A method for fine scanning and quantitative characterization of black shale multi-scale hydraulic fractures

Abstract

The application discloses a black shale multi-scale hydraulic fracture fine scanning and quantitative characterization method, which is applied to the field of unconventional shale oil and gas development and aims at the problem that the prior art cannot quantitatively describe fracture complexity. The method solves the problems that laser scanning is difficult to scan black shale and subtle features of a post-pressing fracture surface are difficult to capture by pasting an identification sheet on the fracture surface. The method can scan a shale sample with a large size, can truly display the three-dimensional form of the post-pressing fracture and the roughness of the fracture surface, and proposes three mathematical models for calculating the fracture roughness, namely, a bulk density, a bedding fracture and a main fracture area ratio and a fracture surface point cloud elevation mean square deviation. The method improves the accuracy of scanning the black shale fracture surface and quantitatively describes the fracture complexity.

Description

Technical Field

[0001] This invention belongs to the field of unconventional shale oil and gas development, and specifically relates to a fine scanning and quantitative characterization technique for multi-scale hydraulic fractures in black shale. Background Technology

[0002] my country has abundant shale oil and gas resources with huge development potential. However, the initial porosity and permeability of shale oil and gas reservoirs are low. To realize the commercial exploitation of shale oil and gas, large-scale hydraulic fracturing is required for development. Currently, indoor hydraulic fracturing experiments are an effective means of revealing the propagation of hydraulic fractures in shale. However, the scanning and extraction of post-fracturing fracture surfaces and the characterization of fracture complexity mainly rely on CT scans, morphological scanning, and conventional fracture complexity characterization methods. These methods have the following drawbacks: 1. Shale is typically black, and black shale is not sensitive to light, absorbing some light and failing to be scanned. The low precision of scanning equipment may also overlook subtle features on the fracture surface. 2. Large-sized shale samples cannot be scanned. Standard shale hydraulic fracturing samples are typically 300×300×300mm cubes, which are large. CT scans of large samples have low precision, filtering out subtle features on the fracture surface. 3. The propagation morphology of fractures cannot be visually represented. Scanning speed is slow, operation is complex, and the scanned fracture surfaces must be manually pieced together to form a complete fracture surface. This pieced-together process introduces errors, and the reconstructed fracture surface is stiff and differs significantly from the actual fracture surface morphology. 4. Most current fracture complexity characterization methods only provide a qualitative description, lacking a quantitative approach to characterizing fracture complexity and a comprehensive method for handling fractures of varying degrees of complexity.

[0003] For the reasons mentioned above, there is an urgent need for a multi-scale hydraulic fracture fine scanning and quantitative characterization method for black shale, which can improve the accuracy of black shale fracture surface scanning and qualitatively describe the complexity of post-compression shale fractures at multiple scales. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes a method for fine scanning and quantitative characterization of multi-scale hydraulic fractures in black shale. This method avoids the drawbacks of black shale absorbing light, which prevents the fracture surface from being scanned and results in low scanning accuracy. It also allows for more intuitive observation of the fracture propagation morphology after the experiment and determines the fracture complexity through a multi-scale fracture complexity characterization method.

[0005] The technical solution adopted in this invention is: a method for fine scanning and quantitative characterization of multi-scale hydraulic fractures in black shale, comprising:

[0006] S1. Preparations before the experiment;

[0007] The black shale outcrop sample was processed into a standard cubic specimen using wire cutting. Then, a blind hole was drilled in the middle of the standard cubic specimen to serve as a simulated wellbore. The wellbore was placed into the simulated wellbore, and the axis of the wellbore after placement was parallel to the shale bedding plane. Then, black glue was used to fill the gap between the outer wall of the wellbore and the wellbore.

[0008] The viscosity of the fracturing fluid is configured according to the on-site construction parameters, and a dye is mixed into the fracturing fluid.

[0009] Based on similarity criteria, the on-site construction parameters were scaled to determine the magnitude of the three principal stresses and the injection rate during the test.

[0010] S2. Conduct a fracturing experiment;

[0011] Connect the wellbore to the fracturing pipe, apply the triaxial principal stress determined in step S1 to the surface of the standard cubic sample using the fracturing fluid prepared in step S1, wait for the standard cubic sample to stabilize, and then perform fracturing on the standard cubic sample according to the injection rate determined in step S1. When the peak fracturing stress drops rapidly to 0, the shale sample will produce fracturing cracks, and the experiment will be stopped.

