Methods, systems, and computer-readable storage media for extracting parameters of slits in electro-imaging.

Abstract

This invention discloses a method, system, and computer-readable storage medium for extracting fracture and cavity parameters from electrical imaging. The method includes: acquiring a full-borehole coverage image from electrical imaging logging; performing initial segmentation on the full-borehole coverage image to obtain initial segmentation fracture and cavity sub-images of the full-borehole conductivity image; extracting target shape parameters from the initial segmentation fracture and cavity sub-images of the full-borehole conductivity image; performing secondary segmentation on the initial segmentation fracture and cavity sub-images of the full-borehole conductivity image based on the target shape parameters of the initial segmentation fracture and cavity sub-images of the full-borehole conductivity image to obtain fracture and cavity sub-images; and extracting electrical imaging fracture and cavity parameters based on the fracture and cavity sub-images. The solution provided by this application can clearly and completely obtain the extracted electrical imaging fracture and cavity parameters and improve the accuracy of the extracted electrical imaging fracture and cavity parameters.

Description

Technical Field

[0001] This application relates to well logging technology, and in particular to a method, system, and computer-readable storage medium for extracting fracture-cavity parameters from electrical imaging. Background Technology

[0002] Carbonate fractured-vuggy reservoirs are characterized by low matrix porosity and well-developed secondary reservoir spaces such as fractures and dissolution pores. For these fractured-vuggy carbonate reservoirs, the development and combination of fractures and dissolution pores are the main factors controlling their effectiveness. Therefore, extracting fracture and dissolution pore information from reservoir logging data is crucial for evaluating the effectiveness of these reservoirs—that is, whether they can produce industrial oil flows or whether they can produce industrial oil flows after reservoir stimulation. Electro-imaging logging measures the electrical conductivity curves of the formation near the wellbore using multi-button electrodes. After preprocessing, combined with accompanying wellbore deviation, diameter, and azimuth measurements, the conductivity curves are visually represented in image form. Due to the intrusion of conductive mud into fractures and dissolution pores, the conductivity at fractures and dissolution pores differs from that of the matrix rock. Therefore, information on fractures and dissolution pores can be extracted from electro-imaging logging images to evaluate the effectiveness of carbonate fractured-vuggy reservoirs.

[0003] In related technologies, the extraction of fracture and cavity parameters in electrical imaging is based on wavelet transform modulus maxima image segmentation technology. Specifically, taking the conductivity curve of a button cell electrode as the object, the influence of formation background noise caused by uneven wellbore is first eliminated. Then, the wavelet transform modulus maxima image segmentation method is used to obtain sub-images containing fractures and dissolution cavities. Fracture and cavity parameter information is then extracted from the sub-images.

[0004] However, the existing methods for extracting fracture and cavity parameters from electro-imaging logging tools have the following problems: 1. The button electrode plates of the electro-imaging logging tool do not fully cover the wellbore, resulting in blank bands between the plates and a lack of measurement information. Due to these blank bands, the processing of electro-imaging data is not clear and complete, affecting the accuracy of the extracted fracture and cavity parameters. 2. In addition to fractures and dissolution cavities, the high-conductivity targets segmented from the image also contain invalid information such as horizontal high-conductivity mud layers, suture lines, and induced fractures. These techniques treat all segmented high-conductivity targets as fractures and dissolution cavities, thus including this invalid information in the extracted electro-imaging fracture and cavity parameters. Summary of the Invention

[0005] This application provides a method, system, and computer-readable storage medium for extracting electrical imaging suture parameters, which can be used to obtain complete results of electrical imaging suture parameter extraction and improve the accuracy of the results.

[0006] On one hand, embodiments of this application provide a method for extracting fracture and cavity parameters from electrical imaging. This method includes: acquiring a full-bore coverage image from electrical imaging logging; performing initial segmentation on the full-bore coverage image to obtain initial segmentation fracture and cavity sub-images of the full-bore conductivity image; extracting target shape parameters from the initial segmentation fracture and cavity sub-images of the full-bore conductivity image; performing secondary segmentation on the initial segmentation fracture and cavity sub-images of the full-bore conductivity image based on the target shape parameters of the initial segmentation fracture and cavity sub-images of the full-bore conductivity image to obtain fracture and cavity sub-images; and extracting electrical imaging fracture and cavity parameters based on the fracture and cavity images.

[0007] Optionally, acquiring a full-bore coverage image from an electrical imaging logging system includes: acquiring full-bore conductivity data from an electrical imaging logging system; and acquiring a full-bore coverage image from an electrical imaging logging system based on the full-bore conductivity data from the electrical imaging logging system.

[0008] Optionally, acquiring whole-wellbore conductivity data from electrical imaging logging includes: inputting raw conductivity data; drawing a raw electrical imaging conductivity image based on the raw conductivity data; and acquiring whole-wellbore conductivity data from electrical imaging logging by applying a gap-filling method between electrical imaging electrodes based on the raw electrical imaging conductivity image.

[0009] Optionally, the full-bore coverage image of the electrical imaging logging is initially segmented to obtain the initial segmentation of the full-bore conductivity image, including: obtaining the initial segmentation of the full-bore conductivity image of the fracture and cavity in the area where an image frame is located based on the full-bore coverage image of the electrical imaging logging; moving the image frame to obtain the initial segmentation of the full-bore conductivity image of the fracture and cavity in other areas; and outputting the initial segmentation of the full-bore conductivity image of the fracture and cavity based on the initial segmentation of the full-bore conductivity image of the area where an image frame is located and the initial segmentation of the full-bore conductivity image of the fracture and cavity in other areas.

[0010] Optionally, based on the full-bore coverage image of the electrical imaging logging, an initial segmentation image of the full-bore conductivity image of an image frame is obtained, including: inputting the full-bore coverage image data of the electrical imaging logging of an image frame; performing a two-dimensional binary wavelet transform on the full-bore coverage image data of the electrical imaging logging of an image frame, calculating the modulus of the wavelet transform coefficients of each conductivity data point for the second-order wavelet transform, obtaining the modulus of the second-order wavelet transform coefficients; based on the modulus of the second-order wavelet transform coefficients, obtaining the modulus maxima points in the depth direction using three-point peak finding; and based on the modulus maxima points, performing initial image segmentation to obtain the full-bore conductivity image segmentation image of the image frame.

[0011] Optionally, the target shape parameters of the initial segmentation of the fracture-cavity image in the whole-wellbore conductivity image are extracted, including: based on the initial segmentation of the fracture-cavity image in the whole-wellbore conductivity image, the angle parameters of the high-conductivity target are extracted as the target shape parameters of the initial segmentation of the fracture-cavity image in the whole-wellbore conductivity image.

[0012] Optionally, based on the target shape parameters of the initial segmentation of the fracture and cavity images in the full-bore conductivity image, a secondary segmentation is performed on the initial segmentation of the fracture and cavity images in the full-bore conductivity image to obtain fracture and cavity images. This includes: removing invalid targets with target shape parameters less than an effective threshold from the initial segmentation of the fracture and cavity images in the full-bore conductivity image to obtain fracture and cavity images.

[0013] Optionally, based on the crack and hole sub-images, electro-imaging crack and hole parameters are extracted, including: extracting electro-imaging crack and hole parameters for the region where an image frame is located based on the crack and hole sub-images; moving the image frame to extract electro-imaging crack and hole parameters for other regions.

