A method for characterizing the pore structure of rocks

Abstract

The present invention provides a method for characterizing the pore structure of rocks. First, different types of image acquisition methods are used to characterize the pore characteristics at different scales. Then, the pore volumes of the overlapping parts with intermediate precision between the images at different scales are calibrated to achieve the characterization of the full-scale pore structure of rock samples. The concept of the present invention is reasonable, integrating pore characterization means at different scales, capable of obtaining the total porosity of pores at all scales, realizing the characterization of the pore results of rocks at different scales, and accurately quantifying the porosity and pore distribution at the millimeter, micrometer, and nanometer scales.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration, and particularly relates to a method for characterizing the pore structure of rocks. Background Art

[0002] The pores inside rocks are the spaces for storing substances such as oil and natural gas. The size and distribution characteristics of the pore structure directly affect the formulation of development plans for resources such as oil and natural gas.

[0003] At present, there are many types of evaluation methods for the pore structure of rocks, which can be generally divided into two categories. One is indirect measurement based on physical rules, and this type of method is typically represented by mercury intrusion testing. The other is direct observation based on various images of rocks, and this type of method is represented by optical thin section images, X-ray CT images, and scanning electron microscopy images, etc.

[0004] Existing evaluation methods for the pore structure of rocks are difficult to characterize the true structure of rocks or can only characterize the pore structure within a certain range, and it is difficult to comprehensively characterize the pore structures at different scales of rocks. For example, the mercury intrusion method equates the internal structure of pores to regular cylindrical shapes, and takes the volume of the throat and the connected pores as a whole, and equates it to the volume of a cylindrical sample. Optical thin sections can only identify pore structures at the micron scale and are difficult to characterize dense rock samples. The area of X-ray CT images is small and can only characterize micron-scale pores in large areas or nano-scale pores in small areas. Scanning electron microscope images can identify nano-scale rock images, but due to existing experimental conditions, the overall area is still small.

[0005] In summary, it is necessary to further innovate the existing technology. Summary of the Invention

[0006] In view of the technical problems existing in the above background art, the present invention proposes a method for characterizing the pore structure of rocks, which has a reasonable concept, integrates pore characterization means at different scales, can obtain the total porosity of pores at all scales, can realize the characterization of the pore structure of rocks at different scales, and can accurately quantify the porosity and pore distribution at the millimeter scale, micron scale, and nano scale.

[0007] To solve the above technical problems, a method for characterizing the pore structure of rocks provided by the present invention first uses different types of image acquisition methods to characterize the pore characteristics at different scales, and then calibrates the pore volume of the overlapping part with intermediate precision between the images at different scales to realize the characterization of the full-scale pore structure of rock samples.

[0008] The method for characterizing the pore structure of rocks, wherein the characterization method specifically includes the following steps:

[0009] (1) Conduct industrial CT scanning on rock samples to obtain millimeter-scale pore images and the pore structure characteristics at this scale;

[0010] (2) Conduct micro-CT scanning on the rock sample to obtain micro-scale pore images and pore structure characteristics at this scale;

[0011] (3) Conduct nano-CT scanning on the rock sample to obtain nano-scale pore images and pore structure characteristics at this scale;

[0012] (4) Based on the nano-scale pore images and pore structure characteristics obtained in the above step (3), perform porosity calculation and multi-scale pore distribution fusion.

[0013] The rock pore structure characterization method, wherein the step (1) specifically includes the following steps:

[0014] (1.1) Place the rock on an industrial CT instrument, and after setting the scanning parameters, obtain the industrial-grade CT image of the rock;

[0015] (1.2) After obtaining the industrial-grade CT image of the core, conduct image segmentation and processing, extract the pore and fracture spaces, equivalent the irregular sample volume to the volume of a sphere as the equivalent sphere, take the radius of the equivalent sphere as the pore radius, and calculate the pore radius and fracture width;

[0016] (1.3) Conduct image segmentation on the industrial-grade CT image, divide it into a pore part where pores can be clearly identified, a solid phase part that can be clearly identified as such, and a pore-containing area with a gray value between the pore part and the solid phase part according to different gray levels, and statistically obtain the proportion of pore volume in the pore part and the pore size distribution.

