Rock pore throat coordination number calculation method and device based on pore fractal dimension

Abstract

The invention relates to a rock pore throat coordination number calculation method and device based on pore fractal dimension, and the method comprises the steps: obtaining a rock sample mercury injection curve through a mercury injection experiment, and obtaining mercury intrusion dynamic parameters of a plurality of test points; calculating a mercury intrusion dynamic parameter logarithm value according to the rock sample mercury intrusion curve; fitting the mercury intrusion dynamic parameter logarithm value to obtain a linear regression fitting straight line; calculating the pore fractal dimension of the rock according to the slope of the linear regression fitting straight line; and calculating the rock pore throat coordination number according to the pore fractal dimension to obtain an interval calculation result of the rock pore throat coordination number. According to the method, the rock pore throat coordination number can be rapidly and quantitatively determined based on the pore fractal dimension, and the fluctuation range of the pore throat coordination number can be accurately given.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration and development, and particularly relates to a method and device for calculating the pore throat coordination number of rocks based on pore fractal dimension. Background Art

[0002] Pores are the spaces in rocks that are not filled with solid minerals and consist of two parts: pore channels and throat channels. Among them, the pore channels have a larger opening and determine the ability to store fluids; the throat channels are narrow channels connecting the pore channels, with a relatively smaller opening, and control the ability to percolate fluids. The pore channels and throat channels are coupled and connected to each other to jointly form a complex spatial topological pore throat network. Therefore, the essence of pores is a complex of pore channels and throat channels, with a pore throat binary structure.

[0003] The pore throat coordination number of rocks refers to the number of throat channels connected to the pore channels, and it is a key characteristic parameter for characterizing the pore throat configuration relationship and structural complexity of rocks. However, there is currently a lack of a quantitative calculation method. In recent years, thanks to the development of scanning imaging and digital core technology, the pore throat coordination number is mainly statistically calculated using the reconstructed pore throat network model.

[0004] However, the pore network model has a complex establishment process, including two-dimensional scanning imaging, three-dimensional digital core reconstruction, pore network model extraction, etc., resulting in a long extraction period and high cost. Only a certain number of tests are carried out during scientific research, and it is difficult to be applied on a large scale.

[0005] Therefore, establishing a simple and effective method for determining the pore throat coordination number to quickly and quantitatively obtain the pore throat coordination number of rocks has important practical significance for accurately and scientifically characterizing the pore throat structure of rocks. Summary of the Invention

[0006] The present invention provides a method and device for calculating the pore throat coordination number of rocks based on pore fractal dimension to solve the defects of the prior art.

[0007] The first aspect of the present invention provides a method for calculating the pore throat coordination number of rocks based on pore fractal dimension, including:

[0008] S1: Obtain the mercury injection curve of the rock sample through a mercury injection experiment to obtain the mercury intrusion dynamic parameters at multiple test points;

[0009] S2: Calculate the logarithmic values of the mercury intrusion dynamic parameters according to the mercury injection curve of the rock sample;

[0010] S3: Fit the logarithmic values of the mercury intrusion dynamic parameters to obtain a linear regression fitting straight line;

[0011] S4: Calculate the pore fractal dimension of the rock according to the slope of the linear regression fitting straight line;

[0012] S5: Calculate the rock pore-throat coordination number according to the pore fractal dimension to obtain the interval calculation result of the rock pore-throat coordination number.

[0013] According to a method for calculating the rock pore-throat coordination number based on the pore fractal dimension provided by the present invention, the mercury intrusion dynamic parameters in step S1 include:

[0014] Mercury intrusion pressure and mercury intrusion saturation;

[0015] The logarithmic values of the mercury intrusion dynamic parameters include:

[0016] Logarithmic value of mercury intrusion pressure and logarithmic value of mercury intrusion saturation.

[0017] According to a method for calculating the rock pore-throat coordination number based on the pore fractal dimension provided by the present invention, the expression of the linear regression fitting straight line in step S3 is:

[0018] lgS Hg = k·lgp c - A;

[0019] Where, lgS Hg Is the logarithmic value of mercury intrusion saturation, k is the slope of the linear regression fitting straight line, lgp c Is the logarithmic value of mercury intrusion pressure, and A is the intercept of the linear regression fitting straight line.