[0014] On one hand, embodiments of this application provide a system for extracting fracture and cavity parameters from electrical imaging. This system includes: a full-bore coverage image generation module for acquiring a full-bore coverage image from electrical imaging logging; a preliminary segmentation module for performing preliminary segmentation on the full-bore coverage image from electrical imaging logging to acquire preliminary segmented fracture and cavity sub-images of the full-bore conductivity image; a target shape parameter extraction module for extracting target shape parameters from the preliminary segmented fracture and cavity sub-images of the full-bore conductivity image; a secondary segmentation module for performing secondary segmentation on the preliminary segmented fracture and cavity sub-images of the full-bore conductivity image based on the target shape parameters of the preliminary segmented fracture and cavity sub-images to acquire fracture and cavity sub-images; and a fracture and cavity parameter extraction module for extracting electrical imaging fracture and cavity parameters based on the fracture and cavity sub-images.

[0015] This application also provides a computer-readable storage medium having at least one program instruction or code, which, when loaded and executed by a processor, enables the computer to implement the method for extracting electro-imaging slit parameters as described above.

[0016] The technical solution provided in this application includes at least the following beneficial effects: 1. Image segmentation is performed using a complete two-dimensional method (full-wellbore electrical conductivity data), and secondary segmentation is performed based on the target shape parameters, resulting in clearer and more complete images of fractures and cavities. 2. The segmented high-conductivity targets eliminate invalid information such as horizontal high-conductivity mud layers, suture lines, and induced fractures, making the extraction results of fracture and cavity parameters from electrical imaging more accurate. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a method for extracting suture parameters in electro-imaging according to an embodiment of the present invention;

[0019] Figure 2 These are the original electrical imaging conductivity image and the full wellbore coverage image obtained by an electrical imaging fracture and cavity parameter extraction method provided in this embodiment of the invention.

[0020] Figure 3 These are the original electrical imaging conductivity image, the electrical imaging logging full-bore coverage image, and the initial segmentation of the full-bore conductivity image into fracture sub-images obtained by an electrical imaging fracture parameter extraction method provided in this embodiment of the invention.

[0021] Figure 4 This is a schematic diagram of the target shape parameters extracted by an electro-imaging slit parameter extraction method provided in an embodiment of the present invention;

[0022] Figure 5 The original electrical imaging conductivity image, the electrical imaging logging full-bore coverage image, the initial segmentation of the full-bore conductivity image, and the fracture and pore images are obtained by an electrical imaging fracture and pore parameter extraction method provided in this embodiment of the invention.

[0023] Figure 6 The results of extracting electrical imaging fracture and cavity parameters are obtained from the full-wellbore coverage image, the initial segmentation of the full-wellbore conductivity image, the fracture and cavity images, and the extraction of electrical imaging fracture and cavity parameters by the electrical imaging fracture and cavity parameter extraction method provided in the embodiments of the present invention.

[0024] Figure 7 This is a comparison between the extracted electrical imaging fracture and cavity parameters obtained by the electrical imaging fracture and cavity parameter extraction method provided in this embodiment of the invention and conventional well logging data;

[0025] Figure 8 This is a comparison between the extraction results of electro-imaging slit parameters obtained by the electro-imaging slit parameter extraction method provided in this embodiment of the invention and the extraction results of slit parameters obtained by related technologies;

[0026] Figure 9 This is a flowchart of an electro-imaging slit parameter extraction method provided in an embodiment of the present invention implemented in the Techlog environment;

[0027] Figure 10 This is a schematic diagram of an electro-imaging slit parameter extraction system provided in an embodiment of the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0029] Please refer to Figure 1 The diagram illustrates a flowchart of an embodiment of an electro-imaging slit parameter extraction method provided in this application. The method includes the following steps:

[0030] Step 101: Obtain full-bore coverage images from electrical imaging logging.

[0031] In related technologies, the button electrode plates of electrical imaging logging tools do not provide 100% coverage of the wellbore, resulting in blank zones between the plates and a lack of measurement information. Due to these blank zones, electrical imaging data segmented along the north-facing section of the wellbore cannot be processed in a complete two-dimensional manner. Therefore, this application's embodiment first acquires a full-wellbore coverage image from the electrical imaging logging tool.

[0032] Acquiring full-bore coverage images from electrical imaging logging includes, but is not limited to, the following sub-steps:

[0033] 1011. Obtain the electrical conductivity data of the entire wellbore from the electrical imaging logging.

[0034] Acquire whole-wellbore electrical conductivity data from electrical imaging logging, including but not limited to the following sub-steps:

[0035] 1011-① Input the raw conductivity data.

[0036] The input raw conductivity data is the electrode conductivity data after shallow resistivity calibration. Since the button electrode system of the electrical imaging logging tool is a non-focused electrode system, the measured value only varies proportionally with the conductivity of the geological body near the wellbore. Therefore, shallow resistivity calibration is used to obtain the electrode conductivity data after shallow resistivity calibration.

[0037] 1011-② Based on the original conductivity data, draw the original electrical imaging conductivity image.

[0038] Based on the original conductivity data, and according to the orientation of the conductivity curve of the button electrode in the middle of the reference plate, the wellbore is cut along due north, and an electrical imaging conductivity image is drawn.

[0039] A reference electrode is an electrode that provides azimuth reference for other electrodes during the logging process. Optionally, the reference electrode can be electrode number 1, which is the electrode numbered 1 in the electrical imaging logging instrument. During the logging process, the azimuth of electrode number 1, i.e., the azimuth of the midpoint of electrode number 1 relative to true north, is measured and recorded, and this azimuth of electrode number 1 provides azimuth reference for other electrodes. In the plotting process of this field, the azimuth of other electrodes relative to true north is usually determined based on the azimuth of electrode number 1. When plotting the conductivity image of the electrical imaging logging based on the azimuth of the conductivity curve of the button electrode in the middle of electrode number 1, it is necessary to cut along the true north direction of the wellbore for plotting.

[0040] Optionally, different electrical imaging logging tools may use different reference plates with different middle button electrodes. For example, the Extended Range Micro-resistivity Imager (XRMI) uses plate 1 as the reference plate, and the 13th button electrode of plate 1 in XRMI is the middle button electrode; the Formation MicroScanner Imager (FMI) uses plate 1 as the reference plate, and the 12th button electrode of plate 1 in FMI is the middle button electrode.

[0041] 1011-③ Based on the original electrical imaging conductivity image, the method of filling the gaps between electrical imaging electrodes is applied to obtain the whole-wellbore conductivity data of electrical imaging logging.

[0042] Optionally, the method of filling the gaps between the electro-imaging electrodes refers to generating gap data between the electrodes of the electro-imaging logging tool by applying the method of growing from the edge of the electrode towards the center of the gap based on the original electro-imaging conductivity image, thereby obtaining conductivity data covering the entire wellbore of the electro-imaging logging tool, i.e., the conductivity data of the entire wellbore of the electro-imaging logging tool.

[0043] 1012. Based on the full-bore conductivity data of electrical imaging logging, obtain the full-bore coverage image of electrical imaging logging.

[0044] In one possible implementation method, based on the full-bore conductivity data of electrical imaging logging, the azimuth of each electrode relative to due north is calculated using the reference electrode azimuth data, and a conductivity image of the full-bore coverage after the blank zone between the electrodes is filled is drawn, which is the full-bore coverage image of electrical imaging logging.

[0045] Please refer to Figure 2 This illustration shows the original electrical imaging conductivity image and the full-bore coverage image obtained by an electrical imaging fracture parameter extraction method according to an embodiment of the present invention. In one possible implementation, based on the orientation of the conductivity curve of the button electrode in the middle of the No. 1 electrode plate of the FMI electrical imaging logging tool, the wellbore is cut along due north, and the following image is drawn: Figure 2 The conductivity image shown is a cross-section taken along the due north side of the wellbore, i.e., the original electrical imaging conductivity image.

