Electric imaging logging reservoir space identification method and system based on longest communication path

Abstract

The invention relates to the technical field of logging data processing, and particularly discloses an electric imaging logging reservoir space identification method and system based on a longest communication path, and the method comprises the steps: converting an electric imaging logging image of a target region into a binary image, calculating the transverse longest communication path length and the vertical longest communication path length of each pixel point in the binary image; determining a middle-low angle crack image of the target area based on all the transverse longest connected path lengths, and determining a high angle crack image of the target area based on all the vertical longest connected path lengths; and determining a corrosion hole image of the target area according to the binary image, the medium-low angle crack image and the high angle crack image. According to the method, the separation of the crack image and the corrosion hole image of the electric imaging image can be realized, the original form of the crack image and the corrosion hole image is maintained to the greatest extent, the distribution of the reservoir space is well described, and a basis can be provided for the fine evaluation of the reservoir pore structure.

Description

Technical Field

[0001] This invention relates to the field of well logging data processing technology, and in particular to a method and system for identifying reservoir space in electrical imaging well logging based on the longest connected path. Background Technology

[0002] Fractures and dissolution pores are the main reservoir spaces and seepage channels in carbonate reservoirs, but their heterogeneous and complex distribution affects the accurate evaluation of these reservoirs. Electro-imaging logging, with its high resolution and intuitive imagery, is widely used in the quantitative evaluation of carbonate reservoirs. Currently, commonly used electro-imaging processing software, such as Schlumberger's GeoFrame, Atlas Copco's eXpress, and CNPC Logging Co., Ltd.'s LEAD, mostly rely on human-computer interaction to pick up fractures and dissolution pores, resulting in low automation and the recognition and processing results being influenced by human factors. Existing image segmentation algorithms still cannot achieve adaptive automatic identification and extraction of fracture and dissolution pore morphologies, especially for irregular fracture surfaces and pores, thus failing to provide accurate quantitative reservoir characterization parameters. Selecting appropriate image recognition methods to segment fractures and dissolution pores from complex geological image backgrounds has become a hot topic and a challenge in quantitative reservoir evaluation.

[0003] Therefore, there is an urgent need to provide a technical solution to address the above problems. Summary of the Invention

[0004] To address the challenges of complex reservoir spaces, diverse pore structures, and difficulties in identifying pores, cavities, and fractures in carbonate reservoirs, this invention provides a method and system for reservoir space identification based on the longest connectivity path in electrical imaging logging.

[0005] In a first aspect, the present invention provides a method for identifying reservoir space in electrical imaging logging based on the longest connected path, the technical solution of which is as follows:

[0006] The electrical imaging logging image of the target area is converted into a binary image, and the length of the longest horizontal connected path and the length of the longest vertical connected path of each pixel in the binary image are calculated.

[0007] Based on all the longest horizontal connected path lengths, the low-to-medium angle crack images of the target region are determined, and based on all the longest vertical connected path lengths, the high-angle crack images of the target region are determined.

[0008] Based on the binary image, the low-to-medium angle crack image, and the high-angle crack image, the dissolution cavity image of the target area is determined; wherein, the low-to-medium angle crack image, the high-angle crack image, and the dissolution cavity image together characterize the storage space identification result of the target area.

[0009] The beneficial effects of the present invention's method for reservoir space identification based on the longest connected path in electrical imaging logging are as follows:

[0010] The method of this invention can separate crack and dissolution cavity images from electro-imaging images while preserving their original morphology to the greatest extent, thus providing a good description of the distribution of reservoir space and a basis for fine evaluation of reservoir pore structure.

[0011] Based on the above scheme, the method for identifying reservoir space in electrical imaging logging based on the longest connected path of the present invention can be further improved as follows.

[0012] In one alternative approach, the step of converting the electrical imaging logging image of the target area into a binary image includes:

[0013] The image value of each pixel in the electrical imaging logging image of the target area is obtained, and the binary pixel value of each pixel is determined according to the relationship between the image value threshold and the image value of each pixel.