[0020] According to a method for calculating the rock pore-throat coordination number based on the pore fractal dimension provided by the present invention, the expression of the pore fractal dimension in step S4 is:

[0021] D = k + 3;

[0022] Where, D is the pore fractal dimension and k is the slope of the linear regression fitting straight line.

[0023] According to a method for calculating the rock pore-throat coordination number based on the pore fractal dimension provided by the present invention, the interval calculation results in step S5 include:

[0024] Minimum pore-throat coordination number, maximum pore-throat coordination number, average pore-throat coordination number.

[0025] According to a method for calculating the rock pore-throat coordination number based on the pore fractal dimension provided by the present invention, the expression of the minimum pore-throat coordination number is:

[0026]

[0027] The expression of the maximum pore-throat coordination number is:

[0028] n max = D - 2;

[0029] The expression for the average pore-throat coordination number is as follows:

[0030]

[0031] where n min is the minimum pore-throat coordination number, D is the pore fractal dimension, n max is the maximum pore-throat coordination number, and n avre is the average pore-throat coordination number.

[0032] In a second aspect of the present invention, a device for calculating the pore-throat coordination number of a rock based on the pore fractal dimension is provided, including:

[0033] An acquisition module: used to obtain the mercury intrusion curve of a rock sample through a mercury intrusion experiment to obtain the mercury intrusion dynamic parameters of multiple test points;

[0034] A logarithm calculation module: used to calculate the logarithm of the mercury intrusion dynamic parameters according to the mercury intrusion curve of the rock sample;

[0035] A fitting module: used to fit the logarithm of the mercury intrusion dynamic parameters to obtain a linear regression fitting line;

[0036] A dimension calculation module: used to calculate the pore fractal dimension of the rock according to the slope of the linear regression fitting line;

[0037] A coordination number calculation module: used to calculate the pore-throat coordination number of the rock according to the pore fractal dimension to obtain the interval calculation result of the pore-throat coordination number of the rock.

[0038] In a third aspect of the present invention, a device for calculating the pore-throat coordination number of a rock based on the pore fractal dimension is provided, including:

[0039] A memory and at least one processor, wherein instructions are stored in the memory;

[0040] At least one of the processors invokes the instructions in the memory so that a device for calculating the pore-throat coordination number of a rock based on the pore fractal dimension executes a method for calculating the pore-throat coordination number of a rock based on the pore fractal dimension as described in any one of the above.

[0041] In a fourth aspect of the present invention, a computer-readable storage medium is provided, on which instructions are stored, and when the instructions are executed by a processor, a method for calculating the pore-throat coordination number of a rock based on the pore fractal dimension as described in any one of the above is implemented.

[0042] The present invention provides a method, apparatus, device and storage medium for calculating the pore-throat coordination number of rocks based on the pore fractal dimension, filling the technical gap in the quantitative calculation method of the pore-throat coordination number of rocks. The present invention deeply integrates the pore fractal dimension with the pore-throat topological structure, providing a simple, feasible and highly operable rapid quantitative calculation method, and providing a new technical approach for the research on the pore-throat characteristics of rocks in the oil and gas exploration and development field. Secondly, the present invention gives the fluctuation range of the pore-throat coordination number, and the range-based characterization method can more comprehensively reflect the complexity and diversity of the real rock pore-throat structure than a single numerical value, making the evaluation of reservoir characteristics more accurate and comprehensive. Thirdly, the present invention can realize the rapid calculation of the pore-throat coordination number through conventional mercury injection experiment data, without additional high-cost equipment and complex tests, greatly reducing the technical threshold and application cost, and facilitating popularization and application in the oil and gas exploration and development work. In addition, based on the method of the present invention, through the fractal theory, the change law of the pore-throat structure in different pressure intervals (low-pressure area, medium-pressure area, high-pressure area) can be analyzed, revealing the internal law of the change of the pore-throat coordination number with the pore-throat size, providing a theoretical basis for understanding the microscopic pore-throat structure of rocks.