[0046] Optionally, based on the whole-wellbore conductivity data from the electrical imaging logging, the azimuth of each electrode relative to true north is calculated using the azimuth data of electrode 1 of the FMI electrical imaging logging tool, and the following plot is obtained: Figure 2 The image shown is a full-bore conductivity image, i.e., a full-bore coverage image of electrical imaging logging.

[0047] in, Figure 2The first track is the conductivity image cut along the due north side of the wellbore, i.e., the original electrical imaging conductivity image; the second track is the depth track, representing the logging depth; the third track is the conductivity image covering the entire wellbore, i.e., the electrical imaging logging full-wellbore coverage image. Figure 2 In the diagram, P1AZ indicates the orientation of electrode 1, deg represents degrees (in degrees), Heated indicates the header, FMI_256 represents the conductivity image cut along the north side of the wellbore (i.e., the original electrical imaging conductivity image), FMI_FILL_LIU3_032_256 represents the full-bore coverage image of the electrical imaging logging, and MD represents the measurement depth.

[0048] Step 102: Perform initial segmentation on the full-bore coverage image of the electrical imaging logging to obtain the initial segmentation of the fractured cavity image of the full-bore conductivity image.

[0049] The initial segmentation of the full-bore coverage image from electrical imaging logging is performed to obtain the initial segmentation of the fracture and cavity sub-images of the full-bore conductivity image, including but not limited to the following sub-steps:

[0050] 1021. Based on the full-bore coverage image of electrical imaging logging, obtain the initial segmentation of the fracture cavity image of the full-bore conductivity image of the area where an image frame is located.

[0051] Here, an image frame corresponds to the sampling interval of conventional logging data, and the area enclosed by an image frame refers to the region covered by the image frame in the full-bore coverage image of the electrical imaging logging. This embodiment first processes the full-bore coverage image of the electrical imaging logging within the area of ​​an image frame.

[0052] Optionally, based on the full-bore coverage image of the electrical imaging logging, the initial segmentation of the fracture-cavity sub-image of the area where an image frame is located is obtained, including but not limited to the following sub-steps:

[0053] 1021-① Input a full-bore coverage image data of an electrical imaging logging frame.

[0054] 1021-② Perform a two-dimensional binary wavelet transform on the full-bore coverage image data of an electrical imaging logging image frame. For wavelet transform of order 2, calculate the modulus of the wavelet transform coefficients for each conductivity data point to obtain the modulus of the second-order wavelet transform coefficients.

[0055] In one example, the conductivity data in a full-bore coverage image of an electrical imaging logging frame is set as follows:

[0056]

[0057] Perform a second wavelet transform to obtain the wavelet coefficients corresponding to the conductivity data:

[0058]

[0059] Where j is the wavelet transform order, and the wavelet coefficients of the second-order wavelet transform of the conductivity data are taken:

[0060]

[0061] Calculate the magnitudes of the second-order wavelet transform coefficients:

[0062]

[0063] 1021-③ Based on the modulus of the second-order wavelet transform coefficients, the three-point peak finding method is used to obtain the modulus maxima in the depth direction.

[0064] The three-point peak finding method is a method for finding maximum points. It uses three points on the curve along the depth direction to fit a quadratic polynomial, and then finds the maximum point of the quadratic polynomial and its corresponding coordinates. This point is the modulus maximum point.

[0065] 1021-④ Based on the modulus maxima, obtain the coordinate pixel value of the modulus maxima, determine the segmentation threshold according to the coordinate pixel value of the modulus maxima, perform initial image segmentation, and obtain the whole wellbore conductivity image segmentation of the image frame area.

[0066] The modulus maxima are the points where the conductivity values ​​in the whole-bore conductivity image change abruptly, i.e., the segmentation points. Optionally, a segmentation threshold is determined based on the location of the segmentation points, and optionally, initial image segmentation is performed based on the segmentation threshold.

[0067] 1022. Move the image frame to obtain the full borehole conductivity image of other areas and the initial segmentation of the fracture hole image.

[0068] In one possible implementation, moving the image frame to obtain the initial segmentation of fracture and cavity sub-images of the whole-well conductivity image for other areas includes: moving the image frame and repeating the above sub-step 1021 until the logging endpoint depth is reached, thereby obtaining the initial segmentation of fracture and cavity sub-images of the whole-well conductivity image for other areas. The logging endpoint depth is obtained from the image.

[0069] 1023. Based on the initial segmentation of the full-bore conductivity image of the region containing an image frame and the initial segmentation of the fracture-cavity image of the full-bore conductivity image of other regions, output the initial segmentation of the full-bore conductivity image of the fracture-cavity image.

[0070] Please refer to Figure 3 This illustration shows the original electrical imaging conductivity image, the electrical imaging logging full-wellbore coverage image, and the initial segmentation of the full-wellbore conductivity image into fracture sub-images obtained by an electrical imaging fracture parameter extraction method according to an embodiment of the present invention. In this embodiment, the electrical imaging logging tool is an FMI logging tool, and the reference electrode is electrode number 1.

[0071] in, Figure 3 The first track is the conductivity image cut along the due north of the wellbore, i.e., the original electrical imaging conductivity image; the second and fourth tracks are depth tracks, representing the logging depth; the third track is the conductivity image covering the entire wellbore, i.e., the electrical imaging logging image covering the entire wellbore; the fifth track is the initial segmentation result of the two-dimensional binary wavelet transform image, i.e., the initial segmentation of the fractured cavity image of the entire wellbore conductivity image. Figure 3 In the diagram, P1AZ indicates the azimuth of electrode 1, deg represents degrees (in degrees), Heated indicates the header, FMI_256 represents the conductivity image cut along the due north direction of the wellbore, FMI_FILL_LIU3_032_256 represents the full-wellbore coverage image of electrical imaging logging, MD represents the measurement depth, and FMI_FILL_LIU3_032_256_SEG_FMI_V represents the initial segmentation of the fracture-cavity image using two-dimensional binary wavelet transform, i.e., the initial segmentation of the full-wellbore conductivity image.

[0072] Step 103: Extract the target shape parameters of the initial segmentation of the fracture hole image from the whole wellbore conductivity image.

[0073] In one possible implementation, extracting the target shape parameters of the initial segmentation fracture-cavity image of the whole-wellbore conductivity image includes: extracting the angle parameters of high-conductivity targets based on the initial segmentation fracture-cavity image of the whole-wellbore conductivity image, and using the angle parameters of high-conductivity targets as the target shape parameters of the initial segmentation fracture-cavity image of the whole-wellbore conductivity image.

[0074] In the two-dimensional conductivity image covering the entire wellbore, the angles of non-effective high-conductivity targets such as horizontal high-conductivity mud layers and sutures differ from those of fractures and pores. To distinguish non-effective high-conductivity targets from fractures and pores using the initial segmentation target shape parameters, the initially segmented fracture and pore sub-images are further processed to extract the angle parameters of the high-conductivity targets.

[0075] Please refer to Figure 4 The diagram illustrates the target shape parameters extracted by an electro-imaging slit parameter extraction method according to an embodiment of the present invention.

[0076] In one possible implementation, extracting the target shape parameters of the initial segmentation of the fracture-cavity image from the full-bore conductivity image includes: extracting the angle parameters of the high-conductivity target based on the initial segmentation of the fracture-cavity image from the full-bore conductivity image.