[0014] The binary image of the target region is obtained based on the binary pixel value of each pixel.

[0015] In one alternative approach, the step of calculating the length of the longest horizontally connected path and the length of the longest vertically connected path for any pixel in the binary image includes:

[0016] Based on the binary pixel value of any pixel in the binary image, calculate the length of the left connected path, the length of the right connected path, the length of the upward connected path, and the length of the downward connected path for any pixel.

[0017] The longest horizontal connected path length of any pixel is obtained by summing the lengths of its left and right connected paths, and the longest vertical connected path length of any pixel is obtained by summing the lengths of its upward and downward connected paths.

[0018] In one alternative approach, the steps of determining low-to-medium angle crack images of the target region based on all the longest lateral connected path lengths, and determining high-angle crack images of the target region based on all the longest vertical connected path lengths, include:

[0019] Among all the longest horizontal connected paths, the longest horizontal connected path length that is greater than a first threshold is determined as the target longest horizontal connected path length, and the low-to-medium angle crack image of the target region is determined based on all the target longest horizontal connected path lengths.

[0020] Among all the longest vertical connected paths, the longest vertical connected path length greater than the second threshold is determined as the target longest vertical connected path length, and the high-angle crack image of the target region is determined based on all the target longest vertical connected path lengths.

[0021] In one alternative approach, the step of determining the dissolution cavity image of the target region based on the binary image, the low-to-medium angle crack image, and the high-angle crack image includes:

[0022] Based on the residual between the binary image, the low-to-medium angle crack image, and the high-angle crack image, the image of the dissolution cavity in the target area is determined.

[0023] Secondly, the present invention provides an electrical imaging logging reservoir space identification system based on the longest connected path, the technical solution of which is as follows:

[0024] It includes: a first processing module, a second processing module, and a recognition module;

[0025] The first processing module is used to: convert the electrical imaging logging image of the target area into a binary image, and calculate the length of the longest horizontal connected path and the length of the longest vertical connected path for each pixel in the binary image;

[0026] The second processing module is used to: determine the low-to-medium angle crack images of the target area based on all the longest horizontal connected path lengths, and determine the high-angle crack images of the target area based on all the longest vertical connected path lengths;

[0027] The identification module is used to: determine the dissolution cavity image of the target area based on the binary image, the low-to-medium angle crack image, and the high-angle crack image; wherein the low-to-medium angle crack image, the high-angle crack image, and the dissolution cavity image together characterize the storage space identification result of the target area.

[0028] The beneficial effects of the electrical imaging logging reservoir space identification system based on the longest connected path of the present invention are as follows:

[0029] The system of this invention can separate crack and dissolution pore images from electro-imaging images and preserve their original morphology to the greatest extent, thus describing the distribution of reservoir space well and providing a basis for fine evaluation of reservoir pore structure.

[0030] Based on the above scheme, the present invention provides an electrical imaging logging reservoir space identification system based on the longest connected path, which can be further improved as follows.

[0031] In one alternative approach, the step of converting the electrical imaging logging image of the target area into a binary image in the first processing module includes:

[0032] The image value of each pixel in the electrical imaging logging image of the target area is obtained, and the binary pixel value of each pixel is determined according to the relationship between the image value threshold and the image value of each pixel.

[0033] The binary image of the target region is obtained based on the binary pixel value of each pixel.

[0034] In one alternative approach, the step of calculating the length of the longest horizontally connected path and the length of the longest vertically connected path for any pixel in the binary image in the first processing module includes:

[0035] Based on the binary pixel value of any pixel in the binary image, calculate the length of the left connected path, the length of the right connected path, the length of the upward connected path, and the length of the downward connected path for any pixel.

[0036] The longest horizontal connected path length of any pixel is obtained by summing the lengths of its left and right connected paths, and the longest vertical connected path length of any pixel is obtained by summing the lengths of its upward and downward connected paths.