[0012] S3. Shale sample crushing and splicing;

[0013] Observe the surface of the standard cubic sample after the experiment, and find the main crack and bedding crack where the dye has overflowed. Use a screwdriver to break the shale sample along the main crack and bedding crack, and then piece the broken shale sample fragments back together to form the shape of the standard cubic sample before breaking.

[0014] S4. Establish framework points;

[0015] At least three identification patches are attached to the outer surface of each shale fragment near the center of the assembled standard cubic specimen. These identification patches are not on the same straight line. The distance between one identification patch and other identification patches on the same outer surface of the same shale fragment is 1-3 cm.

[0016] When the outer surfaces of two adjacent shale fragments are on the same plane on the assembled standard cubic specimen, the minimum distance between the identification pieces on these two outer surfaces is less than or equal to 8 cm; if this condition is not met, the distance between the identification pieces on these two outer surfaces is considered too far, and at least 3 more identification pieces are attached at the junction of these two outer surfaces.

[0017] The identification plates on the outer surface of each shale fragment were scanned sequentially using a handheld 3D laser scanner.

[0018] When the outer surfaces of two shale fragments are perpendicular to each other, attach at least three identification patches to each of the two outer surfaces 1-2 cm from the corners; scan the identification patches 1-2 cm from the corners on the two outer surfaces with a handheld 3D laser scanner.

[0019] The identification patches on the outer surface of each shale fragment after scanning, and the identification patches on the outer surface of each shale fragment 1-2 cm away from the edges, are saved as frame points in Geomagic image post-processing software;

[0020] S5, Crack Surface Scan;

[0021] After establishing the framework, select shale fragments that can be pieced together to form a complete main fracture surface, and attach identification patches to the uneven areas of the main fracture surface containing dye. Use a handheld 3D laser scanner to scan the identification patches on the outer surface of the shale fragments that have been pieced together to form a complete main fracture surface, and determine the spatial position of the main fracture surface on the assembled standard cubic specimen. Then scan the identification patches on the main fracture surface containing dye, import the scanned main fracture surface data into Geomagic image post-processing software, cut out the shape of the actual main fracture surface generated during the hydraulic fracturing process according to the position of dye wetting, and calculate the area of ​​the main fracture surface using Geomagic image post-processing software.

[0022] Select shale fragments that can be pieced together to form a complete bedding fracture surface. Attach identification patches to the uneven areas of the bedding fracture surface containing dye. Use a handheld 3D laser scanner to scan the identification patches on the outer surface of the shale fragments with the complete bedding fracture surface to determine the spatial position of the bedding fracture surface on the assembled standard cubic specimen. Then scan the identification patches on the bedding fracture surface containing dye. Import the scanned bedding fracture surface data into Geomagic image post-processing software. Based on the location of dye wetting, cut out the shape of the actual bedding fracture surface generated during hydraulic fracturing. Use Geomagic image post-processing software to calculate the area of ​​the bedding fracture surface.

[0023] Geomagic image post-processing software automatically stitches and saves the main crack surface and the bedding crack surface based on the frame points.

[0024] S6, Crack Surface Reconstruction;

[0025] The complete main crack surface and bedding crack surface obtained in Geomagic image post-processing software are imported into 3ds Max software. A semi-transparent standard cube with the same size as the standard cube sample in step S1 is created in 3ds Max software. The positions of the main crack surface and bedding crack surface on the semi-transparent standard cube are adjusted according to the positions of the main crack surface and bedding crack surface on the assembled standard cube sample. Finally, the final crack surface model is rendered.

[0026] S7. Quantitative characterization of crack surface complexity;

[0027] Using the area A1 of the main fracture surface, the area A2 of the bedding fracture, and the total fracture area A obtained in step S5, the shale fracture surface is converted into point cloud data to obtain the number of points n and the elevation x of each point. i The standard deviations of the fracture surface complexity, shale mass density, and point cloud data elevation of the fracture surface after compression were calculated respectively, thus obtaining quantitative characterization results of fracture surface complexity.

