection with the sound wave information characteristic deep learning module;
the information analysis unit comprises a crack characteristic determination module, a pore throat characteristic determination module, an information integration module, an information splitting module and a temporary information storage module, wherein the crack characteristic determination module is in communication connection with the information integration module;
the hole seepage test unit comprises a microscopic module, a hole seepage experiment module, a data recording module and a test precision confirming module, wherein the hole seepage experiment module is in communication connection with the data recording module, the microscopic module is in communication connection with the data recording module, and the data recording module is in communication connection with the test precision confirming module;
the information repository unit comprises a storage module, an information extraction module, an information recording module, an information encryption module and an information decryption module, wherein the information recording module is in communication connection with the information encryption module, the information encryption module is in communication connection with the storage module, the storage module is in communication connection with the information extraction module, and the information extraction module is in communication connection with the information decryption module.
Preferably, the operation of the formation resolution unit is as follows:
s1: firstly, the most obvious part of a stratum fault is shot through the image shooting module, one group of images are shot in one time period, the number of each group of images is 10, the interval time is 10min, 5 groups of images are shot in total, the image shooting module uses an ultra-high-definition camera with 2 hundred million pixels and uses a circle of no-light lamp to perform light supplement operation;
s2: randomly extracting 10 images from the image shooting module to form a new group, and identifying the most obvious image of the stratum fault by the image identification module;
s3: then, the image identified in S2 and the image in S1 are verified through an image verification module;
s4: the image detail amplification and interception module is used for amplifying and intercepting the detail of each stratum fault of the image obtained in the S2, if the number of the stratum faults is N, the number of the amplified and intercepted images is N-1, the extracted identification for the second time is added in front of the name data of the image to form a group of detail amplification images, and each image after interception is kept at least 1000 ten thousand pixels;
s5: performing M times, wherein M is more than or equal to 3, transmitting the obtained M groups of images into an image analysis processing module for processing operation, and transmitting the images into an image information storage module for storage, wherein the image information storage module is a tape reel with good stability;
s6: analyzing one image with the largest difference of pixel points in each group of images through an image analysis processing module, and rejecting the image;
s7: then, extracting all the images with the similarity exceeding the preset value in the image information storage module from the image information storage module through the image similarity information, comparing the extracted images with the shot images through the characteristic comparison module, and further confirming the types of all rock layers, wherein the preset values can be 50%, 60% and 85%, and are preset as required;
s8: under the condition that corresponding data cannot be obtained by using the characteristic comparison module, the image deep learning module is used for deep learning, and is an A100 deep learning display card of great invigoration, so that the image deep learning module is convenient to use for deep learning, and a better deep learning effect can be provided.
Preferably, the specific processing procedure of the image similarity information is as follows:
s11: setting a first pixel from the left bottom of the image as a coordinate origin, setting the horizontal direction as an X axis and the vertical direction as a Y axis, positioning each pixel point in the image, wherein the coordinates of the pixel point are (X, Y);
s12: selecting coordinate axes of pixel points of the first contrast image and the second contrast image in an S11 mode, determining the color of the pixel points by using RGB color numbers, and setting the color numbers as Z, so that each pixel point is [ (X, Y) Z ];
s13: if [ (X1, Y1) Z1] is the same as [ (X2, Y2) Z2], it means that the first and second contrast images have the same color at the point of (X, Y), and the similarity between two points is 100%;
s14: when the colors of the first contrast image and the second contrast image are different at a certain point (X, Y), comparing the colors around the pixel point, and comparing [ (X, Y) Z ] with 8 surrounding pixel points: { [ (X, Y) Zn ], [ (X +1, Y) Zn ], [ (X-1, Y) Zn ], [ (X, Y +1) Zn ], [ (X, Y-1) Zn ], [ (X +1, Y +1) Zn ], [ (X +1, Y-1) Zn ], [ (X-1, Y +1) Zn ] }, selecting pixel points with the same Zn and Z, marking the similarity of two pixel points corresponding to (X, Y) of the first contrast image and the second contrast image as 50%, and marking the similarity of two pixel points corresponding to (X, Y) of the first contrast image and the second contrast image as 0% if no same pixel points exist;
s15: and after all pixels are compared, taking the average of the similarity of loudness points of all the same coordinate axes of the first contrast image and the second contrast image to position the similarity of the whole image.