[0043] The present invention has important practical significance for accurately characterizing the pore-throat configuration relationship and structural complexity of rocks, establishing a scientific system for quantitative evaluation of reservoir microscopic pore-throats, and guiding pore-throat network simulation research, etc. The application prospect is very broad, and it can provide important technical support for fields such as oil and gas exploration and development, and underground water resource evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0045] Figure 1 It is a schematic flow chart of a method for calculating the pore-throat coordination number of rocks based on the pore fractal dimension provided by the present invention;

[0046] Figure 2 It is a schematic diagram of a pore simplification model provided by an embodiment of the present invention;

[0047] Figure 3 It is a schematic structural diagram of a device for calculating the pore-throat coordination number of rocks based on the pore fractal dimension provided by the present invention;

[0048] Figure 4 It is a schematic diagram of a mercury injection curve provided by an embodiment of the present invention;

[0049] Figure 5 It is a schematic diagram of linear regression fitting provided by an embodiment of the present invention. Detailed implementation manners

[0050] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention, and they should not be construed as limiting the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts shall fall within the scope of protection of the present invention. In the description of the present invention, it should be understood that the terms used are only for the purpose of description and cannot be construed as indicating or implying relative importance.

[0051] To better understand the present invention, the basic principles of the present invention will be explained below.

[0052] The pore essence is a pore-throat complex with a pore-throat dual structure. Combining with the pore ball-and-stick model, the pore fractal dimension is decomposed into the pore channel fractal dimension and the throat fractal dimension:

[0053] D = D d + D t ;

[0054] where D is the pore fractal dimension, D d is the pore channel fractal dimension, and D t is the throat fractal dimension.

[0055] For the pore channel, if it is regarded as a sphere, it has three-dimensional topological properties, and the fractal dimension is between 2 and 3, that is, D d ∈ (2, 3). For a single throat, if it is regarded as a circular tube, it can be arbitrarily twisted in three-dimensional space. Therefore, the fractal dimension of a single throat is also between 2 and 3, that is, D t,i ∈ (2, 3), where i is the throat index value, and D t,i represents the throat fractal dimension of the i-th throat.

[0056] For the throats in the pores, which are a collection of multiple throats, considering the pore-throat coordination number based on this, the throat fractal dimension can be expressed as:

[0057]

[0058] where n is the pore-throat coordination number.

[0059] Combining the above two equations, we can get:

[0060]

[0061] Based on the above formula, the pore fractal dimension depends on three parameters: the pore channel fractal dimension, the single-throat fractal dimension, and the pore-throat coordination number. Among them, the fractal dimensions of pore channels and single throats have definite ranges of variation, and the variation amplitudes are small; while the pore-throat coordination number is not fixed and has a large variation range. Therefore, the pore-throat coordination number is the key factor affecting the pore fractal dimension. Different pore-throat coordination numbers of rocks result in different topological structures of pore-throat spaces and corresponding pore fractal dimensions.

[0062] Let D t,i be a constant, then the above formula can be rewritten as:

[0063]

[0064] For the above formula, take D d = D t,i = 3 or D d = D t,i = 2, then the minimum pore-throat coordination number, the maximum pore-throat coordination number, and the average pore-throat coordination number can be obtained.

[0065] The embodiments of the present invention will be described below with reference to the drawings.

[0066] As Figure 1 shown, a method for calculating the pore-throat coordination number of rocks based on the pore fractal dimension provided by the first aspect of the present invention includes:

[0067] S1: Obtain the mercury injection curve of the rock sample through a mercury injection experiment to obtain the mercury intrusion dynamic parameters of multiple test points.

[0068] Furthermore, the main principle of the mercury injection method is as follows: Mercury is a non-wetting phase. Under high pressure, mercury is injected into the rock sample, and the capillary pressure and the volume of injected mercury in equilibrium are obtained, so as to obtain the relationship curve between the capillary pressure and the mercury saturation of the rock sample. Since the mercury injection method can directly measure the pore-throat distribution characteristics of rock samples from the inside, it can be used to determine the pore fractal dimension.

[0069] During the mercury injection test of the rock sample, data such as the mercury injection pressure and mercury injection saturation, mercury withdrawal pressure and mercury injection saturation of each test point are completely recorded. The present invention first obtains and arranges these data. Among them, the data of mercury injection pressure and mercury injection saturation are mainly used.