[0017] The rock pore structure characterization method, wherein: in the process of calculating the pore radius in the step (1.2), for a certain pore, take the sum V of all voxels as the volume of the sphere, and the relationship between the radius of the sphere and the volume is V=(4 / 3)*Π*R 3 , and the equivalent sphere radius R is the pore radius.

[0018] The rock pore structure characterization method, wherein: the scanning voxel of the industrial-grade CT image in the step (1.1) is 50 - 600um; the pore part divided in the industrial-grade CT image in the step (1.3) is the millimeter-scale pore characteristics of the rock.

[0019] The rock pore structure characterization method, wherein the specific steps of the step (2) are as follows:

[0020] (2.1) Based on the industrial-grade CT image obtained in the above step (1.1), drill a plug sample core in a representative area;

[0021] (2.2) Place the plunger-like core on a micro-CT scanning instrument. After setting the scanning parameters, obtain the micro-scale CT images of the rock;

[0022] (2.3) Perform image processing and segmentation on the obtained micro-scale CT images of the core. According to the different gray levels, divide the pore part where pores can be clearly identified, the solid phase part that can be clearly identified, and the pore-containing area with gray values between the pore part and the solid phase part;

[0023] (2.4) For the pore and fracture spaces extracted in the step (1.2), calculate the pore radius and fracture width based on the equivalent sphere, calculate the pore volume fraction and pore size distribution in the micro-scale CT image. The distinction between pores and fractures is based on the aspect ratio. The extracted volume with a length or width greater than 10 is considered a fracture, and the rest are pores.

[0024] For the method for characterizing the pore structure of the rock, wherein: in the step (2.1), the diameter of the plunger-like core is 10 - 25 mm, and the length is 2 - 5 cm; in the step (2.2), the scanning voxel of the micro-scale CT image is 0.5 - 10 μm; in the step (2.3), the pore part divided from the micro-scale CT image is the micro-scale pore characteristic of the rock.

[0025] For the method for characterizing the pore structure of the rock, wherein the specific steps of the step (3) are as follows:

[0026] (3.1) Based on the micro-scale CT image obtained in the above step (2.2), select a representative area and cut out a core sub-sample;

[0027] (3.2) Place the core sub-sample on a nano-CT scanning instrument. After setting the scanning parameters, obtain the nano-scale CT image of the rock;

[0028] (3.3) Perform image processing and segmentation on the obtained nano-scale CT image of the rock in the above step (3.2). According to the different gray levels, divide the pore part where pores can be clearly identified and the part that can be clearly identified as the solid phase;

[0029] (3.4) For the extracted pore and fracture spaces, calculate the pore radius and fracture width based on the equivalent sphere, and calculate the pore volume fraction and pore size distribution in the micro-scale CT image.

[0030] For the method for characterizing the pore structure of the rock, wherein: in the step (3.1), a core sub-sample with a diameter of 50 - 100 μm and a length of 100 μm is cut out by using laser cutting technology; in the step (3.2), the scanning voxel of the nano-scale CT image is 50 - 65 nm; in the step (3.3), the pore part divided is the nano-scale pore characteristic of the rock.

[0031] The rock pore structure characterization method, wherein the step (4) specifically includes the following steps:

[0032] (4.1) Porosity calculation

[0033] The porosity value P of the whole rock is the sum of porosities at different scales, that is, P = P 10 +P 11 *P 20 +P 21 *P 30 ; where P is the total porosity, P 10 is the proportion of pores at the millimeter scale, P 11 is the pore-containing area in the millimeter-scale rock image, P 20 is the proportion of pores in the micrometer-scale rock image, P 21 is the proportion of the pore-containing area in the micrometer-scale rock image, P 30 is the proportion of pores in the nanometer-scale rock image;

[0034] (4.2) Pore distribution fusion

[0035] After the pore proportions at different scales are counted, only the distribution part with the minimum pore diameter greater than 1 mm is retained in the pore part of the millimeter-scale rock image, the pore part of the micrometer-scale rock image retains the pore diameter distribution part of 1 μm - 2 mm, and the pore part of the nanometer-scale rock image retains the pore diameter distribution part less than 1 μm; according to the pore proportions at the three scales, the overall proportions of different pore sizes are adjusted, and the adjusted pore proportions at different scales are combined to ensure that the sum of all proportions is 100%.

