Fluid identification method, system and equipment based on oil-based mud electric imaging and medium

Abstract

The invention provides a fluid identification method, system and equipment based on oil-based mud electric imaging and a medium. The method comprises the following steps: collecting crack data and dynamic image data of oil-based mud electric imaging after full-borehole coverage correction; obtaining coordinates of crack lines in the image based on the crack data and the oil-based mud electric imaging dynamic image data, and obtaining a segmented sub-image data body of the crack based on the coordinates of the suture lines in the image; obtaining a crack feature sub-image based on the segmented sub-image data body of the crack; obtaining the chromaticity of each crack based on the crack feature sub-image; based on the chromaticity of each crack, establishing a fluid identification standard based on the chromaticity of the crack, and obtaining a fluid identification result based on the fluid identification standard; according to the method, the application of oil-based mud electric imaging in reservoir fluid type identification is realized, a new means is provided for oil field logging fluid interpretation, and the coincidence rate and accuracy of oil field logging interpretation are improved.

Description

Technical Field

[0001] This invention belongs to the field of well logging technology in oil and gas exploration, specifically relating to a fluid identification method, system, equipment and medium based on oil-based mud electrical imaging. Background Technology

[0002] Electrical imaging logging data offers high resolution and high wellbore coverage, and is often used for reservoir bedding and fracture evaluation. Based on the applicable mud type, it can be divided into water-based mud electrical imaging and oil-based mud electrical imaging. Since water-based mud electrical imaging directly measures formation conductivity, previous researchers combined it with Archie's formula to construct the apparent formation water resistivity distribution spectrum, effectively guiding fluid identification in carbonate formations. Oil-based mud electrical imaging, on the other hand, uses button electrodes to emit alternating currents of two frequencies to measure reservoir impedance information around the well. After inversion processing, the impedance information is converted into formation resistivity information, resulting in high-resolution static and dynamic images of formation resistivity, as well as images of the electrode-wellbore formation gap. Therefore, the apparent formation water resistivity distribution spectrum method based on water-based mud electrical imaging is not applicable to oil-based mud electrical imaging.

[0003] In practical applications of oil-based mud electrophysiological imaging (EPI), it is assumed that the resistivity image obtained through high-resolution inversion reflects the resistivity of the formation around the well, with bright colors representing high resistivity and dark colors representing low resistivity. However, since oil-based mud itself is a high-resistivity signal, fractures after intruding into the formation generally also appear as bright colors, with dark colors rarely appearing. But with the in-depth application of oil-based mud EPI, interpreters have found that when a large number of dark fractures are observed in oil-based mud EPI, water is often found after formation testing, and when a large number of bright fractures are observed, oil and gas are often found after formation testing. Therefore, this phenomenon can be used to identify fluid types, but existing related technologies lack methods for quantitatively characterizing this phenomenon. Summary of the Invention

[0004] To address the problems existing in the prior art, the present invention provides a fluid identification method, system, device and medium based on oil-based mud electroimaging, in order to solve the technical problem that existing related technologies cannot accurately characterize fluid identification.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A fluid identification method based on oil-based mud electrical imaging includes the following steps:

[0007] Collect fracture data, as well as dynamic image data of oil-based mud electro-imaging after full wellbore coverage correction;

[0008] Based on the fracture data and the dynamic image data of oil-based mud electro-imaging, the coordinates of the fracture line in the image are obtained, and the segmented sub-image data volume of the fracture is obtained based on the coordinates of the fracture line in the image.

[0009] Based on the segmented sub-image data of the crack, a crack feature sub-image is obtained;

[0010] The color intensity of each crack is obtained based on the crack feature sub-image;

[0011] Based on the color intensity of each crack, a fluid identification standard based on crack color intensity is established, and the fluid identification result is obtained based on the fluid identification standard.

[0012] Furthermore, the collected crack data is organized and interpreted, including crack depth, crack apparent height, and crack apparent dip.

[0013] The process of full-bore coverage correction is as follows:

[0014] The raw data of oil-based mud electro-imaging is processed to obtain dynamic data, and the dynamic data is then subjected to full-wellbore coverage correction processing to obtain dynamic image data covering the entire wellbore.

