Shale reservoir treatment method and device, electronic equipment and storage medium

Abstract

The invention discloses a shale reservoir treatment method and device, electronic equipment and a storage medium. The method comprises the following steps: determining a first image of a target shale sample, and determining a first surface porosity according to the first image; determining a first reference scale from the candidate scales, selecting the first image according to the first reference scale to obtain at least one second image with the corresponding scale, determining a third image according to the at least one second image with the corresponding scale, and determining a second surface porosity according to the third image; determining a target surface porosity error according to the first surface porosity and the at least one second surface porosity, and determining a surface porosity distribution state according to the at least one second surface porosity; and determining a second reference scale according to the target surface porosity error and the surface porosity distribution state corresponding to different first reference scales, and determining a target scale according to the second reference scale. According to the method, the effectiveness of reservoir porosity evaluation is ensured, and the data volume for image acquisition and the calculation amount during analysis are reduced.

Description

Technical Field

[0001] This invention relates to the field of geological exploration technology, and in particular to a method, apparatus, electronic device and storage medium for processing shale reservoirs. Background Technology

[0002] Shale reservoirs are characterized by low porosity, low permeability, and strong heterogeneity, making the characterization of complex reservoir pore structures a current research hotspot and challenge. In recent years, with the continuous development of science and technology, the resolution of pore structure research has been constantly improving. However, as research precision increases, the sample size for analysis is becoming smaller (a few μm), but the selection of representative sample sizes cannot meet the needs of shale reservoir analysis. Summary of the Invention

[0003] This invention provides a shale reservoir processing method, apparatus, electronic device, and storage medium to address the problem that the selection of representative scales for shale samples cannot meet the needs of shale reservoir analysis.

[0004] According to one aspect of the present invention, a method for processing shale reservoirs is provided, comprising:

[0005] A first image of a target shale sample is determined, and a first porosity is determined based on the first image. The first image is an image obtained by scanning the target shale sample in different regions and then stitching them together. The target shale sample is a shale sample that has been polished and carbonized with a reference shale sample. The reference shale sample is shale rock collected from a shale reservoir. The first porosity is the ratio of the area of ​​pores in the target shale sample in the first image to the area of ​​the first image.

[0006] A first reference scale is determined from the candidate scales. A first image is selected based on the first reference scale to obtain at least one second image of the corresponding scale. A third image is determined based on the at least one second image of the corresponding scale, and a second porosity is determined based on the third image. The candidate scales include a base scale and a magnification scale. The base scale is determined based on the size of the sub-regions of the first image. The magnification scale is the base scale at different magnifications. The third image is any image selected from the at least one second image of the corresponding scale. The second porosity is the proportion of the area of ​​pores in the target shale sample in the third image to the area of ​​the third image.

[0007] A target face rate error is determined based on the first face rate and at least one second face rate, and a face rate distribution state is determined based on at least one second face rate. The target face rate error is used to characterize the mean of the error between the first face rate and at least one second face rate, and the face rate distribution state is used to characterize the distribution state of the second face rate.

[0008] A second reference scale is determined based on the target face rate error and the face rate distribution state corresponding to different first reference scales, and a target scale is determined based on the second reference scale. The target scale enables the captured second image to accurately reflect the overall characteristics of the target shale sample.

[0009] According to another aspect of the present invention, a shale reservoir processing apparatus is provided, comprising:

[0010] The first porosity determination module is used to determine a first image of a target shale sample and determine a first porosity based on the first image. The first image is an image obtained by scanning the target shale sample in different regions and then stitching them together. The target shale sample is a shale sample after polishing and carbonizing a reference shale sample. The reference shale sample is shale rock collected from a shale reservoir. The first porosity is the ratio of the area of ​​pores in the target shale sample in the first image to the area of ​​the first image.

[0011] The second aperture ratio determination module is used to determine a first reference scale from candidate scales, select a first image according to the first reference scale to obtain at least one second image of the corresponding scale, determine a third image according to the at least one second image of the corresponding scale, and determine the second aperture ratio according to the third image. The candidate scales include a base scale and a magnification scale. The base scale is determined according to the size of the sub-regions of the first image. The magnification scale is the base scale at different magnifications. The third image is any image selected from the at least one second image of the corresponding scale. The second aperture ratio is the proportion of the area of ​​pores in the target shale sample in the third image to the area of ​​the third image.

[0012] The target face rate error determination module is used to determine the target face rate error based on the first face rate and at least one second face rate, and to determine the face rate distribution state based on at least one second face rate. The target face rate error is used to characterize the mean of the error between the first face rate and at least one second face rate, and the face rate distribution state is used to characterize the distribution state of the second face rate.

[0013] The target scale determination module is used to determine a second reference scale based on the target face rate error and the face rate distribution state corresponding to different first reference scales, and to determine the target scale based on the second reference scale. The target scale enables the captured second image to accurately reflect the overall characteristics of the target shale sample.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] At least one processor; and

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the shale reservoir processing method according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the shale reservoir processing method according to any embodiment of the present invention.