Preferably, the specific processing procedure of the acoustic wave analysis unit is as follows:
s111: the sound wave generation module is used for emitting sound waves of different frequency bands, the sound waves last for 2s in sequence, and the sound wave emission time interval is 3min every two times;
s112: performing a sound wave receiving operation using the first sound wave receiving module and the second sound wave receiving module;
s113: storing the sound waves received by the first sound wave receiving module and the second sound wave receiving module each time by using a sound wave information storage module;
s114: comparing the sound wave signals received by the first sound wave receiving module and the second sound wave receiving module through a sound wave characteristic comparison module, wherein the model of the first sound wave receiving module and the model of the second sound wave receiving module are DA9052QFN, and the model of the sound wave generating module is SXD-15-3800;
s115: and finally, analyzing the two groups of sound waves through a sound wave analysis module, performing deep learning by using a sound wave information characteristic deep learning module, and expanding a database in a sound wave information storage module.
Preferably, the specific process of the pore penetration test unit is as follows:
s1111: shooting and observing the rock stratum through a microscopic module, and selecting a proper sample to perform a pore-permeation experiment;
s1112: carrying out a pore permeation experiment on the sample at the selected position through a pore permeation experiment module;
s1113: recording data by using a data recording module;
s1114: and after the recording is finished, detecting each item of data of the experiment by using a test precision confirmation module.
Preferably, the specific processing procedure of the information repository unit is as follows:
s11111: various information is transmitted into the information recording module, and the data is encrypted through the information encryption module;
s11112: after encryption is finished, transmitting the encrypted data to a storage module for storage, wherein the storage module contains geological cause information and can be called by a sound wave analysis module;
s11113: after the required extracted data is extracted from the storage module, the data is decrypted through the information decryption module, the storage module comprises a mechanical hard disk and a tape hard disk, the data in the mechanical hard disk and the tape hard disk are the same, and the encryption mode adopts a CCMC encryption format.
In summary, the invention first takes the image of the most easily found fault of the rock formation through the image taking module, then compares the taken image with the local geological image information in the storage module, then intercepts and amplifies the places with the same details and different details through the image detail amplifying and intercepting module, then transmits the obtained image to the image analyzing and processing module for processing operation, extracts all the images with the similarity exceeding 85% in the image information storage module from the image information storage module through the image similarity information, and uses the characteristic comparison module to compare the taken image with the taken image, so as to obtain the information of the features, the structures, the configuration relations and the like of the rock formation, and compares the image information according to the local geological causes, thereby quickening the speed of obtaining the information of the features, the structures, the configuration relations and the like of the rock formation and reducing the difficulty of obtaining the information, manpower and material resources are saved; the sound wave generating module in the sound wave analyzing unit sends out sound waves, data obtained by the first sound wave receiving module and the second sound wave receiving module are compared, the average value of the two sets of data is obtained, the sound waves are analyzed through the sound wave analyzing module, and information such as the characteristics, the structure and the configuration relation of the rock stratum is further confirmed; the information encryption module in the information repository unit carries out CCMC encryption on the data received by the information recording module, so that the condition that geological data is stolen can be effectively prevented, and the labor achievement of Chinese science and technology personnel is effectively protected.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, reference to the description of the terms "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, formation, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, layers, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. The sandstone reservoir microscopic pore analysis system based on the geological cause is characterized by comprising a rock stratum analysis unit, a sound wave analysis unit, an information analysis unit, a pore-permeability test unit and an information storage library unit, wherein the rock stratum analysis unit is in communication connection with the information analysis unit, the sound wave analysis unit is in communication connection with the information analysis unit, the information analysis unit is in communication connection with the information storage library unit, and the pore-permeability test unit is in communication connection with the information analysis unit;
the rock stratum analysis unit comprises an image shooting module, an image identification module, an image verification module, an image detail amplification and interception module, an image analysis processing module, an image information storage module, a characteristic comparison module and an image deep learning module, wherein the image shooting module is in communication connection with the image identification module;
the sound wave analysis unit comprises a sound wave generation module, a first sound wave receiving module, a second sound wave receiving module, a sound wave analysis module, a sound wave information storage module, a sound wave characteristic comparison module and a sound wave information characteristic deep learning module;
the information analysis unit comprises a crack characteristic determination module, a pore throat characteristic determination module, an information integration module, an information splitting module and a temporary information storage module;
the hole seepage test unit comprises a microscopic module, a hole seepage experiment module, a data recording module and a test precision confirmation module, wherein the hole seepage experiment module is in communication connection with the data recording module, the microscopic module is in communication connection with the data recording module, and the data recording module is in communication connection with the test precision confirmation module;
the information repository unit comprises a storage module, an information extraction module, an information recording module, an information encryption module and an information decryption module.