[0028] The dyeing agent mentioned in step S1 is specifically a red or green dyeing agent.

[0029] The main fracture mentioned in step S3 is specifically a hydraulic fracture surface perpendicular to the bedding plane.

[0030] The bedding fractures mentioned in step S3 are specifically hydraulic fracture surfaces parallel to the bedding planes.

[0031] In step S4, when scanning the identification patch on the outer surface of the shale fragment near the corner 1-2cm with a handheld 3D laser scanner, keep the center point of the scanner aligned with the corner, the scanner 30-40cm away from the corner and the scanning angle 45° with the horizontal plane.

[0032] The formula for calculating the complexity of the shale fracture surface after compression in step S7 is:

[0033]

[0034] In the formula, β is the ratio of the area of ​​the bedding fracture to the area of ​​the main fracture; A1 is the area of ​​the main fracture surface of the post-compression shale, in mm. 2 A2 represents the area of ​​post-compression shale bedding fractures, in mm. 2 .

[0035] The formula for calculating the density of the shale mass after compression in step S7 is:

[0036]

[0037] In the formula, ε is the density of the compressed shale mass, in mm. 2 / mm 3 A represents the total area of ​​the fractured surface of the shale after compression, in mm. 2 v represents the volume of the shale sample, in mm. 3 .

[0038] The standard deviation of the elevation of the shale fracture surface point cloud data after compression in step S7 is calculated as follows:

[0039]

[0040] In the formula, S is the standard deviation of the elevation of the point cloud data of the fracture surface of the shale after compression; n is the number of points; x i is the elevation of each point; x is the average elevation of the point cloud on the fracture surface of the shale after compression.

[0041] The beneficial effects of this invention are as follows: By attaching identification patches to the outer surface of the fractured shale fragments and the uneven areas of the surface from which a complete fracture surface can be pieced together, this invention solves the problem of laser scanning being difficult to scan black shale and capturing the subtle features of the fracture surface after compression. The method of this invention improves the accuracy of scanning the fracture surface of black shale, and is also applicable to scanning larger shale samples, which can intuitively show the expansion of fractures in shale after compression; and can qualitatively describe the complexity of fractures in shale after compression at multiple scales. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of the bonding frame points for spliced ​​shale samples;

[0043] Figure 2 This is a schematic diagram of the sample identification strip framework;

[0044] Figure 3 This is a schematic diagram of the main fracture surface of a scanned shale sample;

[0045] Figure 4 This is a schematic diagram of the bedding fracture surface of a scanned shale sample;

[0046] Figure 5 This is a schematic diagram of the fracture surface extracted from a shale sample;

[0047] Figure 6 This is an image of the actual crack surface extracted from sample A after compression;

[0048] Figure 7 This is an image of the actual crack surface extracted from sample B after compression;

[0049] Figure 8 This is a flowchart of the technical process for fine scanning and quantitative characterization of multi-scale hydraulic fractures in black shale.

[0050] Attached reference numerals: 1. Frame identification plate, 2. Shale bedding plane, 3. Wellbore, 4. Handheld scanner, 5. Main fracture plane, 6. Bedding fracture plane. Detailed Implementation

[0051] To facilitate understanding of the technical content of this invention by those skilled in the art, the following description, in conjunction with the accompanying drawings, further illustrates the invention.

[0052] like Figure 8 As shown, the method of the present invention includes the following steps:

[0053] S1. Preparations before the experiment;

[0054] Fresh shale outcrop samples were selected and processed into standard 300×300×300mm cube specimens using wire cutting. A blind hole with a diameter of 22.0mm and a depth of 170.0mm was then drilled in the center of each specimen to serve as a simulated wellbore, ensuring the wellbore axis was parallel to the shale bedding plane. Black adhesive was used to fill the gap between the wellbore outer wall and the wellbore. Based on similarity criteria, the magnitude of the three principal stresses and the water injection rate during the test were determined. The fracturing fluid viscosity was adjusted according to the field construction parameters, and red or green dye was mixed in to facilitate the identification of post-fracturing fractures.

[0055] The dimensions of the standard cubic specimen and the blind hole dimensions in this step can be determined by the processing equipment used in the actual application.