[0077] Optionally, the angular parameter of a high-conductivity target is defined as the angle between the major axis of the high-conductivity target (i.e., the line connecting the two points with the greatest distance on the target edge) and the horizontal direction. Further, optionally, the angular parameter is defined according to the following formula:

[0078]

[0079] Wherein, the horizontal direction is the x-axis, the long axis of the high conductivity target is the y-axis, (x2, y2) is the end point of the long axis of the high conductivity target, and (x1, y1) is the starting point of the long axis of the high conductivity target.

[0080] Step 104: Based on the target shape parameters of the initial segmentation of the fracture and cavity images in the full-bore conductivity image, perform secondary segmentation of the initial segmentation of the fracture and cavity images in the full-bore conductivity image to obtain fracture and cavity images.

[0081] In one possible implementation, based on the target shape parameters of the initial segmentation of the fracture and cavity image of the whole-wellbore conductivity image, a secondary segmentation of the initial segmentation of the fracture and cavity image of the whole-wellbore conductivity image is performed to obtain fracture and cavity images. This includes: removing invalid targets with target shape parameters less than an effective threshold from the initial segmentation of the fracture and cavity image of the whole-wellbore conductivity image to obtain fracture and cavity images.

[0082] In vertical wells, the angular parameters of ineffective targets such as horizontal or low-dipping high-conductivity mudstone laminae and suture lines are very small. For example, 10° is used as the effective threshold for the target shape parameter. Further, high-conductivity targets with a shape parameter less than 10° (i.e., an angular parameter less than 10°) are considered ineffective targets. The initial segmentation of the whole-wellbore conductivity image into fracture and void images is then performed as a secondary segmentation to remove ineffective targets, resulting in fracture and void images. The effective threshold can be set based on experience, and this embodiment does not limit its application.

[0083] Please refer to Figure 5 This illustration shows the original electrical imaging conductivity image, the full-bore coverage image of the electrical imaging logging, the initial segmentation of the full-bore conductivity image into fracture and cavity sub-images, and images of fractures and pores obtained by an electrical imaging fracture and cavity parameter extraction method according to an embodiment of the present invention. The electrical imaging logging tool in this embodiment is an FMI logging tool, and the reference electrode is electrode number 1.

[0084] in, Figure 5 The first track is the conductivity image cut along the due north direction of the wellbore, i.e., the original electrical imaging conductivity image; the second, fourth, and sixth tracks are depth tracks, representing the logging depth; the third track is the conductivity image covering the entire wellbore, i.e., the electrical imaging logging full-wellbore coverage image; the fifth track is the initial segmentation result of the two-dimensional binary wavelet transform image, i.e., the initial segmentation of the fracture and pore sub-image of the full-wellbore conductivity image; the seventh track is the secondary segmentation result based on the target shape parameters, i.e., the fracture and pore sub-image. It can be seen that the initial segmentation of the fracture and pore sub-image of the full-wellbore conductivity image includes both fractures and dissolution pores, as well as horizontal high-conductivity textures; the secondary image segmentation sub-image based on the target shape parameters, i.e., the fracture and pore sub-image, removes the horizontal high-conductivity textures and only includes fractures and dissolution pores. Figure 5In the diagram, P1AZ indicates the orientation of electrode 1, deg represents degrees (in degrees), Heated indicates the header, FMI_256 represents the conductivity image cut along the due north direction of the wellbore, FMI_FILL_LIU3_032_256 represents the full-wellbore coverage image of electrical imaging logging, MD represents the measurement depth, FMI_FILL_LIU3_032_256_SEG_FMI_V represents the initial segmentation of the fracture and cavity sub-image based on the two-dimensional binary wavelet transform, i.e., the initial segmentation of the full-wellbore conductivity image, and FMI_FILL_LIU3_032_256_SEG_FMI_V_SD represents the secondary segmentation sub-image based on the target shape parameters, i.e., the fracture and cavity sub-image.

[0085] Step 105: Extract electro-imaging crack and hole parameters based on crack and hole sub-images.

[0086] In one possible implementation, extracting electro-imaging crack and hole parameters based on crack and hole sub-images includes: for crack and hole sub-images segmented in two steps, extracting electro-imaging crack and hole parameters for the region where an image frame is located based on single-target parameter calculation; moving the image frame to extract electro-imaging crack and hole parameters for other regions.

[0087] Optionally, the electrical imaging fracture-vuggy parameters include, but are not limited to: the average roundness of multiple targets within the image frame, the average length of multiple targets within the image frame, the average width of multiple targets within the image frame, the porosity-fracture porosity within the image frame, and the fracture porosity within the image frame. Further optionally, the above-mentioned electrical imaging fracture-vuggy parameters are used to characterize the quality of fractured reservoirs.

[0088] The technical solution provided in this application includes at least the following beneficial effects: 1. Image segmentation is performed using a complete two-dimensional method (full-wellbore electrical conductivity data), and secondary segmentation is performed based on the target shape parameters, resulting in clearer and more complete images of fractures and cavities. 2. The segmented high-conductivity targets eliminate invalid information such as horizontal high-conductivity mud layers, suture lines, and induced fractures, making the extraction results of fracture and cavity parameters from electrical imaging more accurate.

[0089] Please refer to Figure 6 This illustration shows the results of extracting electrical imaging fracture and void parameters from a full-wellbore coverage image, a preliminary segmentation image of the full-wellbore conductivity image, fracture and void images, and the extraction of electrical imaging fracture and void parameters, obtained using an electrical imaging fracture and void parameter extraction method provided in an embodiment of the present invention. The electrical imaging logging tool in this embodiment is an FMI logging tool, and the reference electrode is electrode number 1.

[0090] in, Figure 6The first channel is the conductivity image covering the entire wellbore, i.e., the full-wellbore coverage image of electrical imaging logging; the second, fourth, and sixth channels are depth channels, representing the logging depth; the third channel is the initial segmentation result of the two-dimensional binary wavelet transform image, i.e., the initial segmentation of the fracture and vulcanization sub-image of the full-wellbore conductivity image; the seventh and eighth channels are the extraction results of electrical imaging fracture and vulcanization parameters. Further, in the seventh and eighth channels, the code APHIT represents the fracture and vulcanization porosity, VVPHIT represents the dissolution porosity, FFPHIT represents the fracture porosity, and XPHIT represents the production index of the fracture and vulcanization flow model. The code P1AZ indicates the azimuth of the first electrode plate, deg represents degrees (in degrees), Heated indicates the header, FMI_FILL_LIU3_032_256 represents the full-bore coverage image of electrical imaging logging, MD represents the measurement depth, FMI_FILL_LIU3_032_256_SEG_FMI_V represents the initial segmentation of the fracture and cavity sub-image using two-dimensional binary wavelet transform, i.e., the initial segmentation of the fracture and cavity sub-image of the full-bore conductivity image, and FMI_FILL_LIU3_032_256_SEG_FMI_V_SD represents the secondary segmentation sub-image based on the target shape parameters, i.e., the fracture and cavity sub-image.

[0091] Please refer to Figure 7 This illustration shows a comparison between the extracted fracture and cavity parameters obtained by an electrical imaging fracture and cavity parameter extraction method according to an embodiment of the present invention and conventional logging data. The electrical imaging logging tool in this embodiment is an FMI logging tool, and the reference electrode is electrode number 1.