[0015] Furthermore, the coordinates of the crack line in the image are:

[0016] x = i;

[0017]

[0018] In the formula, f dep f is the crack depth. az For the apparent tendency of the crack, f heigth The apparent height of the fracture is denoted as i, and i is the column number of the full-bore coverage electrical imaging image data, i = 1-360;

[0019] Define the window length as L, and extract data within the depth range [yL, y+L] along the crack coordinate y to obtain the segmented sub-image data volume of the crack.

[0020] Furthermore, the process of obtaining the crack feature sub-image based on the segmented sub-image data volume of the crack is as follows:

[0021] Calculate the average value of the data color scale within the segmented sub-image data of the crack.

[0022]

[0023] In the formula, z ij --Color mark value for each data point within the fracture image window; i is the column number of the full borehole coverage electrical imaging image data, i = 1-360; L is the image window length;

[0024] Compare each data point in the image window with the average value. Size, if greater than the average Then assign the value of that depth point to 0; if it is less than the average value... The value of that depth point is then retained; after reprocessing the image window data containing the crack, the crack feature sub-image is obtained.

[0025] Furthermore, the image window is a region in the crack image, and each pixel or data point within the region has a corresponding color scale value;

[0026] The color scale value is used to represent the color or brightness attribute of pixels in the image, and the color scale value is used to characterize the features of cracks within the image window.

[0027] Furthermore, the process of obtaining the color intensity of each crack based on the crack feature sub-image is as follows:

[0028]

[0029] In the formula, F tz numz represents the colorimetric value of each crack; numz represents the number of non-zero values ​​in the crack segmentation sub-image.

[0030] Furthermore, based on the color intensity of each crack and combined with oil test data, a fluid identification standard based on crack color intensity is established.

[0031] A fluid identification system based on oil-based mud electro-imaging, comprising:

[0032] The preprocessing unit is configured as follows:

[0033] Used to collect fracture data, as well as dynamic image data of oil-based mud electro-imaging after full borehole coverage correction;

[0034] The segmented computational units are configured as follows:

[0035] Based on the fracture data and oil-based mud electro-imaging dynamic image data, the coordinates of the fracture line in the image are obtained, and the segmented sub-image data volume of the fracture is obtained based on the coordinates of the fracture line in the image.

[0036] The feature calculation unit is configured as follows:

[0037] Used to obtain a crack feature sub-image based on the segmented sub-image data volume of the crack;

[0038] The colorimetric unit is configured as follows:

[0039] Used to obtain the colorimetric value of each crack based on the crack feature sub-image;

[0040] The output unit is configured as follows:

[0041] This is used to establish a fluid identification standard based on the color intensity of each crack, and to obtain the fluid identification result based on the fluid identification standard.

[0042] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the fluid identification method based on oil-based mud electroimaging.

[0043] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the fluid identification method based on oil-based mud electroimaging.

[0044] Compared with the prior art, the present invention has the following beneficial technical effects:

[0045] This invention provides a fluid identification method, system, device, and medium based on oil-based mud electro-imaging, comprising the following steps: collecting fracture data and dynamic image data of oil-based mud electro-imaging after full wellbore coverage correction; obtaining the coordinates of fracture lines in the image based on the fracture data and the dynamic image data of oil-based mud electro-imaging, and obtaining the segmented sub-image data volume of fractures based on the coordinates of the fracture lines in the image; obtaining fracture feature sub-images based on the segmented sub-image data volumes of fractures; obtaining the colorimetric value of each fracture based on the fracture feature sub-images; establishing a fluid identification standard based on the colorimetric value of each fracture; and obtaining the fluid identification result based on the fluid identification standard. This application addresses the phenomenon observed in production applications where a large number of dark fractures in oil-based mud electro-imaging are used to test for water production, and a large number of bright fractures are used to test for gas production. By defining fracture colorimetric parameters based on the interpreted oil-based mud image data, this invention enables the application of oil-based mud electro-imaging in reservoir fluid type identification. This invention provides a new means for oilfield logging fluid interpretation, improving the accuracy and consistency of oilfield logging interpretation. Attached Figure Description

[0046] Figure 1 A flowchart of a fluid identification method based on oil-based mud electro-imaging according to an embodiment of the present disclosure is shown;

[0047] Figure 2 This invention discloses a colorimetric result image of the bright fracture at 7166-7168m in the X1 well oil-based mud electro-imaging system according to an embodiment of the present disclosure.