[0036] Adopting the above technical solution, the present invention has the following beneficial effects:

[0037] The rock pore structure characterization method of the present invention is reasonably conceived, integrates pore characterization means at different scales, can obtain the total porosity of pores at all scales, can realize the characterization of rock pore results at different scales, and can accurately quantify the porosity and pore distribution at the millimeter, micrometer, and nanometer scales.

[0038] Compared with the prior art where different scales are separated, the present invention can achieve the fusion of different scales, more accurately understand the overall pore characteristics of oil and gas reservoirs, provide strong support for clarifying underground geological processes and realizing precise exploration of oil and gas; the fine quantitative characterization of pores at different scales in the present invention can provide a basis for formulating an efficient oil and gas exploitation plan and improve the exploitation efficiency. Description of the drawings

[0039] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the accompanying drawings required for the description of the specific embodiments or the prior art. Obviously, the accompanying drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0040] Figure 1 Schematic diagram showing different parts of the rock micro-CT image involved in the rock pore structure characterization method of the present invention;

[0041] Figure 2 Schematic diagram showing the pore distribution of rocks at different scales and the fused pore distribution involved in the rock pore structure characterization method of the present invention;

[0042] Figure 3 Chart showing the proportion of pores at different scales involved in the rock pore structure characterization method of the present invention. Specific embodiments

[0043] The following will clearly and completely describe the technical solutions of the present invention with reference to the accompanying drawings. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0044] The following further explains and illustrates the present invention in combination with specific embodiments.

[0045] The rock pore structure characterization method provided in this embodiment uses different types of image acquisition methods to characterize the pore characteristics at different scales. The intermediate precision of the images between different scales overlaps, and calibration is performed based on the pore volume of the overlapping part to achieve the full-scale pore structure characterization of the rock sample, which can more truly and comprehensively characterize the pore characteristics of the rock at different scales.

[0046] The rock pore structure characterization method of the present invention specifically includes the following steps:

[0047] (1) Conduct industrial CT scanning on the rock sample to obtain millimeter-scale pore images and the pore structure characteristics at this scale; the detailed steps include:

[0048] (1.1) Place the rock on an industrial CT instrument. After setting parameters such as scanning voltage and current, obtain the industrial-grade CT image of the rock. A CT data volume is a cube, such as 1000X1000X1000, that is, 1,000,000,000 grids, also called voxels. The size of each voxel, namely the precision, is determined by the image acquisition device. The scanning voxel size is mostly 50 - 600um. The operation process refers to the national standard: GB / T 29069-2012 Non-destructive testing - Performance testing methods for industrial computed tomography (CT) systems.

[0049] (1.2) After obtaining the industrial-grade CT image of the core, carry out image segmentation and processing (specifically, for a black-and-white image in the.raw format, segment it into different regions according to different gray-level thresholds. Usually, for an 8-bit raw image, the gray value of the image is 0 - 255, and the pore part is usually 0 - dozens. The pore part can be extracted through the threshold method or other segmentation methods. Calculate parameters for the extracted pores and other features as a whole, such as calculating the pore volume, equivalent average radius, etc.). Extract the pore and fracture spaces, and calculate the pore radius and fracture width based on the equivalent sphere. That is, for a certain pore, take the sum V of all voxels as the volume of the sphere, and the relationship between the sphere radius and the volume is V=(4 / 3)*Π*R 3 , and the equivalent sphere radius R is the pore radius.

[0050] (1.3) Conduct image segmentation on the industrial-grade CT image (specifically, for a black-and-white image in the.raw format, segment it into different regions according to different gray-level thresholds. Usually, for an 8-bit raw image, the gray value of the image is 0 - 255, and the pore part is usually 0 - dozens. The pore part can be extracted through the threshold method or other segmentation methods), and divide the pore part P that can clearly identify pores according to different gray levels 10 , the part P that can be clearly identified as the solid phase 12 and the pore-containing region P with gray values between the pore part and the solid phase part 11 . Statistically calculate the proportion of pore volume and pore size distribution in the pore part. The pore part divided in the aforementioned industrial-grade CT image is the millimeter-scale pore feature of the rock.

