CN118169155A - Compact sandstone reservoir pore-throat characteristic analysis method based on multi-threshold segmentation algorithm - Google Patents
Compact sandstone reservoir pore-throat characteristic analysis method based on multi-threshold segmentation algorithm Download PDFInfo
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Abstract
The invention discloses a dense sandstone reservoir pore throat characteristic analysis method based on a multi-threshold segmentation algorithm, which comprises the steps of obtaining a micrometer scale three-dimensional gray scale image of a micrometer sub-sample and obtaining a nanometer scale three-dimensional gray scale image of a nanometer sub-sample; obtaining a micro-pore throat digital core according to the micro-scale three-dimensional gray level image, and obtaining a nano-pore throat digital core according to the nano-scale three-dimensional gray level image; and obtaining the total porosity and the multi-scale pore throat size distribution of the compact sandstone reservoir according to the porosity and pore throat radius distribution under the micrometer scale and the porosity and pore throat radius distribution under the nanometer scale. The beneficial effects of the invention are as follows: the nano pore throat phase characteristics of the nano pore throat digital core are fused into the matrix phase of the micro pore throat digital core, so that the spatial position information of the nano pore throat in the matrix phase is effectively reserved, and the total porosity and the multi-scale pore throat size distribution of the compact sandstone reservoir can be accurately calculated through multi-value image weighting obtained based on a multi-threshold image segmentation algorithm.
Description
Technical Field
The invention relates to the technical field of dense reservoir pore-throat characteristic research, in particular to a dense sandstone reservoir pore-throat characteristic analysis method based on a multi-threshold segmentation algorithm.
Background
The compact sandstone oil gas resource amount is huge, but the pore-throat space of a reservoir is complex, the size difference of different pore spaces is huge, and how to finely characterize the microstructure of the reservoir is one of key technologies for effectively developing the oil gas layer.
Currently, a plurality of microscopic pore throat characterization methods of a tight reservoir mainly comprise an indirect method and a direct method, wherein the indirect method comprises a mercury injection method, a gas adsorption method and the like, and the direct method comprises a casting body slice, a scanning electron microscope, a focused ion beam, an X-ray CT scanning method and the like. In the indirect method, the mercury porosimetry can rapidly measure parameters such as rock porosity, pore size and the like, but is only applicable to the pores which are mutually communicated; the gas adsorption method can measure the specific surface area and the pore size of the rock, but can not measure closed micropores, and has larger measurement error for the rock core with small specific surface area. In the direct method, the cast sheet and the scanning electron microscope can observe the two-dimensional pore-throat morphology of different scales, but can not reflect the three-dimensional distribution characteristics; the focused ion beam technology is to utilize ion beams to continuously erode and scan the rock at the nano scale to obtain a series of two-dimensional images, and obtain the three-dimensional pore-throat characteristics of the rock by combining the three-dimensional images, but the focused ion beam technology belongs to lossy scanning due to the smaller eroded area; the X-ray (CT) three-dimensional imaging technology is a method for carrying out three-dimensional scanning imaging by utilizing X-rays to penetrate through a sample and utilizing numerical reconstruction of scanning images to obtain pore-throat distribution characteristics, wherein the method can be divided into micro CT and nano CT according to different resolutions of CT scanning, pore-throat structural characteristics of micro-scale and nano-scale are obtained for samples with different sizes, accurate positions of different pore throats in the sample are accurately represented, and three-dimensional visualization is carried out on pore-throat spaces of the samples with different scales, so that the advantage is obvious.
For the same compact sandstone sample, which contains micrometer scale pore throats and nanometer scale pore throats, different pore structures and distributions can be obtained under different scales, and if the compact sandstone pore throats are characterized by only using core data of a single scale, the multi-scale characteristics of the compact sandstone pore throats cannot be expressed completely. In order to describe the multiscale characteristics of the core, a great deal of students study multiscale modeling methods, and mainly two main types of methods are: the first type is an image superposition method, which is mainly to directly superpose three-dimensional images with different scales and resolutions, and the image-based superposition method can be used for establishing a multi-scale digital rock core; the other type is a model integration method, wherein pore network models with different scales are integrated mainly through random modeling, and the integration method based on the pore network models can be used for modeling a multi-scale pore network model. In the whole, the number of the voxels of the multi-scale digital core model obtained by the superposition method is limited, and the requirement on the calculation storage space is too large; the multi-scale digital core model obtained by the integration method simplifies the structure characteristics of the pore throats with smaller scales, and cannot fully describe the spatial position information of the pore throats with smaller scales.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a method for analyzing the pore-throat characteristics of a tight sandstone reservoir based on a multi-threshold segmentation algorithm.