2. The system for analyzing the micro-pores of the sandstone reservoir based on geological causes of claim 1, wherein: the operation process of the rock stratum resolving unit is as follows:
s1: firstly, shooting the most obvious position of a stratum fault through the image shooting module, shooting one group of images in one time period, wherein the number of each group of images is 10, the interval time is 10min, and shooting 5 groups of images in total;
s2: randomly extracting 10 images from the image shooting module to form a new group, and identifying the most obvious image of the stratum fault through the image identification module;
s3: verifying the image identified in the step S2 with the image in the step S1 by the image verification module;
s4: secondly, performing detail amplification and interception of each stratum fault on the image obtained in the step S2 through the image detail amplification and interception module, setting the number of stratum faults as N, and adding the extracted identification for the second time before the name data of the image to form a group of detail amplification images, wherein the number of the stratum faults is 10 to be N-1;
s5: performing M times, wherein M is more than or equal to 3, transmitting the obtained M groups of images into the image analysis processing module for processing operation, and transmitting the images into the image information storage module for storage;
s6: analyzing one image with the largest difference of pixel points in each group of images through the image analysis processing module, and rejecting the image;
s7: extracting all images with preset similarity values in the image information storage module from the image information storage module through image similarity information, and comparing the extracted images with shot images by using the characteristic comparison module so as to confirm the types of rock layers;
s8: under the condition that corresponding data cannot be obtained by using the characteristic comparison module, manual detection is carried out, and deep learning is carried out in the image deep learning module.
3. The system for analyzing the micro-pores of the sandstone reservoir based on geological causes as claimed in claim 2, wherein: the specific processing procedure of the image similarity information is as follows:
s11: setting a first pixel from the left bottom of the image as a coordinate origin, setting the horizontal direction as an X axis and the vertical direction as a Y axis, positioning each pixel point in the image, wherein the coordinates of the pixel point are (X, Y);
s12: selecting coordinate axes of pixel points of the first contrast image and the second contrast image in an S11 mode, determining the color of the pixel points by using RGB color numbers, and setting the color numbers as Z, so that each pixel point is [ (X, Y) Z ];
s13: if [ (X)1,Y1)Z1]And [ (X)2,Y2)Z2]If the two images are the same, the color of the first contrast image and the color of the second contrast image at the point (X, Y) are the same, and the similarity between the two points is recorded as 100%;
s14: when the colors of the first contrast image and the second contrast image are different at a certain point (X, Y), comparing the colors around the pixel point, and comparing [ (X, Y) Z ] with 8 surrounding pixel points: { [ (X, Y) Zn ], [ (X +1, Y) Zn ], [ (X-1, Y) Zn ], [ (X, Y +1) Zn ], [ (X, Y-1) Zn ], [ (X +1, Y +1) Zn ], [ (X +1, Y-1) Zn ], [ (X-1, Y +1) Zn ] }, selecting pixel points with the same Zn and Z, marking the similarity of two pixel points corresponding to (X, Y) of the first contrast image and the second contrast image as 50%, and marking the similarity of two pixel points corresponding to (X, Y) of the first contrast image and the second contrast image as 0% if no same pixel points exist;
s15: and after all pixels are compared, taking the average of the similarity of loudness points of all the same coordinate axes of the first contrast image and the second contrast image to position the similarity of the whole image.