[0092] in, Figure 7The first track is the lithology curve segment, where GR (gamma ray) is the natural gamma ray curve, KTH (kalium+thorium) is the uranium-removed natural gamma ray curve, and CAL (caliper) is the caliper curve; the second track is the depth track; the third track is the resistivity curve track, where RT is the deep lateral resistivity logging curve and RXO is the shallow lateral resistivity logging curve; the fourth track is the porosity curve track, where AC (acoustic time) is the acoustic transit time curve, DEN (density) is the density curve, and CNL (compensated neutron log) is the neutron porosity curve; the fifth track is the calculated porosity curve; the sixth track is the depth track; the seventh track is the full borehole coverage image of the electrical imaging logging; the eighth track is the initial segmentation of the fracture and cavity sub-image of the full borehole conductivity image; the ninth track is the fracture and cavity sub-image; and the tenth track is the result of the extraction of fracture and cavity parameters from the electrical imaging logging, where APHIT is the fracture and cavity porosity, VVPHIT is the dissolution cavity porosity, and FFPHIT is the fracture porosity. The code P1AZ indicates the azimuth of electrode 1, deg indicates degrees (unit of angle), Heated indicates header, FMI_FILL_LIU3_032_256 indicates the full-bore coverage image of electrical imaging logging, FMI_FILL_LIU3_032_256_SEG_FMI_V indicates the initial segmentation of the fracture and pore sub-image based on the two-dimensional binary wavelet transform, i.e., the initial segmentation of the full-bore conductivity image of fracture and pore, FMI_FILL_LIU3_032_256_SEG_FMI_V_SD indicates the secondary segmentation sub-image based on the target shape parameters, i.e., the fracture and pore sub-image, reference indicates depth, gAPI indicates the unit of natural gamma logging value, IN indicates inches, OHMM indicates ohm-meter (unit of resistivity), us / ft indicates microseconds per foot (unit of sonic transit time), and v / v indicates volume / volume (unit of neutron porosity logging).

[0093] According to the electrical imaging logging data, dissolution fractures and cavities are well-developed in the 7064.4 to 7069.5 meter well section, indicating good permeability. During drilling, mud intruded into the dissolution fractures and cavities, resulting in a decrease in the measured lateral resistivity curve values. Furthermore, the development of dissolution cavities and fractures is also reflected in the porosity logging curves. At locations with developed dissolution fractures and cavities, the density curve (DEN) value decreases, the sonic curve (AC) value increases, and the neutron porosity (CNL) curve value slightly increases, corresponding to an increase in the calculated porosity value (PIGE_QEPP). The extraction results of the electrical imaging fracture and cavity parameters obtained in this embodiment of the invention correspond to conventional lateral resistivity and porosity curves. The images of the secondary segmented fractures and dissolution cavities in the well section from 7064.4 to 7069.5 meters show segmented fractures and dissolution cavities. The extracted fractures and cavities have high porosity and show a good inverse correlation with the dual lateral curves and a good positive correlation with the porosity curve.

[0094] Please refer to Figure 8 This illustration shows a comparison between the extracted fracture parameters obtained by an electrical imaging fracture parameter extraction method according to an embodiment of the present invention and the extracted fracture parameters obtained by related technologies. In this embodiment, the electrical imaging logging tool is an FMI logging tool, and the reference electrode is electrode number 1.

[0095] in, Figure 8 The second channel is a static image of electrical conductivity, the fourth channel is the result of extracting electrical imaging slot parameters obtained through related techniques, and the sixth channel is the result of extracting electrical imaging slot parameters obtained in this embodiment of the invention. Compared with related techniques, the slot sub-images segmented in this embodiment of the invention are clearer and more complete, and do not contain non-effective targets such as horizontal high-conductivity textures. Figure 8 In the image, ARRAY_WBI_SCALE2 represents the conductivity image after shallow resistivity scaling, i.e., the static conductivity image of electrical imaging; ARRAY_ABI_SEG represents the result of extracting the electrical imaging crack and hole parameters obtained from related technology processing; imageorientation represents the image orientation; the code P1AZ represents the orientation of the first electrode; deg represents degrees, which is the unit of angle; Heated represents the image header; FMI_FILL_LIU3_032_256_SEG_FMI_V_SD represents the secondary segmented sub-image based on the target shape parameters, i.e., the crack and hole sub-image; and reference represents the depth.

[0096] Please refer to Figure 9 The diagram illustrates a flowchart of an embodiment of the present invention for extracting slit parameters in an electro-imaging slit in the Schlumberger Techlog environment. The method includes the following steps:

[0097] Step 901: Load the data in the Techlog software.

[0098] Optionally, logging data includes conventional data and electrical imaging logging data.

[0099] Step 902: Based on the loaded data, preprocess it using Techlog software.

[0100] Optionally, the electrical imaging logging data can be preprocessed using the electrical imaging logging data preprocessing workflow in the Techlog software.

[0101] Step 903: Based on the preprocessed data, use Techlog software to acquire full-bore coverage images of electrical imaging logging.

[0102] Based on the preprocessed data, the Techlog software is used to acquire full-bore coverage images of electrical imaging logging, including but not limited to the following sub-steps:

[0103] 9031. Based on the preprocessed data, use Techlog software to obtain whole-wellbore electrical conductivity data from electrical imaging logging.

[0104] Based on the preprocessed data, Techlog software was used to acquire whole-wellbore conductivity data from electrical imaging logging, including but not limited to the following sub-steps:

[0105] 9031-① Obtain raw conductivity data from the preprocessed data using Techlog software.

[0106] The raw conductivity data is the electrode conductivity data after shallow resistivity calibration. Since the button electrode system of the electrical imaging logging tool is a non-focused electrode system, the measured value only varies proportionally with the conductivity of the geological body near the wellbore. Therefore, shallow resistivity calibration is used to obtain the electrode conductivity data after shallow resistivity calibration.

[0107] 9031-② Based on the raw conductivity data, the raw electrical imaging conductivity image was plotted using Techlog software.

[0108] Based on the original conductivity data, and according to the orientation of the conductivity curve of the button electrode in the middle of the reference plate, the wellbore is cut open along due north, and an electrical imaging conductivity image is drawn using Techlog software.

[0109] Optionally, different instruments may use different reference plates with different middle button electrodes. For example, the XRMI electro-imaging logging tool uses plate 1 as the reference plate, and the 13th button electrode of plate 1 in the XRMI is the middle button electrode; the FMI electro-imaging logging tool uses plate 1 as the reference plate, and the 12th button electrode of plate 1 in the FMI is the middle button electrode.

[0110] 9031-③ Based on the original electrical imaging conductivity image, the method of filling the gap between electrical imaging electrodes was applied to obtain the whole-wellbore conductivity data of electrical imaging logging in Techlog software.

[0111] Optionally, the method of filling the gaps between the electro-imaging electrodes refers to generating gap data between the electrodes of the electro-imaging logging tool by applying the method of growing from the edge of the electrode towards the center of the gap based on the original electro-imaging conductivity image, thereby obtaining conductivity data covering the entire wellbore of the electro-imaging logging tool, i.e., the conductivity data of the entire wellbore of the electro-imaging logging tool.

[0112] 9032. Based on the full-bore conductivity data from electrical imaging logging, use Techlog software to obtain full-bore coverage images from electrical imaging logging.

[0113] Based on the full-bore conductivity data from the electrical imaging logging, the azimuth of each electrode relative to due north was calculated using the azimuth data of electrode 1. The conductivity image of the full-bore coverage after the blank zone between the electrodes was filled was then plotted in Techlog software, which is the full-bore coverage image of the electrical imaging logging.

[0114] Step 904: Use Techlog software to perform initial segmentation of the full-bore coverage image of the electrical imaging logging to obtain the initial segmentation of the fractured cavity image of the full-bore conductivity image.

[0115] The Techlog software is used to perform initial segmentation of the full-bore coverage image of the electrical imaging logging to obtain the initial segmentation of the fracture and cavity sub-images of the full-bore conductivity image. This includes, but is not limited to, the following sub-steps:

[0116] 9041. Based on the full-bore coverage image of electrical imaging logging, use Techlog software to obtain the initial segmentation of the fracture cavity image of the full-bore conductivity image of the area where an image frame is located.