In order to achieve the above purpose, the invention provides a dense sandstone reservoir pore-throat characteristic analysis method based on a multi-threshold segmentation algorithm, which comprises the following steps:
Acquiring a compact sandstone sample, acquiring a micrometer sub-sample and a nanometer sub-sample on the compact sandstone sample, acquiring a micrometer-scale three-dimensional gray scale image of the micrometer sub-sample, and acquiring a nanometer-scale three-dimensional gray scale image of the nanometer sub-sample;
Obtaining a micro-pore throat digital core according to the micro-scale three-dimensional gray level image, and obtaining a nano-pore throat digital core according to the nano-scale three-dimensional gray level image;
Obtaining porosity and pore throat radius distribution under the micrometer scale according to the micrometer pore throat digital core, obtaining porosity and pore throat radius distribution under the nanometer scale according to the nanometer pore throat digital core, and obtaining total porosity and multi-scale pore throat size distribution of the compact sandstone reservoir according to the porosity and pore throat radius distribution under the micrometer scale and the porosity and pore throat radius distribution under the nanometer scale.
In some embodiments, the microsamples are samples representative of the overall condition of the tight sandstone sample, and the nanosamples are representative of the sites of clay pore development on the tight sandstone sample.
In some embodiments, the digital core of the micro-pore throat is obtained according to a micro-scale three-dimensional gray scale image, specifically:
Dividing the gray scale of the micrometer scale gray scale image into three groups of micrometer pore throat phase C 0, matrix phase C 1 and micrometer particle phase C 2, namely C0＝[0,1,…,t1]、C1＝[t1+1,t1+2,…,t2]、C2＝[t2+1,t2+2,…,L-1], according to a gray scale threshold t 1、t2, wherein L is gray scale, and selecting optimal thresholds t1 and t2 to enable the inter-class variance to be caused And obtaining the maximum value, and dividing the micrometer scale gray scale image according to the optimal threshold t1 and t2 to construct the micrometer pore throat digital core.
In some embodiments, the nano-pore throat digital core is obtained according to a nano-scale three-dimensional gray scale image, specifically:
Dividing the gray scale of the nanoscale gray scale image into two types of nano pore throat phases C 0 and nano particle phases C 1 according to a gray scale threshold t, namely C 0＝[0,1,…,t]、C1 = [ t+1, t+2, …, L-1], wherein L is the gray scale, and selecting an optimal threshold t * to enable the inter-class variance to be achieved And obtaining the maximum value and constructing the nano pore throat digital core.
In some embodiments, the method of computing the inter-class variance includes:
Setting the total pixel number in the image X as N, the gray level as L, and the pixel number of the gray level as i as N i, the probability of each gray level is:
Assuming there are m classes with distinction, there are m-1 thresholds t 1,…,tn,…,tm-1 used to divide the image into m classes. These classes are denoted C0＝[0,1,…,t1],…,Cn＝[tn+1,tn+2,…,tn+1],…,Cm-1＝[tm-1+1,tm-1+2,…,L-1], respectively, defining the inter-class variance as:
Probability of occurrence of each type [ C 0,…,Cn,…,Cm-1 ]:
average gray scale of each type:
wherein, the total average gray scale of the image:
Selecting [ t 1 *,…,tn *,…,tm-1 * ] so that The set of thresholds that takes the maximum value is the required optimal threshold.
In some embodiments, the porosity and pore throat radius distribution at the micrometer scale is obtained from the micrometer pore throat digital core, the porosity and pore throat radius distribution at the nanometer scale is obtained from the nanometer pore throat digital core, and the total porosity and multi-scale pore throat size distribution of the tight sandstone reservoir is obtained from the porosity and pore throat radius distribution at the micrometer scale and the porosity and pore throat radius distribution at the nanometer scale, which specifically comprises:
Obtaining porosity at a micrometer scale according to the micrometer pore throat digital core, obtaining porosity at a nanometer scale according to the nanometer pore throat digital core, and obtaining total porosity of the compact sandstone reservoir according to the porosity at the micrometer scale and the porosity at the nanometer scale;
Obtaining pore throat radius distribution under the micrometer scale according to the micrometer pore throat digital core, obtaining pore throat radius distribution under the nanometer scale according to the nanometer pore throat digital core, and obtaining multi-scale pore throat size distribution of the compact sandstone reservoir according to the pore throat radius distribution under the micrometer scale and the pore throat radius distribution under the nanometer scale.