[0070] Among them, the mercury intrusion dynamic parameters in step S1 include: mercury injection pressure, mercury injection saturation.

[0071] In step S1 of the present invention, mercury intrusion experiment is used to obtain mercury intrusion curve data of rock samples, aiming to measure the pore distribution characteristics of rock samples. Specifically, the basic principle of the mercury intrusion experiment is to use mercury as a non-wetting phase fluid, and under high pressure conditions, force mercury liquid to invade the pore space of rock samples, and record the intrusion of mercury liquid under different pressures. The described mercury intrusion dynamic parameters describe the key measurement indicators during the process of mercury liquid invading rock pores, including the mercury injection pressure, which refers to the pressure value required to press mercury liquid into the pores of rock samples, and the unit is usually MPa. According to the aforementioned Washburn equation, the mercury injection pressure is inversely proportional to the pore throat radius, so it can reflect the size characteristics of rock pore throats. The mercury injection saturation refers to the percentage of the pore volume invaded by mercury liquid in the total pore volume of rock samples under a specific pressure, which reflects the filling degree of rock pores under a specific pressure.

[0072] S2: Calculate the logarithmic values of mercury intrusion dynamic parameters according to the mercury intrusion curve of the rock sample.

[0073] Among them, the logarithmic values of the mercury intrusion dynamic parameters in step S2 include: the logarithmic value of the mercury injection pressure, and the logarithmic value of the mercury injection saturation.

[0074] Furthermore, step S2 is a processing link for logarithmic conversion of mercury intrusion dynamic parameters on the basis of obtaining experimental raw data, aiming to convert data on a linear scale into a logarithmic scale to prepare for subsequent fractal analysis. The logarithmic values of the mercury intrusion dynamic parameters are the key terms in this step. It refers to the results obtained by performing logarithmic operations on the mercury intrusion dynamic parameters obtained in S1, specifically including the logarithmic value of the mercury injection pressure, that is, taking the common logarithm of the mercury injection pressure. The logarithmic processing compresses the pressure value from a range of several orders of magnitude to a narrower interval, which helps to identify power-law relationships in subsequent analysis. And the logarithmic value of the mercury injection saturation is taking the common logarithm of the mercury injection saturation. Similarly, the conversion helps to linearize the fractal relationship.

[0075] According to fractal theory, when an object has fractal characteristics, there is usually a power-law relationship between its characteristic parameters. In step S2 of the present invention, through logarithmic conversion, the power-law relationship can be transformed into a linear relationship, providing a necessary mathematical basis for linear regression analysis in subsequent steps.

[0076] S3: Fit the logarithmic values of the mercury intrusion dynamic parameters to obtain a linear regression fitting line.

[0077] Furthermore, step S3, on the basis of obtaining the logarithmic values in S2, performs linear regression analysis on these logarithmic values through statistical methods, aiming to determine the linear relationship between the logarithmic value of the mercury injection pressure and the logarithmic value of the mercury injection saturation, providing a basis for subsequent calculation of the pore fractal dimension. The linear regression fitting line is a straight-line equation fitted from a series of data points through statistical techniques such as the least squares method.

[0078] Among them, the expression of the linear regression fitting straight line in step S3 is:

[0079] lgS Hg = k·lgp c - A;

[0080] Among them, lgS Hg is the logarithm of the mercury intrusion saturation, k is the slope of the linear regression fitting straight line, lgp c is the logarithm of the mercury intrusion pressure, and A is the intercept of the linear regression fitting straight line.

[0081] Furthermore, in the above formula, the logarithm of the mercury intrusion saturation is the dependent variable, representing the logarithm of the percentage of the pore volume of the mercury intrusion into the rock sample in the total pore volume under a specific pressure. The slope of the linear regression fitting straight line is directly used for subsequent calculation of the pore fractal dimension of the rock, while the logarithm of the mercury intrusion pressure is the independent variable, representing the logarithm of the pressure required to press the mercury into the pores of the rock sample. The intercept of the linear regression fitting straight line is the constant term of the fitting equation.