[0051] (2) Conduct micro-scale CT scanning on the rock sample to obtain the micro-scale pore image and the pore structure characteristics at this scale. The detailed steps include:

[0052] (2.1) Based on the industrial-grade CT image obtained in the above step (1.1), drill a plug core sample with a diameter of 10 - 25mm and a length of 2 - 5cm from a representative area.

[0053] (2.2) Place the plunger-like core on a micro-CT scanning instrument. After setting parameters such as scanning voltage and current, obtain the micro-scale CT images of the rock (as shown in Figure 1 ), and the scanning voxel is mostly 0.5 - 10 um. The operation process refers to the national standard: GB / T 38531-2020 Microbeam Analysis - Computerized Tomography (CT) Analysis Method for Micro-Nano Scale Pore Structure of Tight Rocks.

[0054] (2.3) Perform image processing and segmentation on the obtained micro-scale CT images of the core (specifically, for black-and-white images in.raw format, divide them into different regions according to different gray-scale thresholds. Usually, for an 8-bit.raw image, the gray-scale value of the image is 0 - 255, and the pore part is usually 0 - dozens. The pore part can be extracted through threshold method or other segmentation methods; calculate parameters for the extracted pores and other features as a whole, such as calculating the volume of pores, equivalent average radius, etc.). Divide the pore part P that can clearly identify pores according to different gray-scales 20 , the part P that can be clearly identified as the solid phase 22 and the pore-containing region P with gray-scale values between the pore part and the solid phase part 21 ; among them, the aforementioned divided pore part P 20 is the micro-scale pore characteristic of the rock.

[0055] (2.4) For the pore and fracture spaces extracted in the above step (1.2), calculate the pore radius and fracture width based on equivalent spheres, and calculate the pore volume ratio and pore size distribution in the micro-scale CT image. Among them, the calculation method of the aforementioned pore radius is as follows: After extracting pores, they are different voxel aggregates in space. The volume can be calculated through different numbers of grids. After converting the total volume into an equivalent sphere, the radius of a pore body can be calculated. By statistically analyzing different pore radii in the CT data volume, the distribution of pore radii can be obtained; the calculation method of fracture width is similar to that of pore radius, and these calculations are all operated through mature software.

[0056] (3) Conduct nano-scale CT scanning on the rock sample to obtain nano-scale pore images and pore structure characteristics at this scale; the detailed steps include:

[0057] (3.1) Based on the micro-scale CT images obtained in the above step (2.2), select representative regions and use laser cutting technology to cut out core sub-samples with a diameter of 50 - 100 um and a length of 100 um.

[0058] (3.2) Place the core sub-samples on a nano-CT scanning instrument. After setting parameters such as scanning voltage and current, obtain nano-scale CT images of the rock. The scanning voxel is mostly 50 - 65 nm. The operation process refers to the national standard: GB / T 38531-2020 Microbeam Analysis - Computerized Tomography (CT) Analysis Method for Micro- and Nano-scale Pore Structures in Tight Rocks.

[0059] (3.3) Perform image processing and segmentation on the obtained nano-scale CT images of the core (specifically, for black-and-white images in.raw format, divide them into different regions according to different gray-scale thresholds. Usually, for an 8-bit raw image, the gray-scale value of the image is 0 - 255, and the pore part is usually 0 - dozens. The pore part can be extracted through threshold method or other segmentation methods; calculate parameters for the extracted pores and other features as a whole, such as calculating the volume of pores, equivalent average radius, etc.). Divide the pore part P that can clearly identify pores according to different gray-scales. 30 , and the part P that can be clearly identified as the solid phase. 32 ; Among them, the aforementioned divided pore part P 30 is the nano-scale pore feature of the rock.

[0060] (3.4) For the extracted pore and fracture spaces, calculate the pore radius and fracture width based on equivalent spheres, and calculate the proportion of pore volume and pore size distribution in the micro-scale CT image.