[0019] The technical solution of this invention involves determining a first image of a target shale sample and determining a first porosity based on the first image; determining a first reference scale from candidate scales; selecting at least one second image of the first image based on the first reference scale to obtain at least one second image of the corresponding scale; determining a third image based on the at least one second image of the corresponding scale and determining a second porosity based on the third image; determining a target porosity error based on the first porosity and at least one second porosity; and determining the porosity distribution state based on at least one second porosity. The determination of the target porosity error and porosity distribution state provides a basis for selecting the target scale. Determining a second reference scale based on the target porosity error and porosity distribution state corresponding to different first reference scales, and then determining the target scale based on the second reference scale, ensures the accuracy of the target scale. This method ensures that the porosity in the second image selected based on the target scale reflects the porosity state in the first image of the target shale, thus ensuring the effectiveness of reservoir porosity evaluation while reducing the amount of data collected from images and the computational load during analysis.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] 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.

[0022] Figure 1 A flowchart of a shale reservoir treatment method provided in an embodiment of the present invention;

[0023] Figure 2This is a schematic diagram of a second porosity extraction process for a target shale sample at a scale of 25μm×25μm, provided as an embodiment of the present invention.

[0024] Figure 3 This is a schematic diagram of a second porosity extraction process for a target shale sample at a scale of 125μm×125μm, provided in an embodiment of the present invention.

[0025] Figure 4 This is a schematic diagram of a second porosity extraction process for a target shale sample at a scale of 250μm×250μm, provided in an embodiment of the present invention.

[0026] Figure 5 A schematic diagram illustrating a method for calculating the surface area of ​​a second aperture at a scale of 250μm×250μm provided in an embodiment of the present invention;

[0027] Figure 6 A schematic diagram of the second porosity extraction process for a target shale sample at a scale of 1000μm×1000μm provided in an embodiment of the present invention;

[0028] Figure 7 This is a schematic diagram of the face prevalence distribution provided in an embodiment of the present invention;

[0029] Figure 8 A schematic diagram of a first image of a target shale sample from region A provided in an embodiment of the present invention;

[0030] Figure 9 A second pore image of a target shale sample from region A at a scale of 250μm×250μm, provided as an embodiment of the present invention;

[0031] Figure 10 A second pore profile of a target shale sample from region A at a scale of 250μm×250μm is provided for an embodiment of the present invention;

[0032] Figure 11 This is a schematic diagram of the target porosity error distribution of different target shale samples provided in an embodiment of the present invention;

[0033] Figure 12 This is a schematic diagram of the structure of a shale reservoir processing device provided in an embodiment of the present invention;

[0034] Figure 13 A schematic diagram of the electronic device used to implement the shale reservoir processing method of this invention. Detailed Implementation

[0035] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0036] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0037] Figure 1 This is a flowchart illustrating a shale reservoir processing method provided in an embodiment of the present invention. This embodiment is applicable to determining the appropriate segmentation scale of shale samples during analysis. The method can be executed by a shale reservoir processing device, which can be implemented in hardware and / or software and can be configured in any electronic device with network communication capabilities. Figure 1 As shown, the method includes:

[0038] S110. Determine the first image of the target shale sample and determine the first aperture ratio based on the first image.

[0039] The first image is a stitched image obtained after scanning the target shale sample in sections. Furthermore, the size of each section can be 25 μm × 25 μm.

[0040] The target shale sample is a shale sample that has been polished and carbonized after being compared with a reference shale sample. The reference shale sample is shale rock collected from a shale reservoir.

[0041] Furthermore, the carbon plating process is to uniformly deposit a layer of carbon material on the surface of the reference shale sample.

[0042] The above steps, including carbon plating, can improve the clarity and resolution of images of target shale samples.

[0043] The first porosity is the ratio of the area of ​​pores within the target shale sample in the first image to the area of ​​the first image.

[0044] Specifically, the target shale sample is scanned in regions using the MAPS image acquisition system according to the region size, resulting in several images of the target shale sample with different region sizes. These images are then seamlessly stitched together to obtain the first image. Pores in the first image are extracted, and the total area of ​​the extracted pores is calculated. This calculated area is used as the first porosity.

[0045] The MAPS image acquisition system includes a structured light projector and a scanning electron microscope (SEM). The structured light projector generates and projects a structured light pattern onto the surface of the target shale sample. The SEM then scans the illuminated surface of the target shale sample.

[0046] Furthermore, the extraction of pores in the first image can be performed using AVIZO image processing software. AVIZO is a 3D visualization software capable of performing operations such as image scaling, calibration, conversion, and resampling. It also performs image optimization, filtering and convolution, Fourier frequency conversion, as well as image correction, stitching, registration, computation, correlation, and fusion.

[0047] For example, the target shale sample is placed under the MAPS image acquisition system and scanned to obtain a reference image with a single image pixel resolution of 10nm and a region size of 25μm×25μm. Each target shale sample can acquire 1600 images of 25μm×25μm each, and these 1600 images are seamlessly stitched together to obtain the first image. The first image is then processed using the AVIZO image processing software with a watershed method for pore identification and extraction.

[0048] The above steps, including determining the first face ratio, can provide a reference for determining the subsequent target scale.

[0049] S120. Determine a first reference scale from the candidate scales, select a first image according to the first reference scale to obtain at least one second image of the corresponding scale, determine a third image according to the at least one second image of the corresponding scale, and determine the second face ratio according to the third image.