4. The system for analyzing the micro-pores of the sandstone reservoir based on geological causes of claim 1, wherein: the specific processing procedure of the sound wave analysis unit is as follows:
s111: the sound wave generation module is used for emitting sound waves of different frequency bands, the sound waves last for 2s in sequence, and the sound wave emission time interval is 3min every two times;
s112: performing a sound wave receiving operation using the first sound wave receiving module and a second sound wave receiving module;
s113: storing the sound waves received by the first sound wave receiving module and the second sound wave receiving module each time by using a sound wave information storage module;
s114: comparing the sound wave signals received by the first sound wave receiving module and the second sound wave receiving module through the sound wave characteristic comparison module;
s115: and finally, analyzing the two groups of sound waves through the sound wave analyzing module, performing deep learning by using the sound wave information characteristic deep learning module, and expanding a database in the sound wave information storage module.
5. The system for analyzing the micro-pores of the sandstone reservoir based on geological causes of claim 1, wherein: the specific treatment process of the pore permeation test unit is as follows:
s1111: shooting and observing the rock stratum through a microscopic module, and selecting a proper sample to perform a pore-permeation experiment;
s1112: carrying out a pore permeation experiment on the sample at the selected position through a pore permeation experiment module;
s1113: recording data by using a data recording module;
s1114: and after the recording is finished, detecting each item of data of the experiment by using the test precision confirmation module.
6. The geologic cause-based sandstone reservoir microscopic pore analysis system of claim 4, wherein: the specific processing procedure of the information repository unit is as follows:
s11111: various information is transmitted into the information recording module, and the data is encrypted through the information encryption module;
s11112: after encryption is finished, transmitting the encrypted data to a storage module for storage, wherein the storage module contains geological cause information and can be called by the sound wave analysis module;
s11113: after the required extraction data is extracted from the storage module, the decryption is carried out through the information decryption module.
7. The system for analyzing the micro-pores of the sandstone reservoir based on geological causes of claim 1, wherein: the image recognition module is in communication connection with the image verification module, the image detail amplification intercepting module is in communication connection with the image recognition module, the image detail amplification intercepting module is in communication connection with the image verification module, the image detail amplification intercepting module is in communication connection with the image analysis processing module, the image information storage module is in communication connection with the image analysis processing module, and the image information storage module is in communication connection with the image detail amplification intercepting module.
8. The system for analyzing the micro-pores of the sandstone reservoir based on geological causes of claim 1, wherein: sound wave generation module and first sound wave receiving module communication connection, sound wave generation module and second sound wave receiving module communication connection, first sound wave receiving module contrasts module communication connection with the sound wave characteristics, second sound wave receiving module contrasts module communication connection with the sound wave characteristics, the sound wave characteristics are compared module and sound wave and are analyzed module communication connection, sound wave is analyzed module and sound wave information characteristics degree of deep learning module communication connection, sound wave is analyzed module and sound wave information storage module communication connection, sound wave information storage module and sound wave information characteristics degree of deep learning module communication connection.
9. The system for analyzing the micro-pores of the sandstone reservoir based on geological causes of claim 1, wherein: the fracture characteristic determination module is in communication connection with the information integration module, the pore throat characteristic determination module is in communication connection with the information integration module, the information integration module is in communication connection with the temporary information storage module, and the temporary information storage module is in communication connection with the information splitting module.
10. The system for analyzing the micro-pores of the sandstone reservoir based on geological causes of claim 1, wherein: the information recording module is in communication connection with the information encryption module, the information encryption module is in communication connection with the storage module, the storage module is in communication connection with the information extraction module, and the information extraction module is in communication connection with the information decryption module.
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