In some embodiments, the total porosity of the tight sandstone reservoir is calculated as follows:
V Nanometer hole ＝V Substrate φ Nan (nanometer)
In the method, in the process of the invention, Indicating the total porosity of the densified sandstone sample; /(I)Representing the porosity of the microporous throat digital core; Representing the porosity of the nanopore throat digital core; v Micropores represents the volume occupied by the microporous throat phase in the microporous throat digital rock core; v Substrate represents the volume occupied by the matrix phase in the microporous throat digital core; v Nanometer hole represents the volume occupied by the nano pore throat phase in the nano pore throat digital rock core; v Total (S) represents the total volume of the densified sandstone sample.
In some embodiments, the multi-scale pore throat radius distribution for a tight sandstone reservoir is calculated as follows:
Wherein F (r) Total (S) represents the pore size distribution of the dense sandstone sample; f (r) Micropores represents the micron-scale pore throat radius distribution in the micron pore throat digital core; f (r) Nanometer hole represents the nano-scale pore throat radius distribution in the nano-pore throat digital core; v Micropores represents the volume occupied by the microporous throat phase in the microporous throat digital rock core; v Nanometer hole represents the volume occupied by the nanopore throat phase in the nanopore throat digital core.
In some embodiments, a specific method for obtaining pore throat radius distribution at a micrometer scale from a micrometer pore throat digital core comprises:
Based on the dense sandstone reservoir microporous throat digital core, extracting a corresponding microscale pore network model;
And obtaining the pore throat radius distribution of the micrometer scale according to the micrometer scale pore network model.
In some embodiments, a specific method for obtaining pore throat radius distribution at a nanoscale from a nanopore throat digital core comprises:
based on the dense sandstone reservoir nano pore throat digital core, extracting a corresponding nano-scale pore network model;
And obtaining nano-scale pore throat radius distribution according to the nano-scale pore network model.
Compared with the prior art, the technical scheme provided by the invention has the beneficial effects that: representative micrometer-scale three-dimensional gray level images are obtained through micrometer CT scanning, representative nanometer subsamples are selected on the basis of the representative micrometer-scale three-dimensional gray level images to carry out high-precision nanometer CT scanning, representative nanometer-scale three-dimensional gray level images are obtained, and a foundation can be provided for compact sandstone multi-scale digital rock core construction; then, respectively constructing a micro-pore throat digital core and a nano-pore throat digital core, and further establishing a multi-scale digital core platform based on a multi-threshold segmentation algorithm; based on the compact sandstone micro-nano multi-scale digital core and a corresponding pore network model, the porosity and pore throat radius distribution under the micron-nano scale can be calculated respectively, on the basis, the nano pore throat phase characteristics of the nano pore throat digital core are fused into the matrix phase of the micro pore throat digital core, the space position information of the nano pore throat in the matrix phase is effectively reserved, the total porosity and the multi-scale pore throat size distribution of a compact sandstone reservoir can be calculated accurately through multi-value image weighting acquired based on a multi-threshold image segmentation algorithm, a basic platform is provided for compact sandstone multi-scale pore throat characterization and reservoir evaluation, the problem that the number of voxels of the conventional multi-scale digital core model acquired through an superposition method is limited, and the requirement on calculation storage space is too large is solved; the multi-scale digital core model obtained by the integration method simplifies the structure characteristics of the pore throats with smaller scale, and cannot fully describe the technical problem of spatial position information of the pore throats with smaller scale.
Drawings
FIG. 1 is a schematic flow chart of an embodiment of a method for analyzing pore-throat characteristics of a tight sandstone reservoir based on a multi-threshold segmentation algorithm;
FIG. 2 is a three-dimensional gray scale image acquired based on micro-nano CT scanning;
FIG. 3 is a schematic diagram of the multi-threshold segmentation principle of a micro-nano gray scale image;
FIG. 4 is a multi-scale three-dimensional digital core derived from the three-dimensional gray scale image of FIG. 2;
FIG. 5 is a schematic flow chart of step S3 in FIG. 1;
FIG. 6 is a multi-scale pore network model derived from the multi-scale three-dimensional digital core of FIG. 4;
FIG. 7 is a pore throat radius distribution plot obtained from the multi-scale pore network model of FIG. 6;
FIG. 8 is a graph of a tight reservoir multi-scale pore throat radius distribution.