[0082] S4: Calculate the pore fractal dimension of the rock according to the slope of the linear regression fitting straight line.

[0083] Among them, the expression of the pore fractal dimension in step S4 is:

[0084] D = k + 3;

[0085] Among them, D is the pore fractal dimension and k is the slope of the linear regression fitting straight line.

[0086] The traditional spherical formula method simplifies the pores into spheres and uses the fractal power law to derive a pore fractal formula with water saturation to calculate the pore fractal dimension; while the capillary formula method simplifies the pores into curved circular tubes and uses the fractal power law to derive a pore fractal formula with mercury saturation to calculate the pore fractal dimension. Whether it is a sphere or a circular tube, both have three-dimensional space topology attributes. However, the present invention reconsiders the pore-throat binary structure and coordination number, and simplifies the pores into a ball-stick body, that is, a combination of a sphere and a circular tube. Specifically, the structure of the pore simplification model of the present invention is as Figure 2 shown.

[0087] That is, step S4 of the present invention is based on the fractal power law and the pore-throat binary structure model. Specifically, in the traditional spherical formula method or capillary formula method, the pore fractal dimension is usually limited between 2.0 and 3.0. However, the present invention breaks through this limitation by considering the pore-throat binary structure and coordination number.

[0088] When there are multiple scale - free regions inside the rock, each scale - free region corresponds to a linear regression fitting line. Therefore, multiple pore fractal dimension values can be calculated, indicating that there are multiple co - existing pore - throat structure patterns inside the rock. These different pore fractal dimensions reflect the structural characteristics of the rock within different scale ranges.

[0089] So in step S4, the present invention calculates the pore fractal dimension of the rock through the slope of the linear regression fitting line obtained in S3, and finally obtains the expression for calculating the pore fractal dimension as shown in the above - mentioned expression, providing a key parameter for the subsequent calculation of the rock pore - throat coordination number.

[0090] S5: Calculate the rock pore - throat coordination number according to the pore fractal dimension, and obtain the interval calculation result of the rock pore - throat coordination number. The interval calculation result in step S5 includes:

[0091] The minimum pore - throat coordination number, the maximum pore - throat coordination number, and the average pore - throat coordination number.

[0092] According to a method for calculating the rock pore - throat coordination number based on the pore fractal dimension provided by the present invention, the expression for the minimum pore - throat coordination number is:

[0093]

[0094] The expression for the maximum pore - throat coordination number is:

[0095] n max = D - 2;

[0096] The expression for the average pore - throat coordination number is:

[0097]

[0098] Where n min is the minimum pore - throat coordination number, D is the pore fractal dimension, n max is the maximum pore - throat coordination number, and n avre is the average pore - throat coordination number.

[0099] The coordination number (CoordinationNumber) refers to the number of throats connected to a single pore. For example, if a certain pore is connected to 3 throats, its coordination number is 3. The higher the coordination number, the better the connectivity between pores and the stronger the permeability.

[0100] The minimum coordination number calculated by the present invention corresponds to the pore with the worst connectivity (or the lowest coordination number) in the pore network, the maximum coordination number corresponds to the pore with the best connectivity (or the highest coordination number), and the average coordination number represents the average value of all pore coordination numbers.

[0101] Such as Figure 3As shown in the figure, the present invention also provides a device for calculating the pore throat coordination number of rocks based on the pore fractal dimension, including:

[0102] An acquisition module 100: used to obtain the mercury intrusion curve of a rock sample through a mercury intrusion experiment and obtain the mercury intrusion dynamic parameters of multiple test points;

[0103] A logarithm calculation module 200: used to calculate the logarithm of the mercury intrusion dynamic parameters according to the mercury intrusion curve of the rock sample;

[0104] A fitting module 300: used to fit the logarithm of the mercury intrusion dynamic parameters to obtain a linear regression fitting line;

[0105] A dimension calculation module 400: used to calculate the pore fractal dimension of the rock according to the slope of the linear regression fitting line;

[0106] A coordination number calculation module 500: used to calculate the pore throat coordination number of the rock according to the pore fractal dimension and obtain the interval calculation result of the pore throat coordination number of the rock.