[0050] The candidate scales include: the base scale and the magnification scale. The base scale is determined based on the size of the sub-regions of the first image, and the magnification scale is the base scale at different magnifications.

[0051] Further, the scale refers to the size of the selected image in the first image. For example, the base scale is: scale 1 (25μm × 25μm, base scale); the scaling scales are: scale 2 (125μm × 125μm, base scale × 5), scale 3 (250μm × 250μm, base scale × 10), scale 4 (375μm × 375μm, base scale × 15), scale 5 (500μm × 500μm, base scale × 20), scale 6 (625μm × 625μm, base scale × 25), scale 7 (750μm × 750μm, base scale × 30), and scale 8 (1000μm × 1000μm, base scale × 40). That is, scales 2 through 8 are multiples of scale 1.

[0052] The third image is any image selected from at least one second image of the corresponding scale.

[0053] The second porosity is the proportion of the area of ​​pores within the target shale sample in the third image to the total area of ​​the third image.

[0054] Specifically, a first reference scale is selected from the candidate scales, and a first image is selected based on the first reference scale to obtain at least one second image of the corresponding scale. An image is arbitrarily selected from the second images as a third image, and pores in the third image are extracted. The total area of ​​the extracted pores is calculated, and the calculated area is divided by the area of ​​the third image to obtain the second aperture ratio.

[0055] Furthermore, the first reference scale is selected in the order of scale 1 to scale 8.

[0056] Furthermore, after determining the second face value of the third image, a new image is selected from the second image as the third image, and the second face value of the newly selected third image is determined. This process continues until all images in the second image have participated in the calculation and the corresponding second face values ​​are obtained, at which point at least one second face value is obtained.

[0057] For example, at scale 1, 1600 second images can be obtained, corresponding to 1600 second face rates; at scale 2, 64 second images can be obtained, corresponding to 64 second face rates; at scale 3, 16 second images can be obtained, corresponding to 16 second face rates; at scale 4, 9 second images can be obtained, corresponding to 9 second face rates; at scale 5, 4 second images can be obtained, corresponding to 4 second face rates; at scale 6, 4 second images can be obtained, corresponding to 4 second face rates; at scale 7, 4 second images can be obtained, corresponding to 4 second face rates; and at scale 8, 1 second image can be obtained, corresponding to 1 second face rate.

[0058] For example, when the scale is scale 1, that is, the scale size is 25μm×25μm, selecting the first image at scale 1 can yield 1600 second images, such as... Figure 2 As shown. Using AVIZO image processing software, the watershed method was employed to identify and extract pores in each image, determining the face ratio of each image as: x i j (x 1 1. x 1 2, x 1 3、……、x 1 40 x 2 1. x 2 2, x 2 3、……、x 2 40 x 3 1. x 3 2, x 3 3、……、x 3 40 , ..., x 40 1. x 40 2, x 40 3、……、x 40 40 (). Where i represents the row number of a single image after scanning using MAPS image acquisition and stitching technology, and j represents the column number of a single image, i = {1, 40}, j = {1, 40}. For ease of calculation, k and l are named the row and column at the current scale, respectively, and a i j b i j c i j d i j e i j f i j g i j h represents the second face ratio at scales 1 to 8.

[0059] Furthermore, the aperture ratio of the second aperture corresponding to scale 1 (25μm×25μm) is directly taken as a. k l =x i j There are 1600 second face rates. Here, k represents the row number of the image at scale 1, and l represents the column number of the image, k = i, l = j.

[0060] For example, when the scale is scale 2, that is, the scale size is 125μm×125μm, the first image is selected by scale 2, such as... Figure 3 As shown, by taking 25 reference images of size 25μm×25μm as a selection unit, 64 second images can be obtained. Using AVIZO image processing software, a total of 64 second aperture values ​​corresponding to scale 2 can be obtained. Taking the second aperture value corresponding to scale 2 (125μm×125μm) as b... k l =sum x i j Where k represents the row number of the image at scale 2, l represents the column number of the image, k = {1, 8}, l = {1, 8}, i = {5(k-1), 5k}, j = {5(l-1), 5l}. This is equivalent to b. 1 1 = average(x) 1 1. x 1 2、……、x 1 5,x 2 1. x 2 2、……、x 2 5, ..., x 5 1. x 5 2、……、x 5 5) b 1 2 = average(x) 1 6. x 1 7、……、x 1 10 x 2 6. x 2 7、……、x 2 10 , ..., x 5 6. x 5 7、……、x 5 10 b 1 3 = average(x) 1 11 x 1 12 ... x 1 15 x 2 11 x 2 12 ... x 2 15 , ..., x 5 11 x 5 12 ... x 5 15 ), ..., b 88 = average(x) 36 36 x 36 37 ... x 36 40 x 37 36 x 37 37 ... x 37 40 , ..., x 40 36 x 40 37 ... x 40 40 ).