[0037] Thirdly, the technical solution of an electronic device according to the present invention is as follows:

[0038] It includes a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of the longest connected path-based electrical imaging logging reservoir space identification method of the present invention.

[0039] Fourthly, the technical solution of a computer-readable storage medium provided by the present invention is as follows:

[0040] The computer-readable storage medium stores instructions that, when read, cause the computer-readable storage medium to perform the steps of the longest connected path-based electrical imaging logging reservoir space identification method of the present invention.

[0041] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0042] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0043] Figure 1 This is a flowchart illustrating an embodiment of the method for identifying reservoir space in electrical imaging logging based on the longest connected path according to the present invention.

[0044] Figure 2 A schematic diagram of the reservoir space identification results from electrical imaging logging of fractured-vuggy carbonate reservoirs;

[0045] Figure 3 This is a schematic diagram of an embodiment of an electrical imaging logging reservoir space identification system based on the longest connected path according to the present invention;

[0046] Figure 4 This is a schematic diagram of an embodiment of an electronic device according to the present invention. Detailed Implementation

[0047] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0048] Figure 1 This diagram illustrates a flowchart of an embodiment of an electro-imaging logging reservoir space identification method based on the longest connected path provided by the present invention. This method can be executed by electronic devices such as terminal devices or servers. The terminal device can be any fixed or mobile terminal, such as user equipment (UE), mobile device, user terminal, terminal, cellular phone, cordless phone, personal digital assistant (PDA), handheld device, computing device, vehicle-mounted device, or wearable device. The server can be a single server or a server cluster consisting of multiple servers. Any electronic device can implement the electro-imaging logging reservoir space identification method based on the longest connected path by having its processor call computer-readable instructions stored in its memory. Figure 1 As shown, it includes the following steps:

[0049] S1. Convert the electrical imaging logging image of the target area into a binary image, and calculate the longest horizontal and longest vertical connected path length for each pixel in the binary image.

[0050] In S1, specifically:

[0051] 1) The steps of converting electrical imaging logging images of the target area into binary images include:

[0052] The image value of each pixel in the electrical imaging logging image of the target area is obtained, and the binary pixel value of each pixel is determined according to the relationship between the image value threshold and the image value of each pixel.

[0053] The binary image of the target region is obtained based on the binary pixel value of each pixel.

[0054] Wherein, the size of the electrical imaging logging image is M×N, and the coordinates of any pixel are (x, y, y). i ,y j ), i=1,2,…,M, j=1,2,…,N, (x i ,y j The corresponding image value (pixel value 0-255) is E(x). i ,y j The image value threshold is set to k by default. The binary pixel value of each pixel is determined according to the relationship between the image value threshold and the image value of any given pixel, using the following formula, until the binary pixel value of each pixel is determined:

[0055] Wherein, B(x) i ,y j ) represents a pixel (x) i ,y j The binary pixel value is either 1 or 0.

[0056] 2) The step of calculating the length of the longest horizontally connected path and the length of the longest vertically connected path for any pixel in the binary image includes:

[0057] Based on the binary pixel value of any pixel in the binary image, calculate the lengths of the left-side connected path, right-side connected path, upward connected path, and downward connected path for each pixel. Specifically:

[0058] ① Calculate the length l of the left-connected path to any pixel. l (x i ,y j (excluding the pixel itself):

[0059] When B(x) i ,y j ) = 1, l l (x i ,y j ) = max(l l (x i+1 ,yj-1 ),l l (x i+1 ,y j ),l l (x i+1 ,y j+1 ))

[0060] When B(x) i ,y j When ) = 0, l l (x i ,y j ) = 0.

[0061] ② Calculate the length l of the rightward connected path for any pixel. r (x i ,y j (Including the pixel itself):

[0062] When B(x) i ,y j ) = 1, l r (x i ,y j )=1+max(l r (x i-1 ,y j-1 ),l r (x i-1 ,y j ),l r (x i-1 ,y j+1 ))

[0063] When B(x) i ,y j When ) = 0, l r (x i ,y j ) = 0.