Detailed Description
The following detailed description of preferred embodiments of the application is made in connection with the accompanying drawings, which form a part hereof, and together with the description of the embodiments of the application, are used to explain the principles of the application and are not intended to limit the scope of the application.
Referring to fig. 1, the invention provides a dense sandstone reservoir pore-throat feature analysis method based on a multi-threshold segmentation algorithm, which comprises the following steps:
S1, acquiring a compact sandstone sample, acquiring a micrometer sub-sample and a nanometer sub-sample on the compact sandstone sample, acquiring a micrometer-scale three-dimensional gray scale image of the micrometer sub-sample, and acquiring a nanometer-scale three-dimensional gray scale image of the nanometer sub-sample, wherein the micrometer sub-sample is a sample representing the whole condition of the compact sandstone sample, and the nanometer sub-sample is a representative sample of the clay pore development part on the compact sandstone sample;
In this example, the tight sandstone sample was taken from the Husky basin red river oilfield tight sandstone reservoir. The reservoir is mainly composed of fine sandstone, siltstone and mudstone, the reservoir has poor physical properties, the average porosity of the reservoir is only 8.2%, the average permeability of the reservoir is 0.21mD, the reservoir belongs to a typical compact sandstone reservoir, the reservoir develops micro-scale pores and nano-scale pores, wherein the micro-scale pores mainly consist of primary residual inter-particle pores and intra-particle dissolved pores of feldspar rock scraps, and the nano-scale pores mainly consist of authigenic kaolinite, authigenic illite, illite/Mongolian mixed layer inter-crystal pores and the like.
In the embodiment, a CT scanning method is adopted to obtain three-dimensional gray scale images of the compact sandstone representative micrometer scale and nanometer scale. The CT scanning is to penetrate a sample through conical X-rays emitted by a ray source, meanwhile, image amplification is carried out based on objective lenses with different multiples, the sample rotates 360 degrees to obtain an X-ray attenuation image so as to reconstruct a three-dimensional gray image, the CT image reflects the energy attenuation information of the X-rays in the process of penetrating an object, and therefore the three-dimensional gray image obtained by the CT scanning can reflect the real pore structure and the relative density inside a rock core.
Based on a real sample of a compact sandstone reservoir, firstly, a representative micrometer sub-sample with the diameter of 2mm is drilled, and is scanned by a Zeiss MCT-200 micrometer CT device to obtain a representative micrometer-scale three-dimensional gray scale image (as shown as a diagram in figure 2); on the basis, a representative nanometer subsamples (with the diameter of 65 μm) for clay pore development are prepared, and are scanned by a Zeiss Ultra L-200 nanometer CT device to obtain a representative nanoscale three-dimensional gray scale image (as shown in a b diagram in fig. 2). The voxel resolution of the micrometer-scale three-dimensional gray level image is 1 mu m, the voxel size is 600 multiplied by 500, and the physical size is 600 mu m multiplied by 500 mu m, so that the micrometer-scale pore information of the compact sandstone reservoir is mainly characterized; the voxel resolution of the nanoscale three-dimensional gray-scale image is 65nm, the voxel size is 650 multiplied by 700, and the physical size is 42 mu m multiplied by 45 mu m, and the nanoscale pore information of the tight sandstone reservoir is mainly characterized.
S2, obtaining a micro-pore throat digital core according to the micro-scale three-dimensional gray level image, and obtaining a nano-pore throat digital core according to the nano-scale three-dimensional gray level image;
Aiming at micrometer scale and nanometer scale gray scale images, the invention performs multi-threshold image segmentation based on an improved maximum inter-class variance method. The maximum inter-class variance method is used for single-threshold segmentation, and the principle is that the segmentation is performed by setting a threshold value so as to maximize the variance between the two segmented classes. Here for multi-threshold segmentation.
The principle of the improved maximum inter-class variance method is as follows:
Setting the total pixel number in the image X as N, the gray level as L, and the pixel number of the gray level as i as N i, the probability of each gray level is:
Assuming there are m classes with distinction, there are m-1 thresholds t 1,…,tn,…,tm-1 used to divide the image into m classes. These classes are denoted C0＝[0,1,…,t1],…,Cn＝[tn+1,tn+2,…,tn+1],…,Cm-1＝[tm-1+1,tm-1+2,…,L-1], respectively, defining the inter-class variance as:
Probability of occurrence of each type [ C 0,…,Cn,…,Cm-1 ]:
average gray scale of each type:
wherein, the total average gray scale of the image:
Selecting [ t 1 *,…,tn *,…,tm-1 * ] so that The set of thresholds that takes the maximum value is the required optimal threshold.