[0117] Optionally, based on the full-bore coverage image of the electrical imaging logging, the Techlog software is used to obtain the full-bore conductivity image of the area where an image frame is located, and the initial segmentation of the fracture-cavity sub-image includes, but is not limited to, the following sub-steps:

[0118] 9041-① Input the full-bore coverage image data of an electrical imaging logging frame into the Techlog software;

[0119] 9041-② Use Techlog software to perform a two-dimensional binary wavelet transform on the full-bore coverage image data of an electrical imaging logging frame. For wavelet transform of order 2, calculate the modulus of the wavelet transform coefficients for each conductivity data point to obtain the modulus of the second-order wavelet transform coefficients.

[0120] In one example, the conductivity data in a full-bore coverage image of an electrical imaging logging frame is set as follows:

[0121]

[0122] Perform a second wavelet transform to obtain the wavelet coefficients corresponding to the conductivity data:

[0123]

[0124] Where j is the wavelet transform order, and the wavelet coefficients of the second-order wavelet transform of the conductivity data are taken:

[0125]

[0126] Calculate the magnitudes of the second-order wavelet transform coefficients:

[0127]

[0128] 9041-③ Based on the modulus of the second-order wavelet transform coefficients, the Techlog software is used to obtain the modulus maxima in the depth direction by using three-point peak finding.

[0129] 9041-④ Based on the modulus maxima, the coordinate pixel values ​​of the modulus maxima are obtained using Techlog software. The segmentation threshold is determined based on the coordinate pixel values ​​of the modulus maxima to perform initial image segmentation, thereby obtaining the full borehole conductivity image segmentation of the region where the image frame is located.

[0130] The modulus maxima, i.e., the points where the conductivity values ​​of the whole-bore conductivity image change abruptly, are further, the segmentation points. Optionally, a segmentation threshold is determined based on the location of the segmentation points, and even more optionally, initial image segmentation is performed based on the segmentation threshold.

[0131] 9042. Move the image frame and use Techlog software to obtain the full borehole conductivity image of other areas and the initial segmentation of the fracture hole image.

[0132] Optionally, moving the image frame and obtaining the initial segmentation of fracture and cavity sub-images of the whole-well conductivity image for other areas using Techlog software includes: moving the image frame and repeating the above sub-step 9041 in the Techlog software until the logging endpoint depth is reached, thereby obtaining the initial segmentation of fracture and cavity sub-images of the whole-well conductivity image for other areas. The logging endpoint depth is obtained from the image.

[0133] 9043. Based on the initial segmentation of the full-wellbore conductivity image of the region containing an image frame and the initial segmentation of the fracture-cavity image of the full-wellbore conductivity image of other regions, output the initial segmentation of the full-wellbore conductivity image of the fracture-cavity image in the Techlog software.

[0134] Step 905: Use Techlog software to extract the target shape parameters of the initial segmentation fracture hole image from the whole borehole conductivity image.

[0135] Optionally, the target shape parameters of the initial segmentation of the fracture-cavity image in the whole-wellbore conductivity image are extracted using Techlog software, including: based on the initial segmentation of the fracture-cavity image in the whole-wellbore conductivity image, the angle parameters of the high-conductivity target are extracted using Techlog software, and the angle parameters of the high-conductivity target are used as the target shape parameters of the initial segmentation of the fracture-cavity image in the whole-wellbore conductivity image.

[0136] In the two-dimensional conductivity image covering the entire wellbore, the angles of non-effective high-conductivity targets such as horizontal high-conductivity mud layers and sutures differ from those of fractures and pores. To distinguish non-effective high-conductivity targets from fractures and pores using the initial segmentation target shape parameters, the initially segmented fracture and pore sub-images are further processed to extract the angle parameters of the high-conductivity targets.

[0137] Alternatively, the angular parameter of a high-conductivity target is defined as the angle between the major axis of the high-conductivity target (the line connecting the two points with the greatest distance on the target edge) and the horizontal direction. Alternatively, the angular parameter is defined according to the following formula:

[0138]

[0139] Wherein, the horizontal direction is the x-axis, the long axis of the high conductivity target is the y-axis, (x2, y2) is the end point of the long axis of the high conductivity target, and (x1, y1) is the starting point of the long axis of the high conductivity target.

[0140] Step 906: Based on the target shape parameters of the initial segmentation of the fracture and cavity images from the full-bore conductivity image, the Techlog software is used to perform secondary segmentation of the initial segmentation of the fracture and cavity images from the full-bore conductivity image to obtain fracture and cavity images.

[0141] Optionally, based on the target shape parameters of the initial segmentation of the fracture and cavity images in the full-bore conductivity image, the Techlog software is used to perform secondary segmentation of the initial segmentation of the fracture and cavity images in the full-bore conductivity image to obtain fracture and cavity images. This includes: using the Techlog software to remove invalid targets with target shape parameters less than the effective threshold from the initial segmentation of the fracture and cavity images in the full-bore conductivity image to obtain fracture and cavity images.

[0142] In vertical wells, the angular parameters of ineffective targets such as horizontal or low-dip high-conductivity clay laminae and suture lines are very small. In one example, 10° is used as the effective threshold for the target shape parameter. Further, high-conductivity targets with a shape parameter less than 10° (i.e., angular parameters less than 10°) are considered ineffective targets. In Techlog software, the initial segmentation of the whole-wellbore conductivity image is used to perform secondary segmentation of the fracture and void images to remove ineffective targets, resulting in fracture and void images. The effective threshold can be set based on experience, and this embodiment does not limit its application.

[0143] Step 907: Based on the crack and hole images, extract the electro-imaging crack and hole parameters using Techlog software.

[0144] Optionally, based on the fracture and pore sub-images, the extraction of electrical imaging fracture and pore parameters using Techlog software includes: for the fracture and pore sub-images segmented in the second stage, based on the calculation of single-target parameters, the extraction of electrical imaging fracture and pore parameters for the region where an image frame is located using Techlog software, where an image frame is equivalent to the sampling interval of conventional well logging data; moving the image frame, the extraction of electrical imaging fracture and pore parameters for other regions using Techlog software.

[0145] Optionally, the electro-imaging fracture-vuggy parameters include: the average roundness of multiple targets within the image frame, the average length of multiple targets within the image frame, the average width of multiple targets within the image frame, the porosity-fracture porosity within the image frame, and the fracture porosity within the image frame. Further optionally, the above electro-imaging fracture-vuggy parameters are used to characterize the quality of fractured reservoirs.

[0146] Step 908: Use Techlog software to plot the extracted electro-imaging slit parameters.

[0147] Please refer to Figure 10 The invention illustrates an electro-imaging fracture and cavity parameter extraction system 100, which includes the following modules: a full-bore coverage image generation module 1001, an initial segmentation module 1002, a target shape parameter extraction module 1003, a secondary segmentation module 1004, and a fracture and cavity parameter extraction module 1005.

[0148] A full-bore coverage image generation module 1001 is used to acquire full-bore coverage images from electrical imaging logging. Optionally, the full-bore coverage image generation module 1001 is used for, but not limited to:

[0149] 10011. Obtain the electrical conductivity data of the entire wellbore from the electrical imaging logging.

[0150] Further optionally, the full-bore coverage image generation module 1001 is used for, but is not limited to:

[0151] 10011-① Input the raw conductivity data.