[0064] ③ Calculate the length l of the upward connected path for any pixel. u (x i ,y j (excluding the pixel itself):

[0065] When B(x) i ,y j ) = 1, l u (x i ,y j ) = max(l u (x i-1 ,y j+1 ),l u (x i ,y j+1 ),l u (xi+1 ,y j+1 ))

[0066] When B(x) i ,y j When ) = 0, l u (x i ,y j ) = 0.

[0067] ④ Calculate the length l of the downward connected path for any pixel. d (x i ,y j (Including the pixel itself):

[0068] When B(x) i ,y j ) = 1, l d (x i ,y j )=1+max(l d (x i-1 ,y j-1 ),l d (x i-1 ,y j-1 ),l d (x i-1 ,y j-1 ))

[0069] When B(x) i ,y j When ) = 0, l d (x i ,y j ) = 0.

[0070] The longest horizontal connected path length of any pixel is obtained by summing the lengths of its left and right connected paths, and the longest vertical connected path length of any pixel is obtained by summing the lengths of its upward and downward connected paths.

[0071] Wherein, the length l of the longest horizontal connected path at any pixel is calculated. h (x i ,y j The formula for ) is: l h (x i ,y j )=l l (x i ,y j )+l r (x i ,y j Calculate the length l of the longest vertical connected path at any pixel. v (xi ,y j The formula for ) is: l v (x i ,y j )=l u (x i ,y j )+l d (x i ,y j ).

[0072] It should be noted that the length of the longest horizontal connected path and the length of the longest vertical connected path for each pixel are calculated in the same way.

[0073] S2. Based on the lengths of all the longest horizontal connected paths, determine the low-to-medium angle crack images of the target region, and based on the lengths of all the longest vertical connected paths, determine the high-angle crack images of the target region. Specifically, in S2:

[0074] 1) Among all the longest horizontally connected path lengths, the longest horizontally connected path lengths greater than the first threshold L are determined as the target longest horizontally connected path lengths, and the low-to-medium angle crack image F of the target region is determined based on all the target longest horizontally connected path lengths. h .

[0075] Among them, F h (x i ,y j )={(x i ,y j )|l h (x i ,y j )>L},F h (x i ,y j ) represents a low-to-medium angle crack image F h Pixels in (x) i ,y j The value of ) is used to represent the crack image at medium and low angles. h By all F h (x i ,y j )composition.

[0076] 2) Among all the longest vertical connected path lengths, the longest vertical connected path lengths greater than the second threshold H are determined as the target longest vertical connected path lengths, and the high-angle crack image F of the target region is determined based on all the target longest vertical connected path lengths. v .

[0077] Among them, F v (xi ,y j )={(x i ,y j )|l v (x i ,y j )>H},F v (x i ,y j ) represents a high-angle crack image F v Pixels in (x) i ,y j The value of ) is used to determine the high-angle crack image F. v By all F v (x i ,y j )composition.

[0078] It should be noted that low- to medium-angle crack images of the target region can be determined by searching for the maximum lateral connected paths in the ranges of -45°, 0°, and -45° around each pixel, while high-angle crack images of the target region can be determined by searching for the maximum longitudinal connected paths in the ranges of 45°, 90°, and 135° around each pixel.

[0079] S3. Based on the binary image, the low-to-medium angle crack image, and the high-angle crack image, determine the dissolution cavity image of the target area.

[0080] Among them, images of low-to-medium angle cracks, high-angle cracks, and dissolution cavities collectively characterize the reservoir space identification results of the target area. Specifically, in S3:

[0081] Based on the residual between the binary image, the low-to-medium angle crack image, and the high-angle crack image, the image of the dissolution cavity in the target area is determined.