Firstly, a micron-scale gray scale image is segmented according to an improved maximum inter-class variance method, and a micron pore throat digital rock core is constructed, and the specific method is as follows:
As shown in a graph a in fig. 3, a micrometer scale gray scale image is divided into three groups of micrometer pore throat phase C 0, matrix phase C 1 and micrometer particle phase C 2 according to a gray scale threshold t 1、t2, i.e. C0＝[0,1,…,t1]、C1＝[t1+1,t1+2,…,t2]、C2＝[t2+1,t2+2,…,L-1],, wherein L is gray scale, and the optimal thresholds t1 x and t2 x are selected to enable the inter-class variance to be caused And obtaining the maximum value, and dividing the micrometer scale gray scale image according to the optimal threshold t1 and t2 to construct the micrometer pore throat digital core.
Then, the nanoscale gray scale image is segmented according to an improved maximum inter-class variance method, and a nano pore throat digital rock core is constructed, and the specific method is as follows:
As shown in b diagram in fig. 3, the nanoscale gray scale image is divided into two types of nano-pore throat phases C 0 and nano-particle phases C 1 according to a gray scale threshold t, namely, C 0＝[0,1,…,t]、C1 = [ t+1, t+2, …, L-1], wherein L is gray scale, and the optimal threshold t * is selected so that the inter-class variance is obtained And obtaining the maximum value and constructing the nano pore throat digital core.
In this embodiment, based on the 8-bit three-dimensional gray scale image of the true dense sandstone micrometer scale and nanometer scale, the dense sandstone micrometer scale image can be segmented into three phases (m=3, l=256, n=600600×500) according to a multi-threshold image segmentation algorithm that improves the maximum inter-class variance method: a microporous throat phase, a microparticle phase, and a matrix phase (a plot in fig. 4); the nanoscale image is segmented into two phases (m=2, l=256, n=650×650×700): the nano-pore throat phase and the nano-particle phase (b diagram in fig. 4) are respectively constructed, so that a micro-pore throat digital core and a nano-pore throat digital core are respectively constructed, and a multi-scale digital core platform based on a multi-threshold segmentation algorithm is established. The matrix phase gray value is between the micro pore throat and the micro particle, and is used for representing the nano pore throat and the particle area which cannot be identified under the micro CT scanning precision, and the nano pore and the particle in the matrix phase need to be represented by the nano CT scanning with higher precision, so that the sampling area of the nano subsamples is also exactly located in the matrix phase of the micro subsamples.
S3, obtaining porosity and pore throat radius distribution under the micrometer scale according to the micrometer pore throat digital core, obtaining porosity and pore throat radius distribution under the nanometer scale according to the nanometer pore throat digital core, and obtaining total porosity and multi-scale pore throat size distribution of the compact sandstone reservoir according to the porosity and pore throat radius distribution under the micrometer scale and the porosity and pore throat radius distribution under the nanometer scale.
Referring to fig. 5, step S3 specifically includes the following steps:
s31, obtaining the porosity under the micrometer scale according to the micrometer pore throat digital core, obtaining the porosity under the nanometer scale according to the nanometer pore throat digital core, and obtaining the total porosity of the compact sandstone reservoir according to the porosity under the micrometer scale and the porosity under the nanometer scale.
Based on the digital core of the micro-pore throat and the nano-pore throat, the porosity under the micro-scale and the nano-scale can be obtained respectively. On the basis, the pore proportion of the nano pore throat digital core is fused into the matrix phase of the micro pore digital core, the total porosity of the compact sandstone reservoir is obtained through weighting,
The total porosity is calculated as follows:
V Nanometer hole ＝V Substrate φ Nan (nanometer) (7)
In the method, in the process of the invention, Indicating the total porosity of the densified sandstone sample;
Representing the porosity of the microporous throat digital core;
Representing the porosity of the nanopore throat digital core;
V Micropores represents the volume occupied by the microporous throat phase in the microporous throat digital rock core, m 3;
V Substrate represents the volume occupied by the matrix phase in the microporous throat digital core, m 3;
V Nanometer hole represents the volume occupied by the nanopore throat phase in the nanopore throat digital core, m 3;
V Total (S) represents the total volume of the dense sandstone sample (micrometer CT scan sample), m 3.
As shown in table 1, based on the dense sandstone reservoir micro-pore throat and nano-pore throat digital core, the porosity of the obtained micron-scale digital core is 3.3%, the porosity of the obtained nano-scale digital core is 30.7%, and the total porosity of the dense sandstone reservoir 9.4% obtained after weighting by the above formula is basically consistent with the indoor gas measurement porosity of 8.9%.