[0152] In one possible implementation, the input raw conductivity data is the electrode conductivity data after shallow resistivity calibration. Since the button electrode system of the electrical imaging logging tool is a non-focused electrode system, the measured values ​​only vary proportionally with the conductivity of the geological body near the wellbore. Therefore, shallow resistivity logging data is used for calibration to obtain the electrode conductivity data after shallow resistivity calibration.

[0153] 10011-② Based on the original conductivity data, draw the original electrical imaging conductivity image.

[0154] Based on the original conductivity data, and according to the orientation of the conductivity curve of the button electrode in the middle of the reference plate, the wellbore is cut along due north, and an electrical imaging conductivity image is drawn.

[0155] Optionally, different reference plates of different electrical imaging logging tools have different middle button electrodes. For example, the XRMI electrical imaging logging tool uses plate 1 as the reference plate, and the 13th button electrode of plate 1 in XRMI is the middle button electrode. The FMI electrical imaging logging tool uses plate 1 as the reference plate, and the 12th button electrode of plate 1 in FMI is the middle button electrode.

[0156] 10011-③ Based on the original electrical imaging conductivity image, the method of filling the gaps between electrical imaging electrodes is applied to obtain the whole-wellbore conductivity data of electrical imaging logging.

[0157] Optionally, the method of filling the gaps between the electro-imaging electrodes refers to generating gap data between the electrodes of the electro-imaging logging tool by applying the method of growing from the edge of the electrode towards the center of the gap based on the original electro-imaging conductivity image, thereby obtaining conductivity data covering the entire wellbore of the electro-imaging logging tool, i.e., the conductivity data of the entire wellbore of the electro-imaging logging tool.

[0158] 10012. Based on the full-bore conductivity data of electrical imaging logging, obtain the full-bore coverage image of electrical imaging logging.

[0159] In one possible implementation, based on the full-bore conductivity data from electrical imaging logging, the azimuth of each electrode relative to true north is calculated using reference electrode azimuth data, and a conductivity image covering the entire wellbore after the blank zone between the electrodes is filled is drawn, which is the full-bore coverage image of electrical imaging logging.

[0160] The initial segmentation module 1002 is used to perform initial segmentation on the full-bore coverage image of the electrical imaging logging, and to obtain the initial segmentation of the fracture and cavity images of the full-bore conductivity image. Optionally, the initial segmentation module 1002 is used for, but not limited to:

[0161] 10021. Based on the full-bore coverage image of electrical imaging logging, obtain the initial segmentation of the fracture cavity image of the full-bore conductivity image of the area where an image frame is located.

[0162] Further optionally, the initial segmentation module 1002 is used for, but is not limited to:

[0163] 10021-① Input a full-bore coverage image data of an electrical imaging logging frame;

[0164] 10021-② Perform a two-dimensional binary wavelet transform on the full-bore coverage image data of an electrical imaging logging image frame. For wavelet transform of order 2, calculate the modulus of the wavelet transform coefficients for each conductivity data point to obtain the modulus of the second-order wavelet transform coefficients.

[0165] In one example, the conductivity data in a full-bore coverage image of an electrical imaging logging frame is set as follows:

[0166]

[0167] Perform a second wavelet transform to obtain the wavelet coefficients corresponding to the conductivity data:

[0168]

[0169] Where j is the wavelet transform order, and the wavelet coefficients of the second-order wavelet transform of the conductivity data are taken:

[0170]

[0171] Calculate the magnitudes of the second-order wavelet transform coefficients:

[0172]

[0173] 10021-③ Based on the modulus of the second-order wavelet transform coefficients, the modulus maxima are obtained by using three-point peak finding in the depth direction.

[0174] 10021-④ Based on the modulus maxima, obtain the coordinate pixel value of the modulus maxima, determine the segmentation threshold according to the coordinate pixel value of the modulus maxima, perform initial image segmentation, and obtain the whole wellbore conductivity image segmentation of the image frame area.

[0175] The modulus maxima, i.e., the points where the conductivity values ​​of the whole-bore conductivity image change abruptly, are further, the segmentation points. Optionally, a segmentation threshold is determined based on the location of the segmentation points, and even more optionally, initial image segmentation is performed based on the segmentation threshold.

[0176] 10022. Move the image frame to obtain the full borehole conductivity image of other areas and the initial segmentation of the fracture hole image.

[0177] In one possible implementation, the initial segmentation module 1002 is used to: move the image frame and repeat the above sub-step 10021 until the logging endpoint depth, to obtain the initial segmentation of the fracture-cavity sub-image of the whole-wellbore conductivity image of other areas. The logging endpoint depth is obtained from the image.

[0178] 10023. Based on the initial segmentation of the full-bore conductivity image of the region containing an image frame and the initial segmentation of the fracture-cavity image of the full-bore conductivity image of other regions, output the initial segmentation of the full-bore conductivity image of the fracture-cavity image.

[0179] The target shape parameter extraction module 1003 is used to extract the target shape parameters of the initial segmentation fracture hole image of the whole wellbore electrical conductivity image.

[0180] Optionally, the target shape parameter extraction module 1003 is used to: extract the angle parameters of high-conductivity targets based on the initial segmentation of fracture and cavity images from the full-bore conductivity image. On the two-dimensional conductivity image covering the entire wellbore, horizontal high-conductivity mud layers, suture lines, and other non-effective high-conductivity targets have different angles than fracture and cavity targets. To distinguish non-effective high-conductivity targets from fracture and cavity targets using the initial segmentation target shape parameters, the initially segmented fracture and cavity images are further processed to extract the angle parameters of high-conductivity targets.

[0181] Further optionally, the angular parameter of a high-conductivity target is defined as the angle between the major axis of the high-conductivity target (the line connecting the two points with the greatest distance on the target edge) and the horizontal direction.

[0182] The secondary segmentation module 1004 is used to perform secondary segmentation on the fracture and cavity images of the initial segmentation of the full-wellbore conductivity image based on the target shape parameters of the initial segmentation of the fracture and cavity images, and to obtain fracture and cavity images.

[0183] Optionally, the secondary segmentation module 1004 is used to: remove invalid targets with target shape parameters less than an effective threshold from the initial segmentation of the fracture and cavity image in the whole-wellbore conductivity image, thereby obtaining fracture and cavity images. In vertical wells, the angular parameters of invalid targets such as horizontal or low-dipity high-conductivity mudstone laminae and suture lines are very small. In one example, 10° is used as the effective threshold for the target shape parameter. Further optionally, the secondary segmentation module 1004 is used to treat high-conductivity targets with target shape parameters less than 10°, i.e., angular parameters less than 10°, as invalid targets, and perform secondary segmentation on the initial segmentation of the fracture and cavity image in the whole-wellbore conductivity image to remove invalid targets, thereby obtaining fracture and cavity images.

[0184] The fracture and pore parameter extraction module 1005 is used to extract electrical imaging fracture and pore parameters based on fracture and pore sub-images. Optionally, the fracture and pore parameter extraction module 1005 is used to: extract electrical imaging fracture and pore parameters for a region containing an image frame based on single-target parameter calculation for a fracture and pore sub-image segmented by secondary segmentation, where an image frame is equivalent to the sampling interval of conventional well logging data; and move the image frame to extract electrical imaging fracture and pore parameters for other regions.

[0185] Optionally, the electro-imaging fracture-vuggy parameters include: the average roundness of multiple targets within the image frame, the average length of multiple targets within the image frame, the average width of multiple targets within the image frame, the porosity-fracture porosity within the image frame, and the fracture porosity within the image frame. Further optionally, the above electro-imaging fracture-vuggy parameters are used to characterize the quality of fractured reservoirs.