[0082] Wherein, according to the formula: C(x) i ,y j )=B(x i ,y j )-F h (x i ,y j )-F v (x i ,y j The pixel points (x) in the image of the dissolution cavity were calculated. i ,y j The values ​​of C(x) are all possible values ​​of C(x). i ,y j (This is a diagram of dissolved cavities.)

[0083] Figure 2The results of electrical imaging logging for reservoir space identification in carbonate fractured-vuggy reservoirs using the technical solution of this embodiment are presented. Figure 2 a) is the result of the electrical imaging interpretation. Figure 2 b) is the digital core sample at 64.82m. Figure 2 c) is a thin section of the casting at 64.82m. Crack images were automatically acquired respectively. Figure 2 (a) The 4th column from left to right in the image and the image of dissolution cavities ( Figure 2 In column a) from left to right, the image segmentation result preserves the original morphology of the reservoir space structure. Simultaneously, the reservoir space structure parameters of this segment, including fracture orientation, were automatically calculated. Figure 2 (a) The 6th column from left to right) and cracks, pores, and porosity ( Figure 2 (Column 7 from left to right in a). Through comparison with digital cores... Figure 2 b) and cast sheet Figure 2 c) A comparison showed that the well section did indeed exhibit cracks and dissolution cavities, which verified the reliability of the maximum connectivity path identification results.

[0084] The technical solution of this embodiment can separate the crack and dissolution cavity images in the electro-imaging image and maintain their original morphology to the greatest extent, which can well describe the distribution of reservoir space and provide a basis for fine evaluation of reservoir pore structure.

[0085] Figure 3 A schematic diagram of an embodiment of an electrical imaging logging reservoir space identification system 200 based on the longest connected path provided by the present invention is shown. Figure 3 As shown, the system 200 includes: a first processing module 210, a second processing module 220, and an identification module 230;

[0086] The first processing module 210 is used to: convert the electrical imaging logging image of the target area into a binary image, and calculate the length of the longest horizontal connected path and the length of the longest vertical connected path for each pixel in the binary image;

[0087] The second processing module 220 is used to: determine the low-to-medium angle crack image of the target area based on all the longest horizontal connected path lengths, and determine the high-angle crack image of the target area based on all the longest vertical connected path lengths;

[0088] The identification module 230 is used to: determine the dissolution cavity image of the target area based on the binary image, the low-to-medium angle crack image, and the high-angle crack image; wherein the low-to-medium angle crack image, the high-angle crack image, and the dissolution cavity image together characterize the storage space identification result of the target area.

[0089] In one alternative approach, the step of converting the electrical imaging logging image of the target area into a binary image in the first processing module 210 includes:

[0090] The image value of each pixel in the electrical imaging logging image of the target area is obtained, and the binary pixel value of each pixel is determined according to the relationship between the image value threshold and the image value of each pixel.

[0091] The binary image of the target region is obtained based on the binary pixel value of each pixel.

[0092] In one alternative approach, the step of calculating the length of the longest horizontal connected path and the length of the longest vertical connected path for any pixel in the binary image in the first processing module 210 includes:

[0093] Based on the binary pixel value of any pixel in the binary image, calculate the length of the left connected path, the length of the right connected path, the length of the upward connected path, and the length of the downward connected path for any pixel.

[0094] The longest horizontal connected path length of any pixel is obtained by summing the lengths of its left and right connected paths, and the longest vertical connected path length of any pixel is obtained by summing the lengths of its upward and downward connected paths.

[0095] In one alternative embodiment, the second processing module 220 is specifically used for:

[0096] Among all the longest horizontal connected paths, the longest horizontal connected path length that is greater than a first threshold is determined as the target longest horizontal connected path length, and the low-to-medium angle crack image of the target region is determined based on all the target longest horizontal connected path lengths.

[0097] Among all the longest vertical connected path lengths, the longest horizontal connected path length that is greater than the second threshold is determined as the target longest vertical connected path length, and the high-angle crack image of the target region is determined based on all the target longest vertical connected path lengths.