[0061] For example, when the scale is scale 3, that is, the scale size is 250μm×250μm, the first image is selected by scale 1, such as... Figure 4 As shown, by taking 100 reference images of size 25μm×25μm as a selection unit, 16 second images can be obtained. Using AVIZO image processing software, a total of 16 second aperture values ​​corresponding to scale 3 can be obtained. Taking the second aperture value corresponding to scale 3 (250μm×250μm) as c... k l =sum x i j Where k represents the row number of the image at scale 3, l represents the column number of the image, k = {1, 4}, l = {1, 4}, i = {10(k-1), 10k}, j = {10(l-1), 10l}, as shown Figure 5 As shown, c k l Includes: C 1 1. C 1 2. C 1 3. C 1 4. C 2 1. C 2 2. C 2 3. C 2 4. C 3 1. C 3 2. C 3 3. C 3 4. C 4 1. C 4 2. C 4 3. C 4 4, where c 1 1 = average(x) 1 1. x 1 2、……、x 1 10 x2 1. x 2 2、……、x 2 10 , ..., x 10 1. x 10 2、……、x 10 10 ), c 1 2 = average(x) 1 11 x 1 12 ... x 1 20 x 2 11 x 2 12 ... x 2 20 , ..., x 11 11 x 11 12 ... x 11 20 ), ..., c 4 4 = average(x) 31 31 x 31 32 ... x 31 40 x 32 31 x 32 32 ... x 32 40 , ..., x 40 31 x 40 32 ... x 40 40 Furthermore, Figure 5 Also includes C 2 4. By those x i j composition.

[0062] For example, when the scale is scale 4, i.e., the scale size is 375μm × 375μm, selecting the first image at scale 4 yields 9 second images. Using AVIZO image processing software, a total of 9 second aperture values ​​corresponding to scale 4 can be obtained. Let d be the second aperture value corresponding to scale 4 (375μm × 375μm). k l =sum x i jWhere k represents the row number of the image at scale 4, and l represents the column number of the image, k = {1, 3}, l = {1, 3}. When k, l = 1, i, j = {1, 15}; when k, l = 2, i, j = {14, 28}; when k, l = 3, i, j = {26, 40}.

[0063] For example, when the scale is scale 5, i.e., the scale size is 500μm × 500μm, selecting the first image at scale 5 yields 4 second images. Using AVIZO image processing software, a total of 4 second aperture values ​​corresponding to scale 5 can be obtained. Taking the second aperture value corresponding to scale 5 (500μm × 500μm) as e... k l =sum x i j , where k represents the row number of the image under scale 5, l represents the column number of the image, k = {1, 2}, l = {1, 2}, i = {20(k-1), 20k}, j = {20(l-1), 20l}.

[0064] For example, when the scale is scale 6, i.e., the scale size is 625μm × 625μm, selecting the first image at scale 6 yields 4 second images. Using AVIZO image processing software, a total of 4 facets of the second facets corresponding to scale 6 can be obtained. Taking the facet of the second facets corresponding to scale 6 (625μm × 625μm) as f... k l =sum x i j Where k represents the row number of the image at scale 6, and l represents the column number of the image, k = {1, 2}, l = {1, 2}. When k, l = 1, i, j = {1, 25}; when k, l = 2, i, j = {15, 40}.

[0065] For example, when the scale is scale 7, i.e., the scale size is 750μm × 750μm, selecting the first image at scale 7 yields 4 second images. Using AVIZO image processing software, a total of 4 second aperture values ​​corresponding to scale 7 can be obtained. Let g be the second aperture value corresponding to scale 7 (750μm × 750μm). k l =sum x i j Where k represents the row number of the image at scale 7, and l represents the column number of the image, k = {1, 2}, l = {1, 2}. When k, l = 1, i, j = {1, 35}; when k, l = 2, i, j = {5, 40}.

[0066] For example, when the scale is scale 8, that is, the scale size is 1000μm×1000μm, the first image is selected by scale 8, such as... Figure 6 As shown, by taking 1600 reference images of size 25μm×25μm as a selection unit, one second image can be obtained. The face density h of the second face density is the face density of the first face density.

[0067] S130. Determine the target face rate error based on the first face rate and at least one second face rate, and determine the face rate distribution state based on at least one second face rate.

[0068] Among them, the target face rate error is used to characterize the mean of the error between the first face rate and at least one second face rate.

[0069] Among them, the face rate distribution state is used to characterize the distribution state of the second face rate.

[0070] Specifically, the error between at least one second face rate and the first face rate is calculated to obtain the reference face rate error, and the average of the reference face rate error is obtained to obtain the standard face rate error. A face rate distribution diagram is drawn based on at least one second face rate; the face rate distribution state is determined based on the distribution of the second face rates in the distribution diagram.

[0071] Furthermore, a face rate distribution map, such as Figure 7 As shown in the figure, the face rate distribution at scales 1, 2, 3, and 4 is relatively dispersed, while the face rate distributions at scales 5, 6, and 7 are relatively concentrated.

[0072] S140. Determine the second reference scale based on the target face rate error and face rate distribution state corresponding to different first reference scales, and determine the target scale based on the second reference scale.

[0073] The target scale enables the captured second image to accurately reflect the overall characteristics of the target shale sample.

[0074] Specifically, the target face rate errors corresponding to different first reference scales are selected based on the face rate distribution. The selected target face rate errors are then filtered based on the face rate distribution, and the scales corresponding to the target face rate errors with the most concentrated face rate distribution are used as the second reference scales. The target scale is then determined based on the second reference scales.