[0061] (4) Based on the nano-scale pore images and the pore structure features at this scale obtained in the above step (3), perform porosity calculation and multi-scale pore distribution fusion; the detailed steps include:

[0062] (4.1) Porosity calculation: The porosity value P of the whole rock is the sum of porosities at different scales, that is, P = P 10 + P 11 * P 20 + P 21 * P 30 , where P is the total porosity, in %, P 10 is the proportion of millimeter-scale pores, in %; P 11 is the pore-containing area in the millimeter-scale rock image, in %; P 20 is the proportion of pores in the micro-scale rock image, in %; P 21 is the proportion of pore-containing area in the micro-scale rock image, in %; P 30 is the proportion of pores in the nano-scale rock image, in %.

[0063] (4.2) Pore distribution fusion: After calculating the pore proportion at different scales, only the distribution part with the minimum pore diameter greater than 1 mm is retained in the pore part of the millimeter-scale rock image, the pore part of the micrometer-scale rock image retains the pore diameter distribution part of 1 μm - 2 mm, and the pore part of the nanometer-scale rock image retains the pore diameter distribution part less than 1 μm; according to the pore proportion of the three scales, adjust the overall proportion of different pore sizes, and fuse the pore distributions of the three scales (see Figure 2 );

[0064] The following further describes the method of pore distribution fusion in the foregoing step (4.2) in conjunction with specific embodiments:

[0065] According to the image results at different scales, calculate the proportion of pore sizes at this scale. The millimeter-scale pore size range is 50 μm - 10,000 μm, the micrometer-scale pore range is 0.5 μm - 1,000 μm, and the nanometer-scale range is 0.001 μm - 1 μm; among them, the millimeter-scale image only intercepts the pore proportion above 1,000 μm, and the micrometer-scale image intercepts Figure 1 the pore proportion of the part of μm - 1,000 μm, and the nanometer-scale image intercepts the pore proportion of the part of 0.001 - 1 μm; the pore proportion of different scales is obtained from the calculated value in step (4.1) (see below Figure 3 ); according to different proportions, adjust the proportions of millimeter-scale, micrometer-scale, and nanometer-scale pore distributions; then combine the adjusted pore proportions of different scales to ensure that the sum of all proportions is 100%.

[0066] The concept of the present invention is reasonable, integrating pore characterization means at different scales, capable of obtaining the total porosity of pores at all scales, realizing the characterization of rock pore results at different scales, and accurately quantifying the porosity and pore distribution at millimeter-scale, micrometer-scale, and nanometer-scale.