[0098] In an alternative embodiment, the identification module 230 is specifically used for:

[0099] Based on the residual between the binary image, the low-to-medium angle crack image, and the high-angle crack image, the image of the dissolution cavity in the target area is determined.

[0100] The technical solution of this embodiment can separate the crack and dissolution cavity images in the electro-imaging image and maintain their original morphology to the greatest extent, which can well describe the distribution of reservoir space and provide a basis for fine evaluation of reservoir pore structure.

[0101] The parameters and steps for implementing the corresponding functions of each module in the longest connected path-based electrical imaging logging reservoir space identification system 200 of this embodiment can be referred to the parameters and steps in the embodiments of the longest connected path-based electrical imaging logging reservoir space identification method above, and will not be repeated here.

[0102] like Figure 4 As shown, an electronic device 300 according to an embodiment of the present invention includes a processor 320 coupled to a memory 310. The memory 310 stores at least one computer program 330, which is loaded and executed by the processor 320 to enable the electronic device 300 to implement any of the above-mentioned methods for identifying reservoir space based on the longest connected path in electrical imaging logging. Specifically:

[0103] The electronic device 300 can vary considerably due to differences in configuration or performance. It may include one or more processors 320 (Central Processing Units, CPUs) and one or more memories 310. The memories 310 store at least one computer program 330, which is loaded and executed by the processors 320 to enable the electronic device 300 to implement any of the longest connectivity path-based reservoir space identification methods provided in the above embodiments. Of course, the electronic device 300 may also have wired or wireless network interfaces, a keyboard, and input / output interfaces for input / output. It may also include other components for implementing device functions, which will not be elaborated upon here.

[0104] An embodiment of the present invention provides a computer-readable storage medium storing at least one computer program, which is loaded and executed by a processor to enable a computer to implement any of the above-mentioned methods for identifying reservoir space based on the longest connected path in electrical imaging logging.

[0105] Alternatively, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, a floppy disk, and an optical data storage device, etc.

[0106] In an exemplary embodiment, a computer program product or computer program is also provided, which includes computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the electronic device to perform any of the above-described methods for identifying reservoir space based on the longest connected path in electrical imaging logging.

[0107] It should be noted that the terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and represent a limitation on a specific order or sequence. Where appropriate, the order of use for similar objects can be interchanged so that the embodiments of this application described herein can be implemented in an order other than that shown or described.

[0108] Those skilled in the art will recognize that this invention can be implemented as a system, method, or computer program product. Therefore, this disclosure can be specifically implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, this invention can also be implemented as a computer program product in one or more computer-readable media containing computer-readable program code.

[0109] Any combination of one or more computer-readable media can be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0110] 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. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A longest connected path based electrical imaging well log reservoir space identification method, characterized in that, The method comprises the following steps: Converting an electrical imaging logging image of a target area into a binary image, and calculating a horizontal longest connected path length and a vertical longest connected path length of each pixel point in the binary image; Determining a medium-low angle fracture image of the target area based on all the horizontal longest connected path lengths, and determining a high angle fracture image of the target area based on all the vertical longest connected path lengths; Determining a dissolution pore image of the target area according to the binary image, the medium-low angle fracture image and the high angle fracture image; wherein the medium-low angle fracture image, the high angle fracture image and the dissolution pore image jointly represent a reservoir space identification result of the target area.

2. The longest connected path based electrical imaging well log reservoir space identification method of claim 1, wherein, The step of converting the electrical imaging logging image of the target area into a binary image comprises: Obtaining an image value of each pixel point in the electrical imaging logging image of the target area, and respectively determining a binary pixel value of each pixel point according to a size relationship between an image value threshold and the image value of each pixel point; Obtaining the binary image of the target area according to the binary pixel value of each pixel point.