[0048] Figure 3 This shows the colorimetric results of the dark fractures at 7180-7182m in the X1 well oil-based mud electro-imaging of an embodiment of this disclosure;

[0049] Figure 4A diagram of a fluid identification system based on oil-based mud electroimaging, according to an embodiment of the present disclosure, is shown. Detailed Implementation

[0050] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0051] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0052] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0053] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection, an electrical connection, or a communication connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0054] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0055] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0056] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0057] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0058] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0059] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0060] Figure 1 A flowchart of a fluid identification method based on oil-based mud electroimaging according to an embodiment of this disclosure is shown, as follows: Figure 1 As shown, it includes the following steps:

[0061] Step S1: Collect fracture data and dynamic image data of oil-based mud electro-imaging after full wellbore coverage correction;

[0062] Preferably, in this embodiment of the disclosure, the collected fracture data is organized and interpreted. The organized and interpreted content of the fracture data includes: fracture depth, fracture apparent height, and fracture apparent dip. Specifically, the fracture depth refers to the logging depth of the fracture in the underground reservoir, which is generally obtained through the interpretation results of electrical imaging logging data. The fracture apparent height refers to the height difference between the peak and trough of the sine wave representing the fracture in the electrical imaging dynamic image. The fracture apparent dip refers to the dip of the fracture as shown in the electrical imaging image, which differs from the actual dip of the fracture.

[0063] The process of full-bore coverage correction is as follows:

[0064] The raw data of oil-based mud electro-imaging is processed to obtain dynamic data, and the dynamic data is then subjected to full-wellbore coverage correction processing to obtain dynamic image data covering the entire wellbore.

[0065] Specifically, the process of processing raw data from oil-based mud electro-imaging to obtain dynamic data is as follows:

[0066] The raw data of oil-based mud electro-imaging consists of wellbore impedance information measured by the instrument's button electrode. After noise removal and depth matching of the raw data, the electrode impedance information is inverted into formation resistivity information. By defining the conversion relationship between resistivity magnitude and color scale, dynamic images are obtained.

[0067] Specifically, such as Figure 2 and Figure 3 As shown, the first image in the figure is dynamic image data of oil-based mud electro-imaging after processing based on Techlog, and the second image is image data of the entire wellbore coverage of oil-based mud electro-imaging after processing based on Techlog.

[0068] Step S2: Based on the crack data and the dynamic image data of oil-based mud electro-imaging, obtain the coordinates of the crack line in the image, and obtain the segmented sub-image data volume of the crack based on the coordinates of the crack line in the image;

[0069] Preferably, in this embodiment of the disclosure, the coordinates of the crack line in the image are:

[0070] x = i;

[0071]

[0072] In the formula, f dep f is the crack depth. az For the apparent tendency of the crack, f heigth The apparent height of the fracture is denoted as i, and i is the column number of the full-bore coverage electrical imaging image data, i = 1-360;

[0073] Define a window length of L, and extract data within the depth range [yL, y+L] along the crack coordinate y to obtain the segmented sub-image data volume of the crack; specifically, in the embodiments of this disclosure, as follows Figure 2 and Figure 3 The third layer is the crack segmentation sub-image, which is said to be the data corresponding to the crack segmentation sub-image, that is, the crack segmentation sub-image data volume.

[0074] Step S3: Obtain the crack feature sub-image based on the segmented sub-image data volume of the crack;

[0075] Preferably, in this embodiment of the disclosure, the process of obtaining the crack feature sub-image based on the segmented sub-image data volume of the crack is as follows:

[0076] Calculate the average value of the data color scale within the segmented sub-image data of the crack.

[0077]

[0078] In the formula, z ij --Includes the color scale value of each data point within the cracked image window;

[0079] Compare each data point in the image window with the average value. Size, if greater than the average Then assign the value of that depth point to 0; if it is less than the average value... The value of that depth point is then retained; after reprocessing the image window data containing the crack, the crack feature sub-image is obtained.