Table 1 sample physical parameters based on multiscale digital core analysis
S32, obtaining pore throat radius distribution under the micrometer scale according to the micrometer pore throat digital core, obtaining pore throat radius distribution under the nanometer scale according to the nanometer pore throat digital core, and obtaining multi-scale pore throat size distribution of the compact sandstone reservoir according to the pore throat radius distribution under the micrometer scale and the pore throat radius distribution under the nanometer scale.
Based on the digital core of the micro pore throat and the nano pore throat, respectively extracting corresponding pore network models to obtain pore throat radius distribution characteristics under the micro-scale and nano-scale. On the basis, the pore throat distribution characteristics of the nano pore throat digital core are fused into the matrix phase of the micro pore throat digital core, and the multi-scale pore throat radius distribution characteristics of the compact sandstone reservoir are obtained through weighting, wherein the calculation formula is as follows:
wherein F (r) Total (S) represents the pore size distribution of the dense sandstone sample;
F (r) Micropores represents the micron-scale pore throat radius distribution in the micron pore throat digital core;
F (r) Nanometer hole represents the nanoscale pore throat radius distribution in the digital core of the pore throat.
Specifically, the specific method for obtaining pore throat radius distribution under the micrometer scale according to the micrometer pore throat digital rock core comprises the following steps:
(1) Based on the dense sandstone reservoir microporous throat digital core, extracting a corresponding microscale pore network model (a diagram in fig. 6);
(2) The pore throat radius distribution on the micrometer scale was obtained from the micrometer scale pore network model (graph a in fig. 7). As can be seen from the graph a in fig. 7, the micron-scale pore throat radius distribution curve mainly characterizes the distribution characteristics of the dense sandstone micron pore throat, and the pore throat radius distribution peak value is 3.24 μm;
Specifically, the specific method for obtaining pore throat radius distribution under the nanoscale according to the nano pore throat digital rock core comprises the following steps:
(1) Based on the dense sandstone reservoir nano pore throat digital core, extracting a corresponding nano-scale pore network model (b diagram in fig. 6);
(2) According to the nanoscale pore network model, a nanoscale pore throat radius distribution (b diagram in fig. 7) is obtained. As shown in b graph in fig. 7, the nano-scale pore throat radius distribution curve mainly characterizes the distribution characteristics of dense sandstone nano pore throats, and the pore throat radius distribution peak value is 380nm.
As shown in a graph a in fig. 8, pore-throat distribution of the nano pore-throat digital core is fused into a matrix phase of the micro pore-throat digital core, and multi-scale pore-throat radius distribution of the compact sandstone reservoir is obtained after weighting by the formula. It can be found that the weighted pore throat radius distribution peak value is 1.01 mu m, the distribution range is 30 nm-13.1 mu m, and the pore throat distribution peak value can contain the micrometer-scale and nanometer-scale pore throat distribution information of a compact sandstone reservoir; meanwhile, by comparing the multi-scale digital core analysis result with the indoor high-pressure mercury injection experimental result (b diagram and c diagram in fig. 8) of the sample, the pore-throat radius distribution characteristics obtained by the high-pressure mercury injection experiment and the multi-scale digital core analysis are basically consistent. The pore-throat radius of the high-pressure mercury-pressing experiment is slightly lower than the analysis result of the digital core, because the high-pressure mercury-pressing experiment mainly reflects the structural characteristics of the throat of the reservoir, and the multi-scale digital core can reflect the pore and throat information of the reservoir at the same time.
In summary, the technical scheme provided by the invention has the beneficial effects that:
(1) The CT scanning has the advantages of true three-dimensional imaging and nondestructive characteristics, the representative micrometer-scale three-dimensional gray scale image is obtained through micrometer CT scanning, the representative nanometer subsamples are selected to carry out high-precision nanometer CT scanning on the basis, the representative nanometer-scale three-dimensional gray scale image is obtained, and the foundation can be provided for compact sandstone multi-scale digital rock core construction.