[0186] It should be understood that the above Figure 10 The system provided is illustrated using the above-described division of functional modules as an example. In practical applications, the functions described above can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. Furthermore, the system and method embodiments provided in the above examples belong to the same concept, and their specific implementation processes are detailed in the method embodiments, which will not be repeated here.

[0187] In an exemplary embodiment, a computer-readable storage medium is also provided, which stores at least one piece of program code that is loaded and executed by a processor to enable a computer to implement any of the above-described methods for extracting electro-imaging slit parameters.

[0188] Optionally, the aforementioned 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, floppy disk, and optical data storage device, etc.

[0189] In an exemplary embodiment, a computer program or computer program product is also provided, which stores at least one computer instruction, which is loaded and executed by a processor to enable the computer to implement any of the above-described methods for extracting electro-imaging slit parameters.

[0190] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices or modules, or may be electrical, mechanical or other forms of connection.

[0191] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of the embodiments of this application, depending on actual needs.

[0192] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0193] It should also be understood that, in the various embodiments of this application, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0194] In this application, the term "at least one" means one or more, and the term "multiple" means two or more. For example, multiple data means two or more data.

[0195] It should be understood that the terminology used in the description of the various examples herein is for the purpose of describing particular examples only and is not intended to be limiting. As used in the description of the various examples and the appended claims, the singular forms “a” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0196] The above are merely exemplary embodiments of this application and are not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application shall be included within the protection scope of this application.

Claims

1. A method for extracting parameters of an electrical imaging slit, characterized in that, The method includes: Acquire full-bore coverage images from electrical imaging logging; The full-bore coverage image of the electrical imaging logging is initially segmented to obtain the initial segmentation of the fracture cavity image of the full-bore conductivity image; Extract the target shape parameters of the initial segmentation of the fractured cavity image from the full-bore conductivity image; Based on the target shape parameters of the initial segmentation of the fracture and cavity images in the full-wellbore conductivity image, the initial segmentation of the fracture and cavity images in the full-wellbore conductivity image is further segmented to obtain fracture and cavity images; Based on the images of cracks and holes, extract the electrical imaging crack and hole parameters; The acquisition of whole-wellbore electrical conductivity data from electrical imaging logging includes: Input the raw conductivity data; Based on the original conductivity data, an original electrical imaging conductivity image is drawn; Based on the original electrical imaging conductivity image, the method of filling the gaps between electrical imaging electrodes is applied to obtain the whole-wellbore conductivity data of electrical imaging logging. The method of obtaining whole-wellbore conductivity data by applying the gap-filling method between electrical imaging electrodes based on the original electrical imaging conductivity image includes: Based on the original electrical imaging conductivity image, the method of growing from the edge of the electrode to the center of the gap is applied to generate the blank band data between the electrodes of the electrical imaging logging tool, so as to obtain the conductivity data covering the entire wellbore of the electrical imaging logging. The extraction of target shape parameters from the initial segmentation of the fractured cavity image of the whole-wellbore conductivity image includes: Based on the initial segmentation of the fracture and cavity image in the full-bore conductivity image, the angle parameters of the high-conductivity target are extracted, and the angle parameters of the high-conductivity target are used as the target shape parameters of the initial segmentation of the fracture and cavity image in the full-bore conductivity image.

2. The method according to claim 1, characterized in that, The acquisition of full-bore coverage images from electrical imaging logging includes: Acquire whole-wellbore electrical conductivity data from electrical imaging logging; Based on the full-bore conductivity data from the electrical imaging logging, a full-bore coverage image from the electrical imaging logging is obtained.

3. The method according to claim 1, characterized in that, The initial segmentation of the full-bore coverage image of the electrical imaging logging to obtain the initial segmentation of the fractured cavity image of the full-bore conductivity image includes: Based on the full-bore coverage image of the electrical imaging logging, the initial segmentation of the fracture and cavity image is obtained for the full-bore conductivity image of the area where an image frame is located. Move the image frame to obtain the initial segmentation of the fracture hole image and the overall borehole conductivity image of other areas; Based on the initial segmentation of the fracture and hole image of the whole borehole conductivity image in the region where the image frame is located, and the initial segmentation of the fracture and hole image of the whole borehole conductivity image in the other regions, the initial segmentation of the fracture and hole image of the whole borehole conductivity image is output.

4. The method according to claim 1 or 3, characterized in that, The process of obtaining an initial segmentation of the fracture-cavity image based on the full-bore coverage image of the electrical imaging logging includes: Input a full-bore coverage image data of an electrical imaging logging frame; A two-dimensional binary wavelet transform is performed on the full-wellbore coverage image data of the electrical imaging logging of the image frame. For the wavelet transform of order 2, the modulus of the wavelet transform coefficients of each conductivity data point is calculated to obtain the modulus of the second-order wavelet transform coefficients. Based on the modulus of the second-order wavelet transform coefficients, the modulus maxima are obtained by three-point peak finding in the depth direction. Based on the modulus maxima, initial image segmentation is performed to obtain a segmented image of the borehole conductivity of the region where an image frame is located.

5. The method according to claim 1, characterized in that, The method involves performing secondary segmentation of the fracture and cavity images based on the target shape parameters of the initial segmentation of the full-wellbore conductivity image to obtain fracture and cavity images, including: In the initial segmentation of the fracture and cavity images from the whole-well conductivity image, invalid targets with target shape parameters less than the effective threshold are removed to obtain fracture and cavity images.

6. The method according to any one of claims 1-3 and 5, characterized in that, The step of extracting electro-imaging crack and hole parameters based on the crack and hole sub-images includes: Based on the sub-images of cracks and holes, electrical imaging crack and hole parameters are extracted from the region where an image frame is located. Move the image frame to extract electro-imaging slit parameters from other areas.

7. A system for extracting parameters of an electro-imaging slit, characterized in that, The system includes: The full borehole coverage image generation module is used to acquire full borehole coverage images from electrical imaging logging. The initial segmentation module is used to perform initial segmentation on the full-bore coverage image of the electrical imaging logging to obtain the initial segmentation of the fracture hole image of the full-bore conductivity image; The target shape parameter extraction module is used to extract the target shape parameters of the initial segmentation fracture cavity image of the whole borehole conductivity image; The secondary segmentation module is used to perform secondary segmentation on the initial segmentation of the fracture and cavity image of the full-wellbore conductivity image based on the target shape parameters of the initial segmentation of the fracture and cavity image, and obtain fracture and cavity images. The crack / hole parameter extraction module is used to extract electro-imaging crack / hole parameters based on the crack / hole sub-images; The full-bore coverage image generation module is specifically used to input raw electrical conductivity data; draw raw electrical imaging conductivity images based on the raw electrical conductivity data; and obtain full-bore electrical conductivity data for electrical imaging logging by applying a method of filling the gaps between electrical imaging electrodes based on the raw electrical imaging conductivity image. The step of obtaining full-bore electrical conductivity data for electrical imaging logging by applying a method of filling the gaps between electrical imaging electrodes based on the raw electrical imaging conductivity image includes: generating gap band data between the electrodes of the electrical imaging logging tool by applying a method of growing from the electrode edges towards the center of the gaps based on the raw electrical imaging conductivity image, so as to obtain electrical conductivity data covering the entire wellbore of the electrical imaging logging tool. The target shape parameter extraction module is specifically used to extract the angle parameters of high-conductivity targets based on the initial segmentation of the fracture-cavity image of the full-bore conductivity image, and to use the angle parameters of the high-conductivity targets as the target shape parameters of the initial segmentation of the fracture-cavity image of the full-bore conductivity image.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one program instruction or code, which, when loaded and executed by a processor, enables the computer to implement the method for extracting electro-imaging slit parameters as described in any one of claims 1-6.

Images