[0075] Optionally, before determining the first image of the target shale sample, steps A1-A2 are also included:

[0076] Step A1: Segment the reference shale sample and grind and polish it to obtain the shale sample to be processed.

[0077] Specifically, reference shale samples were collected from the shale reservoir. The shale samples were cut into relatively flat and appropriately sized 1cm×1cm×2mm cubes, which were then manually finely ground with 800-grit, 1000-grit, and 2000-grit sandpaper, and then polished circumferentially using an argon ion polisher.

[0078] The above steps, including segmenting and polishing the reference shale sample, are to ensure that the surface of the shale sample to be treated is smooth, thus guaranteeing the success of carbon plating.

[0079] Step A2: Carbon plating is performed on the shale sample to be processed to obtain the target shale sample.

[0080] Specifically, the shale sample to be treated is carbonized according to the carbonization method to obtain the target shale sample.

[0081] Among them, carbon plating methods can be vacuum evaporation coating, which involves heating carbon materials to evaporation temperature in a high vacuum environment, causing the carbon materials to vaporize and deposit on the surface of the shale sample to be treated; sputtering coating, which uses high-energy particles (such as argon ions) to bombard a carbon target, causing carbon atoms to be sputtered from the target surface and deposited on the surface of the shale sample to be treated; and ion plating, which accelerates carbon ions under the action of an electric field and deposits them on the surface of the shale sample to be treated.

[0082] The above steps allow carbon plating to form a conductive layer on the surface of the shale sample to be treated, enabling electrons to flow smoothly on the carbon-plated target shale sample, thereby improving the clarity and resolution of the image during image acquisition.

[0083] Optionally, the first face proportion is determined based on the first image, including steps B1-B3:

[0084] Step B1: Extract the pores contained in the first image to obtain the first pore image.

[0085] Specifically, the pores contained in the first image are extracted using AVIZO image processing software to obtain the first pore image.

[0086] Step B2: Determine the area of ​​the first pore based on the first pore image.

[0087] The area of ​​the first pore is the sum of the areas of all pores in the first image.

[0088] Specifically, based on the pores extracted from the first pore image, the contours of the pores are drawn using AVIZO image processing software, and the pore radius is determined based on the pore contour. The area of ​​the pore is determined based on the obtained pore radius, and the area of ​​all pores in the first image is summed to obtain the area of ​​the first pore.

[0089] Step B3: Determine the first aperture ratio based on the ratio of the first aperture area to the first image area.

[0090] Specifically, the area of ​​the first pore is divided by the area of ​​the first image to obtain the first aperture ratio.

[0091] Optionally, the face ratio of the second face is determined based on the third image, including steps C1-C3:

[0092] Step C1: Extract the pores contained in the third image to obtain at least one second pore image.

[0093] Specifically, the pores contained in the third image are extracted using AVIZO image processing software to obtain at least one second pore image.

[0094] Step C2: Determine the area of ​​the second pore based on at least one second pore image.

[0095] The area of ​​the second pore is the sum of the areas of all pores in the third image.

[0096] Specifically, based on the pores extracted from the second pore image, the contours of the pores are drawn using AVIZO image processing software, and the pore radius is determined based on the pore contour. The area of ​​the pore is determined based on the obtained pore radius, and the area of ​​all pores in the third image is summed to obtain the area of ​​the second pore.

[0097] Step C3: Determine the aperture ratio of the second pore based on the ratio of the area of ​​the second pore to the area of ​​the third image.

[0098] Specifically, the area of ​​the second pore is divided by the area of ​​the third image to obtain the second pore ratio.

[0099] Optionally, the area of ​​the first pore is determined based on the first pore image, including steps D1-D3:

[0100] Step D1: Extract the reference pore profile from the first pore image.

[0101] Specifically, pores are extracted from the first pore image using AVIZO image processing software, and the pore contours are drawn to obtain a reference pore contour.

[0102] Step D2: Determine the reference pore radius based on the reference pore profile, and determine the reference pore area based on the reference pore radius.

[0103] Specifically, the shape of the pore profile is determined based on the reference pore profile, the radius of the reference pore is determined based on the shape of the profile, and the area of ​​the reference pore is determined based on the radius of the reference pore and the shape of the profile.

[0104] Furthermore, the reference pore radius is determined based on the shape of the profile by: determining the distance between the two endpoints of the pore based on the shape of the profile, and then determining the reference pore radius based on this distance. For example, suppose the profile is a circle. Then the radius of the circle is used as the reference pore radius.

[0105] Step D3: Determine the first pore area based on at least one reference pore area.

[0106] Specifically, the first pore area is obtained by summing up all the reference pore areas.

[0107] Furthermore, the second pore area is determined in the same way as the first pore area, which will not be elaborated here.

[0108] Optionally, the target face ratio error is determined based on the first face ratio and at least one second face ratio, including steps E1-E2:

[0109] Step E1: Determine the reference face rate error based on the first face rate and the second face rate.

[0110] The reference face rate error is used to characterize the difference between the first face rate and the second face rate.

[0111] Specifically, the difference between the first face rate and the second face rate is calculated and divided by the first face rate to obtain the reference face rate error.