[0056] S2. Conduct a fracturing experiment;

[0057] Connect the wellbore to the fracturing pipe, select the fracturing fluid according to S1, apply triaxial principal stress to the cubic surface of the shale sample and wait for the shale sample to stabilize for 5 minutes, then perform hydraulic fracturing on the shale sample at the set injection rate. When the peak fracturing stress drops rapidly to 0, the shale sample will develop fracturing cracks, and the experiment will be stopped.

[0058] S3. Shale sample crushing and splicing;

[0059] Observe the surface of the shale sample after the experiment, find the main crack (hydraulic crack surface perpendicular to the bedding plane) and bedding crack (hydraulic crack surface parallel to the bedding plane) on the surface of the shale sample where the dye has overflowed, use a screwdriver to break it along the crack, and then piece the broken shale sample fragments back together to the cube shape before breaking.

[0060] S4. Establish framework points;

[0061] After the cubic shale sample is assembled, 4-5 identification patches with a diameter of 0.5 cm are attached to the outer surface of each shale fragment near the center. The distance between the two nearest identification patches on the outer surface of a single fragment should be 1-3 cm, and the identification patches should not be on the same straight line. When the outer surfaces of two shale fragments are on the same plane on the cubic shale sample, the distance between the two nearest identification patches on the outer surfaces of the two shale fragments should not exceed 8 cm. When the distance between the two nearest identification patches is greater than 8 cm, 4-5 more identification patches should be attached between the two fragments to act as a "bridging" device. A handheld 3D... The laser scanner scans the identification pieces sequentially. When the surfaces of two fragments with the identification pieces attached are perpendicular, first attach 4-5 identification pieces to each side of the corner near the bend between the two fragments, 1-2 cm away, to act as a "bridge". When scanning the identification pieces on both sides of the corner with a handheld 3D laser scanner, keep the center point of the scanner aligned with the corner, keep the scanner 30-40 cm away from the corner and keep the scanning angle at about 45° to the horizontal plane. Save the scanned frame points in the Geomagic image post-processing software. The frame points established are used as reference coordinates to locate the position of the scanned crack.

[0062] The outer surface of the shale fragments mentioned in this step should be coplanar with the original standard cube surface before compression.

[0063] In this step, at least three identification patches should be pasted on the outer surface of the shale fragment each time to ensure the accuracy of the scan; in this embodiment, pasting four to five patches each time is a more suitable choice.

[0064] In this step, the scanner should be 30-40cm away from the edge and the scanning angle should be about 45° to the horizontal plane. The specific scanning angle can be deviated by 10° to the left or right, that is, the scanning angle can be 35°-55° to the horizontal plane.

[0065] S5, Crack Surface Scan;

[0066] After establishing the framework, select shale fragments that can be pieced together to form a complete main fracture surface. Attach identification patches to the uneven areas of the main fracture surface containing dye. Use a handheld 3D laser scanner to scan the identification patches on the outer surface of the main fracture to determine its spatial position within the cubic shale sample. After determining the spatial position, scan the dyed main fracture surface. The handheld 3D laser scanner uses the light reflected from the identification patches to determine their undulation, thus revealing the fine features of the fracture surface. The scanned image of the main fracture surface is then processed in Geomagic image post-processing software, where it is cropped according to the dye penetration location. The shape of the actual main fracture surface generated during hydraulic fracturing is determined, and its area is calculated using software. Fragments suitable for piecing together a bedding fracture surface are selected, and identification patches are attached to the uneven areas of the bedding surface containing dye. A handheld 3D laser scanner is used to first scan the identification patches on the outer surface of the bedding fracture, then scan the bedding fracture itself. The scanned bedding fracture surface is imported into Geomagic image post-processing software. Based on the location of dye wetting, the shape of the actual bedding fracture surface generated during hydraulic fracturing is cut out, and its area is calculated using Geomagic software. The software automatically stitches together and saves the main fracture surface and the bedding fracture surface based on frame points.

[0067] The number of identification patches to be pasted on the uneven surface of the crack in this step depends on the size of the uneven surface. For example, at least one identification patch should be pasted at the center of the uneven surface so that the handheld 3D laser scanner can determine the undulation of the uneven surface based on the light information reflected back from the identification patches.