[0080] Specifically, the image window is a region in the crack image, and each pixel or data point in the region has a corresponding color scale value;

[0081] The color scale value is used to represent the color or brightness attribute of pixels in the image, and the color scale value is used to characterize the features of cracks within the image window, such as the width, length, shape, or color of the crack.

[0082] Specifically, the image window can be of any shape and size, but common shapes include rectangles or squares. The choice of window can be based on image features such as edges, corners, textures, or colors, or on a specific application requirement.

[0083] Step S4: Obtain the colorimetric values ​​of each crack based on the crack feature sub-image;

[0084] Preferably, in this embodiment of the disclosure, the process of obtaining the colorimetric value of each crack based on the crack feature sub-image is as follows:

[0085]

[0086] In the formula, F tz For each crack, the crack colorimetric value is denoted by numz; numz represents the number of non-zero values ​​in the crack segmentation sub-image. Specifically, for example... Figure 2 and Figure 3 The fifth image in the middle represents the color intensity of each crack.

[0087] Step S5: Based on the color intensity of each crack, establish a fluid identification standard based on crack color intensity.

[0088] Preferably, in this embodiment of the disclosure, a fluid identification standard based on crack color intensity is established based on the color intensity of each crack and the differences in oil test data;

[0089] Specifically, in some embodiments, the oil testing data corresponding to the imaging logging data includes production data, fluid properties (such as oil, gas, water, etc.), pressure recovery curves, and other information. Certain colorimetric ranges may correspond to specific fluid types, such as high-conductivity fractures being rich in water, while low-conductivity fractures may be rich in oil or gas. Based on statistical analysis and the experience of those skilled in the art, colorimetric thresholds for fluid identification can be determined. These thresholds should be able to distinguish different types of fluids and have a certain degree of stability and reliability.

[0090] Specifically, in the embodiments disclosed herein, such as Figure 2 As shown, the test confirmed that this section is an oil and gas layer, and the color intensity of the cracks is mainly distributed between 88 and 200. Figure 3 Tests confirmed that this section is a gas-bearing water layer, with fracture color values ​​mainly distributed between 40 and 80. Therefore, it was determined that the fracture color value of the gas layer should be greater than 80, while the fracture color value of the water layer should be less than 80. Based on this method and judgment criteria, 10 wells in the Kelasu structural belt of the Tarim Oilfield were processed. Statistical analysis of 14 test layers from these 10 wells revealed that the interpretation conclusions of 12 layers were consistent with the test conclusions, achieving a well logging fluid interpretation consistency rate of 85.7%, effectively supporting the well logging interpretation of this block.

[0091] This embodiment also discloses a fluid identification system 10 based on oil-based mud electrical imaging, such as... Figure 4 As shown, it includes:

[0092] The preprocessing unit is configured as follows:

[0093] Used to collect fracture data, as well as dynamic image data of oil-based mud electro-imaging after full borehole coverage correction;

[0094] The segmented computational units are configured as follows:

[0095] Based on the fracture data and oil-based mud electro-imaging dynamic image data, the coordinates of the fracture line in the image are obtained, and the segmented sub-image data volume of the fracture is obtained based on the coordinates of the fracture line in the image.

[0096] The feature calculation unit is configured as follows:

[0097] Used to obtain a crack feature sub-image based on the segmented sub-image data volume of the crack;

[0098] The colorimetric unit is configured as follows:

[0099] Used to obtain the colorimetric value of each crack based on the crack feature sub-image;

[0100] The output unit is configured as follows:

[0101] This is used to establish a fluid identification standard based on the color intensity of each crack, and to obtain the fluid identification result based on the fluid identification standard.

[0102] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used for the operation of a fluid identification method based on oil-based mud electro-imaging.

[0103] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the fluid identification method based on oil-based mud electroimaging in the above embodiments.