[0112] For example, the reference face rate error can be calculated using the following formula:

[0113] Mi = |(First Face Percentage - Second Face Percentage) / First Face Percentage| × 100%

[0114] Step E2: Average the face rate error of at least one reference face to obtain the face rate error of the target face.

[0115] Specifically, the target face face error is obtained by averaging the calculated face face rate errors of at least one reference face.

[0116] For example, the target face rate error can be calculated using the following formula:

[0117]

[0118] Where Mi is the reference face rate error; n is the number of reference face rate errors.

[0119] Optionally, a second reference scale is determined based on the target face area error and face area distribution state corresponding to different first reference scales, and the target scale is determined based on the second reference scale, including steps F1-F4:

[0120] Step F1: Determine the scale to be judged based on the face rate distribution.

[0121] Specifically, the scale where the face rate distribution is relatively concentrated is used as the scale to be judged.

[0122] For example, such as Figure 7 As shown, the face rate distribution states corresponding to scale 5, scale 6, and scale 7 are relatively concentrated, so scale 5, scale 6, and scale 7 are used as the scales to be judged.

[0123] Step F2: Compare the target face rate error corresponding to the scale to be judged with the preset error.

[0124] The preset error is determined based on the actual rock structure within the shale reservoir. An example preset error could be 10%.

[0125] For example, assuming the target face rate error at scale 5 is 19.14%; the target face rate error at scale 6 is 7.09%; and the target face rate error at scale 7 is 4.94%, the target face rate errors at scales 5, 6, and 7 are compared with 10%.

[0126] Step F3: If the target surface rate error corresponding to the scale to be judged is less than the preset error, then the corresponding scale to be judged is used as the second reference scale.

[0127] Specifically, if the target surface rate error corresponding to the scale to be judged is less than the preset error, the target surface rate error will use the scale to be judged based on the preset error as the second reference scale.

[0128] For example, assuming the target face rate error of scale 5 is 19.14%; the target face rate error of scale 6 is 7.09%; the target face rate error of scale 7 is 4.94%; and the preset error is 10%, then the second reference scales are scale 6 and scale 7.

[0129] Step F4: Determine the target scale based on the second reference scale.

[0130] Specifically, the smallest scale in the second reference scale is taken as the target scale.

[0131] For example, multiple blocky shale samples from the upper section of Group B in region A are selected and cut into relatively flat and appropriately sized cubes of 1cm × 1cm × 2mm. After grinding and polishing, they are carbonized to obtain the target shale samples. The target shale samples are then scanned and images acquired using a MAPS image acquisition system. Figure 8 The image shown is a large-scale square field-of-view image composed of 1600 25μm×25μm images acquired using the MAPS image acquisition system, i.e., the first image. Selecting scale 1 (25μm×25μm), and selecting from the first image using scale 1, yields 1600 second images, as shown below. Figure 9 As shown, the AVIZO image processing software was used to identify and extract pores in each image using the watershed method. The image after pore extraction is shown below. Figure 10 As shown in Table 1, the second face values ​​of the 1600 extracted images were statistically processed, and the second face values ​​of scales 2-8 were calculated based on the second face value corresponding to scale 1. The results are as follows: there are 64 data points for scale 2 (125μm×125μm), 16 data points for scale 3 (250μm×250μm), 9 data points for scale 4 (375μm×375μm), 4 data points for scale 5 (500μm×500μm), 4 data points for scale 6 (625μm×625μm), 4 data points for scale 7 (750μm×750μm), and 1 data point for scale 8 (1000μm×1000μm).

[0132] Table 1. Rate of at least one second face at different scales

[0133]

[0134]

[0135] Furthermore, a schematic diagram of the face proportion distribution is drawn for at least one second face proportion corresponding to different scales, such as... Figure 11 As shown, the data gradually converges from scale 1 to scale 8. The porosity distribution at scale 5 is 0.186, with an error of 19.14% compared to scale 8; the porosity distribution at scale 6 is 0.070, with an error of 7.09% compared to scale 8; and the porosity distribution at scale 7 is 0.045, with an error of 4.94% compared to scale 8. The analysis results of the porosity distribution at scale 5 show that its error is too large, while the errors of scales 6 and 7 compared to scale 8 are both less than 10%. Based on this analysis, scale 6 is determined to be the representative scale of the large-scale image that concentrates the data and can reflect the overall phenomenon. Therefore, scale 6 is determined as the target scale for shale reservoir porosity.

[0136] The technical solution of this embodiment involves determining a first image of the target shale sample and determining a first porosity based on the first image; determining a first reference scale from candidate scales; selecting at least one second image of the first image based on the first reference scale to obtain at least one second image of the corresponding scale; determining a third image based on the at least one second image of the corresponding scale and determining a second porosity based on the third image; determining a target porosity error based on the first porosity and at least one second porosity; and determining the porosity distribution state based on at least one second porosity. The determination of the target porosity error and porosity distribution state provides a basis for the selection of the target scale. Determining a second reference scale based on the target porosity error and porosity distribution state corresponding to different first reference scales, and then determining the target scale based on the second reference scale, ensures the accuracy of the target scale. This method ensures that the porosity in the second image selected based on the target scale reflects the porosity state in the first image of the target shale, thus ensuring the effectiveness of reservoir porosity evaluation while reducing the amount of data collected from images and the computational load during analysis.