[0068] S6, Crack Surface Reconstruction;

[0069] The complete fracture surface obtained in Geomagic software is imported into 3ds Max software. A 300×300×300mm semi-transparent standard cube is created in 3ds Max to simulate a cubic shale sample. The position of the fracture surface and the semi-transparent standard cube are adjusted according to the position of the fracture surface on the cubic shale sample. Finally, the final fracture surface model is rendered.

[0070] S7. Quantitative characterization of crack surface complexity;

[0071] Using the area A1 of the main fracture surface, the area A2 of the bedding fracture, and the total fracture area A obtained in step S5, the shale fracture surface is then converted into point cloud data to obtain the number of points n and the elevation x of each point. i The following three formulas are used to calculate the complexity of the fracture surface of the shale after compression.

[0072]

[0073] In the formula, β is the ratio of the area of ​​the bedding fracture to the area of ​​the main fracture; A1 is the area of ​​the main fracture surface of the post-compression shale, in mm. 2 A2 represents the area of ​​post-compression shale bedding fractures, in mm. 2 ;

[0074]

[0075] In the formula, ε is the density of the compressed shale mass, in mm. 2 / mm 3 A represents the total area of ​​the fractured surface of the shale after compression, in mm. 2 v represents the volume of the shale sample, in mm. 3 ;

[0076]

[0077] In the formula, S is the standard deviation of the elevation of the point cloud data of the fracture surface of the shale after compression; n is the number of points; x i is the elevation of each point; x is the average elevation of the point cloud on the fracture surface of the post-compression shale;

[0078] Hydraulic fracturing experiments were conducted on two groups of shale samples, A (vertical principal stress of 22 MPa, horizontal maximum principal stress of 14 MPa, and horizontal minimum principal stress of 8 MPa) and B (vertical principal stress of 22 MPa, horizontal maximum principal stress of 18 MPa, and horizontal minimum principal stress of 8 MPa), with an injection rate of 20 ml / min. After the experiments, the fracture surface was extracted and the fracture complexity was calculated using the method described above. The calculation results are shown in Table 1.

[0079] Table 1 Calculation results of crack surface and crack complexity

[0080]

[0081] In summary, the method of this invention can solve the problem of laser scanning being difficult to scan black shale and capturing the subtle features of post-compression fracture surfaces. It can scan large-sized shale samples and use a multi-scale calculation method to calculate the complexity of post-compression shale, thus achieving quantitative characterization of fracture surface complexity.

[0082] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Various modifications and variations can be made to the invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the scope of the claims of the invention.