[0107] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0108] The present invention also provides a device for calculating the pore throat coordination number of rocks based on the pore fractal dimension, including:

[0109] A memory and at least one processor, wherein instructions are stored in the memory;

[0110] At least one of the processors invokes the instructions in the memory so that a device for calculating the pore throat coordination number of rocks based on the pore fractal dimension executes a method for calculating the pore throat coordination number of rocks based on the pore fractal dimension as described in any one of the above.

[0111] The present invention also provides a computer-readable storage medium, on which instructions are stored, and when the instructions are executed by a processor, a method for calculating the pore throat coordination number of rocks based on the pore fractal dimension as described in any one of the above is implemented.

[0112] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0113] The following describes a method for calculating pore throat coordination number based on pore fractal dimension provided by the present invention in combination with specific embodiments.

[0114] This embodiment takes an oilfield with an area of about 5000 km 2 as an example. The main production layer of the oilfield is the Chang 8 oil group of the Yanchang Formation in the Triassic, belonging to the delta front sedimentation. The average porosity of the reservoir is 12.1%, and the average permeability is 10 -3 μm 2 , belonging to a low-porosity and low-permeability reservoir.

[0115] Taking the mercury injection curve of the 6# rock sample (2064.1 m) in Well X105 in the Chang 8 oil group of the above oilfield as an example, the basic data of the mercury injection experiment of this rock sample is shown in Table 1, and the test mercury injection curve data is shown in Table 2. The corresponding mercury injection curve is as Figure 4 shown.

[0116] Table 1 Basic data table of mercury injection experiment of rock sample

[0117] Core number: 6# <![CDATA[Pore volume (cm 3 ):]]> 1.51 Sample weight (g): 30.02 Well number: West 105 <![CDATA[Sample volume (cm 3 ):]]> 12.17 Lithology: Grey oil-impregnated fine sandstone Well depth (m): 2064.1 Porosity (%): 12.47 Stratigraphic horizon: <![CDATA[Length 81]]> <![CDATA[Permeability (×10 -3 μm 2 ):]]> 0.216

[0118] Table 2 Data table of mercury injection curve of rock sample

[0119]

[0120]

[0121] According to the above mercury injection curve data of the rock sample (mercury injection pressure and mercury injection saturation), calculate the logarithms of the mercury injection pressure and mercury injection saturation at multiple test points in the mercury injection curve of the rock sample. The calculation results are shown in Table 3.

[0122] Table 3 Calculation result table of logarithms of mercury injection pressure and mercury injection saturation of rock sample

[0123]

[0124]

[0125]

[0126] Based on the logarithm of the mercury injection pressure and the mercury injection saturation at multiple test points in the mercury injection curve of the rock sample, with the logarithm of the mercury injection pressure lgcp as the independent variable and the logarithm of the mercury injection saturation lgHgS as the dependent variable, a scatter plot of lgcp and lgHgS is plotted and linearly regressed and fitted.

[0127] The specific fitting results are as Figure 5 shown. It can be seen from Figure 5 that there are three fitting straight lines for the 6# rock sample, and the expressions of the obtained straight lines are respectively:

[0128] The first fitting straight line, and the first fitting straight line is the straight line fitted by the green marked points, and the expression is:

[0129] y = 9.1785x + 2.9656;

[0130] R 2 = 0.9044;

[0131] The second fitting straight line, and the second fitting straight line is the straight line fitted by the blue marked points, and the expression is:

[0132] y = 1.6764x + 0.1752;

[0133] R 2 = 0.996;

[0134] The third fitting straight line, and the third fitting straight line is the straight line fitted by the blue marked points, and the expression is:

[0135] y = 0.2216x + 1.4696;

[0136] R 2 = 0.9576;

[0137] From the above three expressions, it can be seen that their slopes are 9.1785 → 1.6764 → 0.2216 in descending order, which indicates that the pores of this rock sample have a three-segment fractal characteristic, and there are three scale-free regions (low-pressure region, medium-pressure region, high-pressure region) inside the pores. Each scale-free region corresponds to a type of pore-throat structure. Therefore, the three types of pore-throat structures coexist inside the pores of the 6# rock sample in this embodiment.