[0137] Figure 12 This is a schematic diagram of a shale reservoir processing device provided in an embodiment of the present invention. This embodiment is applicable to determining the appropriate segmentation scale of shale samples during analysis. The shale reservoir processing device can be implemented in hardware and / or software, and can be configured in any electronic device with network communication capabilities. Figure 12 As shown, the device includes: a first surface area ratio determination module 210, a second surface area ratio determination module 220, a target surface area ratio error determination module 230, and a target size determination module 240, wherein:

[0138] First porosity determination module 210: used to determine the first image of the target shale sample and determine the first porosity based on the first image. The first image is an image obtained by stitching together the target shale sample after scanning it in different regions. The target shale sample is a shale sample after polishing and carbonizing a reference shale sample. The reference shale sample is shale rock collected from a shale reservoir. The first porosity is the ratio of the area of ​​pores in the target shale sample in the first image to the area of ​​the first image.

[0139] Second porosity determination module 220: used to determine a first reference scale from candidate scales, select a first image according to the first reference scale to obtain at least one second image of the corresponding scale, determine a third image according to the at least one second image of the corresponding scale, and determine the second porosity according to the third image. The candidate scales include: a base scale and a magnification scale. The base scale is determined according to the size of the sub-regions of the first image. The magnification scale is the base scale at different magnifications. The third image is any image selected from at least one second image of the corresponding scale. The second porosity is the proportion of the area of ​​pores in the target shale sample in the third image to the area of ​​the third image.

[0140] Target face rate error determination module 230: used to determine the target face rate error based on the first face rate and at least one second face rate, and to determine the face rate distribution state based on at least one second face rate. The target face rate error is used to characterize the mean of the error between the first face rate and at least one second face rate, and the face rate distribution state is used to characterize the distribution state of the second face rate.

[0141] Target scale determination module 240: used to determine the second reference scale based on the target surface area error and surface area distribution state corresponding to different first reference scales, and to determine the target scale based on the second reference scale. The target scale enables the captured second image to accurately reflect the overall characteristics of the target shale sample.

[0142] Optionally, the shale reservoir processing unit also includes:

[0143] Shale sample determination module: used to segment and polish the reference shale sample to obtain the shale sample to be processed;

[0144] Target shale sample determination module: used to perform carbon plating treatment on the shale sample to be processed to obtain the target shale sample.

[0145] Optionally, the first face rate determination module 210 includes:

[0146] First pore image determination unit: used to extract the pores contained in the first image to obtain the first pore image;

[0147] First pore area determination unit: used to determine the first pore area based on the first pore image, wherein the first pore area is the sum of the areas of all pores in the first image;

[0148] First aperture ratio determination unit: used to determine the first aperture ratio based on the ratio of the area of ​​the first aperture to the area of ​​the first image.

[0149] Optionally, the second face rate determination module 220 includes:

[0150] Second pore image determination unit: used to extract pores contained in the third image to obtain at least one second pore image;

[0151] Second pore area determination unit: used to determine the second pore area based on at least one second pore image, wherein the second pore area is the sum of the areas of all pores in the third image;

[0152] Second aperture ratio determination unit: used to determine the second aperture ratio based on the ratio of the area of ​​the second aperture to the area of ​​the third image.

[0153] Optionally, the first pore area determining unit includes:

[0154] Second pore profile determination subunit: used to extract reference pore profile from the first pore image;

[0155] Reference pore area determination sub-unit: used to determine the reference pore radius based on the reference pore profile, and to determine the reference pore area based on the reference pore radius;

[0156] Second pore area determination subunit: used to determine the first pore area based on at least one reference pore area.

[0157] Optionally, the target face rate error determination module 230 includes:

[0158] Reference face rate error determination unit: used to determine the reference face rate error based on the first face rate and the second face rate, the reference face rate error being used to characterize the difference between the first face rate and the second face rate;

[0159] Target face surface rate error determination unit: used to average the face surface rate error of at least one reference face surface to obtain the target face surface rate error.

[0160] Optionally, the target scale determination module 240 includes:

[0161] Unit for determining the scale to be judged: used to determine the scale to be judged based on the face rate distribution.

[0162] Comparison unit: used to compare the target face rate error corresponding to the scale to be judged with a preset error;

[0163] Second reference scale determination unit: If the target surface area error corresponding to the scale to be judged is less than the preset error, then the corresponding scale to be judged will be used as the second reference scale.

[0164] Target scale determination unit: used to determine the target scale based on the second reference scale.

[0165] The shale reservoir treatment device provided in this embodiment of the invention can perform the shale reservoir treatment method provided in any of the above embodiments of the invention, and has the corresponding functions and beneficial effects of performing the shale reservoir treatment method. For details, please refer to the relevant operations of the shale reservoir treatment method in the foregoing embodiments.

[0166] Figure 13 This is a schematic diagram of an electronic device for implementing the shale reservoir processing method according to embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0167] like Figure 13 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0168] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0169] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as shale reservoir processing methods.

[0170] In some embodiments, the shale reservoir processing method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded into and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the shale reservoir processing method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the shale reservoir processing method by any other suitable means (e.g., by means of firmware).