[0067] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for characterizing the pore structure of a rock, characterized in that : First, different types of image acquisition methods are used to characterize pore features at different scales. Then, the pore volumes of the overlapping parts with intermediate precision between images at different scales are calibrated to achieve the characterization of the full-scale pore structure of rock samples; The characterization method specifically includes the following steps: (1) Conduct industrial CT scanning on the rock sample to obtain millimeter-scale pore images and the pore structure features at this scale; specifically, it includes the following steps: (1.1) Place the rock on the industrial CT instrument. After setting the scanning parameters, obtain the industrial-grade CT image of the rock; (1.2) After obtaining the industrial-grade CT image of the core, conduct image segmentation and processing, extract the pore and fracture spaces, equivalent the irregular sample volume to the volume of a sphere as the equivalent sphere, take the radius of the equivalent sphere as the pore radius, and calculate the pore radius and fracture width; (1.3) Conduct image segmentation on the industrial-grade CT image, divide it into a pore part where pores can be clearly identified, a solid-phase part that can be clearly identified, and a transition region between the pore part and the solid-phase part, i.e., the pore-containing region, where the gray value of the pore-containing region is between that of the pore part and the solid-phase part, and statistically obtain the proportion of the pore volume in the pore part and the pore size distribution; (2) Conduct microscale CT scanning on the rock sample to obtain microscale pore images and the pore structure features at this scale; the specific steps are as follows: (2.1) Based on the industrial-grade CT image obtained in the above step (1.1), drill a plug sample core from a representative area; (2.2) Place the plug sample core on the micro-CT scanning instrument. After setting the scanning parameters, obtain the microscale CT image of the rock; (2.3) Conduct image processing and segmentation on the obtained microscale CT image of the core, divide it into a pore part where pores can be clearly identified, a solid-phase part that can be clearly identified, and a pore-containing region with a gray value between that of the pore part and the solid-phase part; (2.4) For the pore and fracture spaces extracted in the above step (1.2), calculate the pore radius and fracture width based on the equivalent sphere, calculate the proportion of the pore volume in the microscale CT image and the pore size distribution. The distinction between pores and fractures is based on the aspect ratio. Extracted volumes with a length or width greater than 10 are considered fractures, and the rest are pores; (3) Conduct nanoscale CT scanning on the rock sample to obtain nanoscale pore images and the pore structure features at this scale; the specific steps are as follows: (3.1) Based on the microscale CT image obtained in the above step (2.2), select a representative area and cut out a core sub-sample; (3.2) Place the core sub-sample on the nano-CT scanning instrument. After setting the scanning parameters, obtain the nanoscale CT image of the rock; (3.3) Conduct image processing and segmentation on the nanoscale CT image of the rock obtained in the above step (3.2), divide it into a pore part where pores can be clearly identified and a part that can be clearly identified as the solid phase according to the different gray levels; (3.4) For the extracted pore and fracture spaces, calculate the pore radius and fracture width based on the equivalent sphere, and calculate the proportion of the pore volume in the microscale CT image and the pore size distribution; (4)Based on the nanoscale pore images and the pore structure characteristics at this scale obtained in the above step (3), porosity calculation and multi-scale pore distribution fusion are carried out; specifically, it includes the following steps: (4.1)Porosity calculation The porosity value P of the whole rock is the sum of porosities at different scales, i.e., P = P 10 + P 11 * P 20 + P 21 * P 30 ; where P is the total porosity, P 10 is the proportion of pores at the millimeter scale, P 11 is the pore-containing area in the millimeter-scale rock image, P 20 is the proportion of pores in the micrometer-scale rock image, P 21 is the proportion of the pore-containing area in the micrometer-scale rock image, P 30 is the proportion of pores in the nanometer-scale rock image; (4.2)Pore distribution fusion After counting the pore ratios at different scales, only the distribution part with the minimum pore diameter greater than 1 mm is retained in the pore part of the millimeter-scale rock image, the pore part of the micrometer-scale rock image retains the pore diameter distribution part of 1 μm - 2 mm, and the pore part of the nanometer-scale rock image retains the pore diameter distribution part less than 1 μm; according to the pore ratios at the three scales, the overall ratios of different pore sizes are adjusted, and the adjusted pore ratios at different scales are combined to ensure that the sum of all ratios is 100%.

2. The method for characterizing the pore structure of rocks according to claim 1, wherein: The process of calculating the pore radius in the step (1.2) is as follows: for a certain pore, the sum V of all voxels is regarded as the volume of a sphere, and the relationship between the radius of the sphere and the volume is V = (4 / 3) * Π * R 3 , and the equivalent sphere radius R is the pore radius.

3. The method for characterizing the pore structure of rocks according to claim 1, characterized in that: In the step (1.1), the scanning voxel of the industrial-grade CT image is 50 - 600 μm; In the step (1.3), the pore part divided in the industrial-grade CT image is the millimeter-scale pore characteristics of the rock.

4. The method for characterizing the pore structure of rocks according to claim 1, wherein: In the step (2.1), the diameter of the plunger-like core is 10 - 25 mm, and the length is 2 - 5 cm; In the step (2.2), the scanning voxel of the micrometer-scale CT image is 0.5 - 10 μm; In the step (2.3), the pore part divided in the micrometer-scale CT image is the micrometer-scale pore characteristics of the rock.

5. The method for characterizing the pore structure of rock according to claim 1, characterized in that: In the step (3.1), a core sub-sample with a diameter of 50 - 100 μm and a length of 100 μm is cut out by using laser cutting technology; In the step (3.2), the scanning voxel of the nanometer-scale CT image is 50 - 65 nm; In the step (3.3), the pore part divided is the nanometer-scale pore characteristics of the rock.

Images