(2) Dividing the micrometer scale gray level image based on a multi-threshold dividing algorithm to divide a micrometer pore throat phase, a micrometer particle phase and a matrix phase, wherein the gray level value of the matrix phase is between the micrometer pore throat and the micrometer particle and is used for representing the nanometer pore throat and particle areas which cannot be identified under the micrometer CT scanning precision, and the nanometer pores and particles in the matrix phase need to be represented by the nanometer CT scanning with higher precision, so that the sampling area of the nanometer subsamples is just located in the matrix phase of the micrometer subsamples; the nanoscale gray scale image is divided into two phases: the nano-pore throat phase and the nano-particle phase respectively construct a micro-pore throat digital core and a nano-pore throat digital core, and then a multi-scale digital core platform based on a multi-threshold segmentation algorithm is established.
(3) Based on the compact sandstone micro-nano multi-scale digital core and a corresponding pore network model, the porosity and pore throat radius distribution under the micron-nano scale can be calculated respectively, on the basis, the nano pore throat phase characteristics of the nano pore throat digital core are fused into the matrix phase of the micro pore throat digital core, the space position information of the nano pore throat in the matrix phase is effectively reserved, the total porosity and multi-scale pore throat size distribution of a compact sandstone reservoir can be calculated accurately through multi-value image weighting acquired based on a multi-threshold image segmentation algorithm, and the rationality and the correctness of a digital core analysis method are verified through indoor experimental measurement result comparison, so that a basic platform is provided for compact sandstone multi-scale pore throat representation and reservoir evaluation, and important academic significance and practical application value are realized.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the technical scope of the present invention should be included in the scope of the present invention.
Claims (10)
1. A dense sandstone reservoir pore-throat characteristic analysis method based on a multi-threshold segmentation algorithm is characterized by comprising the following steps:
Acquiring a compact sandstone sample, acquiring a micrometer sub-sample and a nanometer sub-sample on the compact sandstone sample, acquiring a micrometer-scale three-dimensional gray scale image of the micrometer sub-sample, and acquiring a nanometer-scale three-dimensional gray scale image of the nanometer sub-sample;
Obtaining a micro-pore throat digital core according to the micro-scale three-dimensional gray level image, and obtaining a nano-pore throat digital core according to the nano-scale three-dimensional gray level image;
Obtaining porosity and pore throat radius distribution under the micrometer scale according to the micrometer pore throat digital core, obtaining porosity and pore throat radius distribution under the nanometer scale according to the nanometer pore throat digital core, and obtaining total porosity and multi-scale pore throat size distribution of the compact sandstone reservoir according to the porosity and pore throat radius distribution under the micrometer scale and the porosity and pore throat radius distribution under the nanometer scale.
2. The method for analyzing pore-throat characteristics of a tight sandstone reservoir based on a multi-threshold segmentation algorithm according to claim 1, wherein the micrometer subsamples are representative samples of the overall condition of the tight sandstone sample, and the nanometer subsamples are representative samples of the sites of clay pore development on the tight sandstone sample.
3. The method for analyzing the pore throat characteristics of the tight sandstone reservoir based on the multi-threshold segmentation algorithm according to claim 1, wherein the method is characterized in that the micron pore throat digital core is obtained according to a micron-scale three-dimensional gray scale image, and specifically comprises the following steps:
Dividing the gray scale of the micrometer scale gray scale image into three groups of micrometer pore throat phase C 0, matrix phase C 1 and micrometer particle phase C 2, namely C0＝[0,1,…,t1]、C1＝[t1+1,t1+2,…,t2]、C2＝[t2+1,t2+2,…,L-1], according to a gray scale threshold t 1、t2, wherein L is gray scale, and selecting optimal thresholds t1 and t2 to enable the inter-class variance to be caused And obtaining the maximum value, and dividing the micrometer scale gray scale image according to the optimal threshold t1 and t2 to construct the micrometer pore throat digital core.
4. The method for analyzing the pore-throat characteristics of the tight sandstone reservoir based on the multi-threshold segmentation algorithm according to claim 3, wherein the method is characterized in that the nano pore-throat digital core is obtained according to the nano-scale three-dimensional gray scale image, and specifically comprises the following steps:
Dividing the gray scale of the nanoscale gray scale image into two types of nano pore throat phases C 0 and nano particle phases C 1 according to a gray scale threshold t, namely C 0＝[0,1,…,t]、C1 = [ t+1, t+2, …, L-1], wherein L is the gray scale, and selecting an optimal threshold t * to enable the inter-class variance to be achieved And obtaining the maximum value and constructing the nano pore throat digital core.