3. The longest connected path based electrical imaging well log reservoir space identification method of claim 2, wherein, The step of calculating the horizontal longest connected path length and the vertical longest connected path length of any pixel point in the binary image comprises: Respectively calculating a left connected path length, a right connected path length, an upward connected path length and a downward connected path length of the any pixel point based on the binary pixel value of the any pixel point in the binary image; Obtaining the horizontal longest connected path length of the any pixel point according to a sum of the left connected path length and the right connected path length of the any pixel point, and obtaining the vertical longest connected path length of the any pixel point according to a sum of the upward connected path length and the downward connected path length of the any pixel point.

4. The longest connected path based electrical imaging well log reservoir space identification method of claim 1, wherein, The step of determining the medium-low angle fracture image of the target area based on all the horizontal longest connected path lengths, and determining the high angle fracture image of the target area based on all the vertical longest connected path lengths comprises: In all the horizontal longest connected path lengths, determining a horizontal longest connected path length greater than a first threshold value as a target horizontal longest connected path length, and determining the medium-low angle fracture image of the target area according to all the target horizontal longest connected path lengths; In all the vertical longest connected path lengths, determining a vertical longest connected path length greater than a second threshold value as a target vertical longest connected path length, and determining the high angle fracture image of the target area according to all the target vertical longest connected path lengths.

5. The longest connected path based electrical imaging well log reservoir space identification method according to any one of claims 1 to 4, characterized in that, The step of determining the dissolution pore image of the target area according to the binary image, the medium-low angle fracture image and the high angle fracture image comprises: Determining the dissolution pore image of the target area based on a residual error between the binary image, the medium-low angle fracture image and the high angle fracture image.

6. A longest connected path based electrical imaging well log reservoir space identification system, characterized by, The method comprises the following steps: A first processing module, a second processing module and an identification module; The first processing module is configured to convert an electrical imaging logging image of a target region into a binary image, and calculate a horizontal longest connected path length and a vertical longest connected path length of each pixel point in the binary image; The second processing module is configured to determine a low-to-medium angle fracture image of the target region based on all the horizontal longest connected path lengths, and determine a high angle fracture image of the target region based on all the vertical longest connected path lengths; The identification module is configured to determine a dissolution pore image of the target region according to the binary image, the low-to-medium angle fracture image and the high angle fracture image; wherein the low-to-medium angle fracture image, the high angle fracture image and the dissolution pore image jointly represent a reservoir space identification result of the target region.

7. The longest connected path based electrical imaging well log reservoir space identification system of claim 6, wherein, The step of converting the electrical imaging logging image of the target region into a binary image in the first processing module comprises: obtaining an image value of each pixel point in the electrical imaging logging image of the target region, and determining a binary pixel value of each pixel point according to a size relationship between an image value threshold and the image value of each pixel point, respectively; obtaining the binary image of the target region according to the binary pixel value of each pixel point.

8. The longest connected path based electrical imaging well log reservoir space identification system of claim 7, wherein, The step of calculating the horizontal longest connected path length and the vertical longest connected path length of any pixel point in the binary image in the first processing module comprises: calculating a left connected path length, a right connected path length, an upward connected path length and a downward connected path length of the any pixel point in the binary image based on a binary pixel value of the any pixel point, respectively; obtaining the horizontal longest connected path length of the any pixel point according to a sum of the left connected path length and the right connected path length of the any pixel point, and obtaining the vertical longest connected path length of the any pixel point according to a sum of the upward connected path length and the downward connected path length of the any pixel point.

9. An electronic device, comprising: The electronic device comprises a processor coupled with a memory, and the memory stores at least one computer program, which is loaded and executed by the processor, so that the electronic device implements the electrical imaging logging reservoir space identification method based on the longest connected path according to any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores at least one computer program, which is loaded and executed by the processor, so that the computer readable storage medium implements the electrical imaging logging reservoir space identification method based on the longest connected path according to any one of claims 1 to 5.

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