[0171] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0172] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0173] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0174] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0175] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0176] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0177] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0178] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for treating shale reservoirs, characterized in that, include: A first image of a target shale sample is determined, and a first porosity is determined based on the first image. The first image is an image obtained by scanning the target shale sample in different regions and then stitching them together. The target shale sample is a shale sample that has been polished and carbonized with a reference shale sample. The reference shale sample is shale rock collected from a shale reservoir. The first porosity is the ratio of the area of ​​pores in the target shale sample in the first image to the area of ​​the first image. A first reference scale is determined from the candidate scales. A first image is selected based on the first reference scale to obtain at least one second image of the corresponding scale. A third image is determined based on the at least one second image of the corresponding scale, and a second porosity is determined based on the third image. The candidate scales include a base scale and a magnification scale. The base scale is determined based on the size of the sub-regions of the first image. The magnification scale is the base scale at different magnifications. The third image is any image selected from the at least one second image of the corresponding scale. The second porosity is the proportion of the area of ​​pores in the target shale sample in the third image to the area of ​​the third image. A target face rate error is determined based on the first face rate and at least one second face rate, and a face rate distribution state is determined based on at least one second face rate. The target face rate error is used to characterize the mean of the error between the first face rate and at least one second face rate, and the face rate distribution state is used to characterize the distribution state of the second face rate. A second reference scale is determined based on the target face rate error and the face rate distribution state corresponding to different first reference scales, and a target scale is determined based on the second reference scale. The target scale enables the captured second image to accurately reflect the overall characteristics of the target shale sample.

2. The method according to claim 1, characterized in that, Before determining the first image of the target shale sample, the method further includes: The reference shale sample was segmented and then polished to obtain the shale sample to be processed. The shale sample to be processed was carbonized to obtain the target shale sample.

3. The method according to claim 1, characterized in that, Determining the first face proportion based on the first image includes: The pores contained in the first image are extracted to obtain the first pore image; The first pore area is determined based on the first pore image, and the first pore area is the sum of the areas of all pores in the first image; The first aperture ratio is determined based on the ratio of the first aperture area to the first image area.

4. The method according to claim 1, characterized in that, Determining the face ratio of the second face based on the third image includes: The pores contained in the third image are extracted to obtain at least one second pore image; The second pore area is determined based on the at least one second pore image, and the second pore area is the sum of the areas of all pores in the third image; The second aperture ratio is determined based on the ratio of the area of ​​the second pore to the area of ​​the third image.

5. The method according to claim 3, characterized in that, Determining the first pore area based on the first pore image includes: Extract the reference pore profile from the first pore image; The reference pore radius is determined based on the reference pore profile, and the reference pore area is determined based on the reference pore radius; The first pore area is determined based on at least one reference pore area.

6. The method according to claim 1, characterized in that, The step of determining the target face ratio error based on the first face ratio and at least one second face ratio includes: A reference face rate error is determined based on the first face rate and the second face rate, and the reference face rate error is used to characterize the difference between the first face rate and the second face rate; The target face face error is obtained by averaging the face face errors of at least one reference face.

7. The method according to claim 1, characterized in that, The step of determining a second reference scale based on the target face rate error corresponding to different first reference scales and the face rate distribution state, and determining the target scale based on the second reference scale, includes: The criteria to be judged are determined based on the distribution of face rate. The target face rate error corresponding to the scale to be judged is compared with the preset error; If the target face rate error corresponding to the scale to be judged is less than the preset error, then the corresponding scale to be judged will be used as the second reference scale. The target scale is determined based on the second reference scale.

8. A shale reservoir processing device, characterized in that, include: The first porosity determination module is used to determine a first image of a target shale sample and determine a first porosity based on the first image. The first image is an image obtained by scanning the target shale sample in different regions and then stitching them together. The target shale sample is a shale sample after polishing and carbonizing a reference shale sample. The reference shale sample is shale rock collected from a shale reservoir. The first porosity is the ratio of the area of ​​pores in the target shale sample in the first image to the area of ​​the first image. The second aperture ratio determination module is used to determine a first reference scale from candidate scales, select a first image according to the first reference scale to obtain at least one second image of the corresponding scale, determine a third image according to the at least one second image of the corresponding scale, and determine the second aperture ratio according to the third image. The candidate scales include a base scale and a magnification scale. The base scale is determined according to the size of the sub-regions of the first image. The magnification scale is the base scale at different magnifications. The third image is any image selected from the at least one second image of the corresponding scale. The second aperture ratio is the proportion of the area of ​​pores in the target shale sample in the third image to the area of ​​the third image. The target face rate error determination module is used to determine the target face rate error based on the first face rate and at least one second face rate, and to determine the face rate distribution state based on at least one second face rate. The target face rate error is used to characterize the mean of the error between the first face rate and at least one second face rate, and the face rate distribution state is used to characterize the distribution state of the second face rate. The target scale determination module is used to determine a second reference scale based on the target face rate error and the face rate distribution state corresponding to different first reference scales, and to determine the target scale based on the second reference scale. The target scale enables the captured second image to accurately reflect the overall characteristics of the target shale sample.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the shale reservoir processing method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the shale reservoir processing method according to any one of claims 1-7.

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