5. The method for analyzing the pore-throat characteristics of the tight sandstone reservoir based on the multi-threshold segmentation algorithm according to claim 4, wherein the method for calculating the inter-class variance comprises the following steps:
Setting the total pixel number in the image X as N, the gray level as L, and the pixel number of the gray level as i as N i, the probability of each gray level is:
assuming there are m classes with distinction, there are m-1 thresholds [ t 1,…,tn,…,tm-1 ] to divide the image into m classes, these classes denoted C0＝[0,1,…,t1],…,Cn＝[tn+1,tn+2,…,tn+1],…,Cm-1＝[tm-1+1,tm-1+2,…,L-1], respectively define the inter-class variance as:
Probability of occurrence of each type [ C 0,…,Cn,…,Cm-1 ]:
average gray scale of each type:
wherein, the total average gray scale of the image:
Selecting [ t 1 *,…,tn *,…,tm-1 * ] so that The set of thresholds that takes the maximum value is the required optimal threshold.
6. The method for analyzing pore-throat characteristics of a tight sandstone reservoir based on a multi-threshold segmentation algorithm according to claim 1, wherein the method for analyzing pore-throat characteristics of the tight sandstone reservoir based on the multi-threshold segmentation algorithm is characterized by obtaining porosity and pore-throat radius distribution at a micrometer scale according to a micrometer pore-throat digital core, obtaining porosity and pore-throat radius distribution at a nanometer scale according to a nanometer pore-throat digital core, and obtaining total porosity and multi-scale pore-throat size distribution of the tight sandstone reservoir according to the porosity and pore-throat radius distribution at the micrometer scale and the porosity and pore-throat radius distribution at the nanometer scale, and specifically comprises the following steps:
Obtaining porosity at a micrometer scale according to the micrometer pore throat digital core, obtaining porosity at a nanometer scale according to the nanometer pore throat digital core, and obtaining total porosity of the compact sandstone reservoir according to the porosity at the micrometer scale and the porosity at the nanometer scale;
Obtaining pore throat radius distribution under the micrometer scale according to the micrometer pore throat digital core, obtaining pore throat radius distribution under the nanometer scale according to the nanometer pore throat digital core, and obtaining multi-scale pore throat size distribution of the compact sandstone reservoir according to the pore throat radius distribution under the micrometer scale and the pore throat radius distribution under the nanometer scale.
7. The method for analyzing pore-throat characteristics of a tight sandstone reservoir based on a multi-threshold segmentation algorithm according to claim 6, wherein the calculation formula of the total porosity of the tight sandstone reservoir is as follows:
V Nanometer hole ＝V Substrate φ Nan (nanometer)
In the method, in the process of the invention, Indicating the total porosity of the densified sandstone sample; /(I)Representing the porosity of the microporous throat digital core; /(I)Representing the porosity of the nanopore throat digital core; v Micropores represents the volume occupied by the microporous throat phase in the microporous throat digital rock core; v Substrate represents the volume occupied by the matrix phase in the microporous throat digital core; v Nanometer hole represents the volume occupied by the nano pore throat phase in the nano pore throat digital rock core; v Total (S) represents the total volume of the densified sandstone sample.
8. The method for analyzing pore-throat characteristics of a tight sandstone reservoir based on a multi-threshold segmentation algorithm according to claim 6, wherein the calculation formula of the multi-scale pore-throat radius distribution of the tight sandstone reservoir is as follows:
Wherein F (r) Total (S) represents the pore size distribution of the dense sandstone sample; f (r) Micropores represents the micron-scale pore throat radius distribution in the micron pore throat digital core; f (r) Nanometer hole represents the nano-scale pore throat radius distribution in the nano-pore throat digital core; v Micropores represents the volume occupied by the microporous throat phase in the microporous throat digital rock core; v Nanometer hole represents the volume occupied by the nanopore throat phase in the nanopore throat digital core.
9. The method for analyzing pore-throat characteristics of a tight sandstone reservoir based on a multi-threshold segmentation algorithm according to claim 6, wherein the specific method for obtaining pore-throat radius distribution under a micrometer scale according to a micrometer pore-throat digital core comprises the following steps:
Based on the dense sandstone reservoir microporous throat digital core, extracting a corresponding microscale pore network model;
And obtaining the pore throat radius distribution of the micrometer scale according to the micrometer scale pore network model.
10. The method for analyzing pore-throat characteristics of a tight sandstone reservoir based on a multi-threshold segmentation algorithm according to claim 6, wherein the specific method for obtaining pore-throat radius distribution under the nanoscale according to the nano-pore-throat digital core comprises the following steps:
based on the dense sandstone reservoir nano pore throat digital core, extracting a corresponding nano-scale pore network model;
And obtaining nano-scale pore throat radius distribution according to the nano-scale pore network model.
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