[0104] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0105] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0106] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0107] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0108] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0109] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that can be understood by those skilled in the art. The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A fluid identification method based on oil-based mud electrical imaging, characterized in that, Includes the following steps: Collect fracture data, as well as dynamic image data of oil-based mud electro-imaging after full wellbore coverage correction; Based on the fracture data and the dynamic image data of oil-based mud electro-imaging, the coordinates of the fracture line in the image are obtained, and the segmented sub-image data volume of the fracture is obtained based on the coordinates of the fracture line in the image. Based on the segmented sub-image data of the crack, a crack feature sub-image is obtained; The color intensity of each crack is obtained based on the crack feature sub-image; Based on the color intensity of each crack, a fluid identification standard based on crack color intensity is established, and the fluid identification result is obtained based on the fluid identification standard.

2. The fluid identification method based on oil-based mud electro-imaging according to claim 1, characterized in that, The collected crack data is organized and interpreted, including crack depth, crack apparent height, and crack apparent dip. The process of full-bore coverage correction is as follows: The raw data of oil-based mud electro-imaging is processed to obtain dynamic data, and the dynamic data is then subjected to full-wellbore coverage correction processing to obtain dynamic image data covering the entire wellbore.

3. The fluid identification method based on oil-based mud electro-imaging according to claim 1, characterized in that, The coordinates of the crack line in the image are: x = i; In the formula, f dep f is the crack depth. az For the apparent tendency of the crack, f heigth The apparent height of the fracture is denoted as i, and i is the column number of the full-bore coverage electrical imaging image data, i = 1-360; Define the window length as L, and extract data within the depth range [yL, y+L] along the crack coordinate y to obtain the segmented sub-image data volume of the crack.

4. The fluid identification method based on oil-based mud electro-imaging according to claim 1, characterized in that, The process of obtaining the crack feature sub-image based on the segmented sub-image data volume of the crack is as follows: Calculate the average value of the data color scale within the segmented sub-image data of the crack. In the formula, z ij represents the color code value for each data point within the fractured image window; i is the column number of the full-bore coverage electrical imaging image data, i = 1-360; L is the image window length; Compare each data point in the image window with the average value. Size, if greater than the average Then assign the value of that depth point to 0; if it is less than the average value... The value of that depth point is then retained; after reprocessing the image window data containing the crack, the crack feature sub-image is obtained.

5. The fluid identification method based on oil-based mud electroimaging according to claim 4, characterized in that, The image window is a region in the crack image, and each pixel or data point within the region has a corresponding color scale value; The color scale value is used to represent the color or brightness attribute of pixels in the image, and the color scale value is used to characterize the features of cracks within the image window.

6. The fluid identification method based on oil-based mud electro-imaging according to claim 1, characterized in that, The process of obtaining the colorimetric values ​​of each crack based on the crack feature sub-image is as follows: In the formula, F tz The colorimetric value of each crack; numz is the number of non-zero values ​​in the crack segmentation sub-image; z ij is the color code value for each data point within the fractured image window; i is the column number of the full-bore coverage electrical imaging image data, i = 1-360; L is the image window length.

7. The fluid identification method based on oil-based mud electro-imaging according to claim 1, characterized in that, Based on the color intensity of each crack and combined with oil test data, a fluid identification standard based on crack color intensity is established.

8. A fluid identification system based on oil-based mud electro-imaging, characterized in that, The fluid identification method based on oil-based mud electro-imaging according to any one of claims 1-7 includes: The preprocessing unit is configured as follows: Used to collect fracture data, as well as dynamic image data of oil-based mud electro-imaging after full borehole coverage correction; The segmented computational units are configured as follows: Based on the fracture data and oil-based mud electro-imaging dynamic image data, the coordinates of the fracture line in the image are obtained, and the segmented sub-image data volume of the fracture is obtained based on the coordinates of the fracture line in the image. The feature calculation unit is configured as follows: Used to obtain a crack feature sub-image based on the segmented sub-image data volume of the crack; The colorimetric unit is configured as follows: Used to obtain the colorimetric value of each crack based on the crack feature sub-image; The output unit is configured as follows: This is used to establish a fluid identification standard based on the color intensity of each crack.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the fluid identification method based on oil-based mud electro-imaging as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the fluid identification method based on oil-based mud electro-imaging as described in any one of claims 1 to 7.

Images