Claims

1. A method for fine scanning and quantitative characterization of multi-scale hydraulic fractures in black shale, characterized in that, include: S1. Preparations before the experiment; The black shale outcrop sample was processed into a standard cubic specimen by wire cutting. Then, a blind hole was drilled in the middle of the standard cubic specimen as a simulated wellbore. The wellbore was placed into the simulated wellbore, and the axis of the wellbore after placement was parallel to the shale bedding plane. Then, black glue was used to fill the gap between the outer wall of the wellbore and the wellbore. The viscosity of the fracturing fluid is configured according to the on-site construction parameters, and a dye is mixed into the fracturing fluid. Based on similarity criteria, the on-site construction parameters were scaled to determine the magnitude of the three principal stresses and the injection rate during the test. S2. Conduct a fracturing experiment; Connect the wellbore to the fracturing pipe, apply the triaxial principal stress determined in step S1 to the surface of the standard cubic sample, wait for the standard cubic sample to stabilize, and then perform fracturing on the standard cubic sample according to the injection rate determined in step S1. When the peak fracturing stress drops rapidly to 0, the shale sample will produce fracturing cracks, and the experiment will be stopped. S3. Shale sample crushing and splicing; Observe the surface of the standard cubic sample after the experiment, and find the main crack and bedding crack where the dye has overflowed. Use a screwdriver to break the shale along the main crack and bedding crack, and then piece the broken shale fragments back together to form the shape of the standard cubic sample before breaking. S4. Establish framework points; At least three identification patches are attached to the outer surface of each shale fragment near the center of the assembled standard cubic specimen. These identification patches are not on the same straight line. The distance between one identification patch and other identification patches on the same outer surface of the same shale fragment is 1-3 cm. When the outer surfaces of two adjacent shale fragments are on the same plane on the assembled standard cubic specimen, the minimum distance between the identification pieces on these two outer surfaces is less than or equal to 8 cm; if this condition is not met, the distance between the identification pieces on these two outer surfaces is considered too far, and at least 3 more identification pieces are attached at the junction of these two outer surfaces. The identification plates on the outer surface of each shale fragment were scanned sequentially using a handheld 3D laser scanner. When the outer surfaces of two shale fragments are perpendicular to each other, attach at least 3 identification patches to each of the two outer surfaces 1-2 cm from the corners; scan the identification patches on the two outer surfaces 1-2 cm from the corners using a handheld 3D laser scanner; The identification patches on the outer surface of each shale fragment after scanning, and the identification patches on the outer surface of each shale fragment 1-2cm away from the edges, are saved as frame points in Geomagic image post-processing software; S5, Crack Surface Scan; After establishing the framework, select shale fragments that can be pieced together to form a complete main fracture surface, and attach identification patches to the uneven areas of the main fracture surface containing dye. Use a handheld 3D laser scanner to scan the identification patches on the outer surface of the shale fragments that have been pieced together to form a complete main fracture surface, and determine the spatial position of the main fracture surface on the assembled standard cubic specimen. Then scan the identification patches on the main fracture surface containing dye, import the scanned main fracture surface data into Geomagic image post-processing software, cut out the shape of the actual main fracture surface generated during the hydraulic fracturing process according to the position of dye wetting, and calculate the area of ​​the main fracture surface using Geomagic image post-processing software. Select shale fragments that can be pieced together to form a complete bedding fracture surface. Attach identification patches to the uneven areas of the bedding fracture surface containing dye. First, use a handheld 3D laser scanner to scan the identification patches on the outer surface of the shale fragments with the complete bedding fracture surface to determine the spatial position of the bedding fracture surface on the assembled standard cubic specimen. Then, scan the identification patches on the bedding fracture surface containing dye. Import the scanned bedding fracture surface data into Geomagic image post-processing software. Based on the location of dye wetting, cut out the shape of the actual bedding fracture surface generated during hydraulic fracturing. Calculate the area of ​​the bedding fracture surface using Geomagic image post-processing software. Geomagic image post-processing software automatically stitches and saves the main crack surface and the bedding crack surface based on the frame points. S6, Crack Surface Reconstruction; The complete main crack surface and bedding crack surface obtained in Geomagic image post-processing software are imported into 3ds Max software. A semi-transparent standard cube with the same size as the standard cube sample in step S1 is created in 3ds Max software. The positions of the main crack surface and bedding crack surface on the semi-transparent standard cube are adjusted according to their positions on the assembled standard cube sample. Finally, the final crack surface model is rendered. S7. Quantitative characterization of crack surface complexity; Using the area A1 of the main fracture surface, the area A2 of the bedding fracture surface, and the total fracture area A obtained in step S5, the shale fracture surface is converted into point cloud data, obtaining the number of points n and the elevation x of each point. i Calculate the complexity of the fracture surface of the shale after compression: ； In the formula It is the ratio of the area of ​​the bedding fracture surface to the area of ​​the main fracture surface; Post-compression shale mass density : ； In the formula This represents the volume of the shale sample. Standard deviation of elevation of point cloud data of fracture surface in post-compression shale : ； In the formula, n is the number of points; x i The elevation of each point; The average elevation of the point cloud on the fracture surface of the compressed shale; This yields a quantitative characterization of the crack surface complexity.

2. The method for fine scanning and quantitative characterization of multi-scale hydraulic fractures in black shale according to claim 1, characterized in that, The dyeing agent mentioned in step S1 is specifically a red or green dyeing agent.

3. The method for fine scanning and quantitative characterization of multi-scale hydraulic fractures in black shale according to claim 2, characterized in that, In step S4, when scanning the identification piece on the outer surface of the shale fragment 1-2cm from the corner with a handheld 3D laser scanner, keep the center point of the scanner aligned with the corner, keep the scanner 30-40cm away from the corner and the scanning angle is 35°-55° with the horizontal plane.

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