[0138] Subsequently, according to the slope of the linear regression fitting straight line, the pore fractal dimension is determined, and the corresponding pore-throat coordination number value is calculated through the obtained pore fractal dimension and the corresponding minimum pore-throat coordination number, maximum pore-throat coordination number, and average pore-throat coordination number. The final calculation results of the pore-throat coordination number are shown in Table 4.

[0139] Table 4 Calculation results of pore fractal dimension and pore-throat coordination number of rock samples

[0140] Parameter Low pressure area Medium pressure area High pressure area Linear slope 9.1785 1.6764 0.2216 Pore fractal dimension 12.1785 4.6764 3.2216 Minimum pore-throat coordination number 6.12 1.12 0.15 Maximum pore-throat coordination number 10.18 2.68 1.22 Average pore-throat coordination number 8.15 1.90 0.68

[0141] As can be seen from Table 4, from the low-pressure area → medium-pressure area → high-pressure area, as the mercury injection pressure increases or the pore throat radius decreases, the pore fractal dimension gradually decreases, from 12.1785 → 4.6764 → 3.2216, and the average pore throat coordination number decreases in turn from 8.15 → 1.90 → 0.68, indicating that the number of throats matching the rock pore channels continuously decreases, and the complexity of the pore throat structure decreases accordingly.

[0142] A method and device for calculating the pore throat coordination number of rock based on fractal dimension provided by the present invention utilize fractal theory combined with mercury injection experiments to obtain the pore fractal dimension, a characteristic parameter representing the irregularity degree of the pore throat structure. Considering the binary structure and coordination number of the pore throat, the pore fractal dimension is deeply integrated with the pore throat topological structure, providing a method for quickly and quantitatively determining the pore throat coordination number of rock based on the pore fractal dimension.

[0143] Case analysis shows that this method can not only determine the average value of the pore throat coordination number of rock, but also determine its minimum and maximum values, giving the fluctuation range of the pore throat coordination number. The method of the present invention is simple, easy to implement and highly operable. It not only provides a new technical approach for the quantitative calculation of the pore throat coordination number of rock, but also has important practical significance for accurately characterizing the configuration relationship and structural complexity of the rock pore throat, establishing a scientific system for quantitative evaluation of reservoir micro-pore throats, and guiding the research on pore throat network simulation, etc., and has a very broad application prospect.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit 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 described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A calculation method for the pore throat coordination number of rock based on the pore fractal dimension, characterized in that Including: S1: Obtain the mercury intrusion curve of the rock sample through mercury intrusion experiments to obtain the dynamic parameters of mercury intrusion at multiple test points; S2: Calculate the logarithmic values of the dynamic parameters of mercury intrusion according to the mercury intrusion curve of the rock sample; S3: Fit the logarithmic values of the dynamic parameters of mercury intrusion to obtain a linear regression fitting line; S4: Calculate the pore fractal dimension of the rock according to the slope of the linear regression fitting line; S5: Calculate the pore throat coordination number of the rock according to the pore fractal dimension to obtain the interval calculation result of the pore throat coordination number of the rock.

2. The method for calculating the pore throat coordination number of rock based on the pore fractal dimension according to claim 1, wherein The dynamic parameters of mercury intrusion in step S1 include: Mercury intrusion pressure, mercury intrusion saturation.

3. The method for calculating the pore throat coordination number of a rock based on the pore fractal dimension according to claim 2, wherein The logarithmic values of the dynamic parameters of mercury intrusion in step S2 include: Logarithmic value of mercury intrusion pressure, logarithmic value of mercury intrusion saturation.

4. A method for calculating the pore throat coordination number of a rock based on the pore fractal dimension according to claim 1, characterized in that, The expression of the linear regression fitting line in step S3 is: lgS Hg = k·lgp c - A; where, lgS Hg is the logarithm of mercury intrusion saturation, k is the slope of the linear regression fitting line, lgp c is the logarithm of mercury intrusion pressure, and A is the intercept of the linear regression fitting line.

5. A method for calculating the pore throat coordination number of rock based on the pore fractal dimension according to claim 1, characterized in that The expression of the pore fractal dimension in step S4 is: D = k + 3; Where D is the pore fractal dimension and k is the slope of the linear regression fitting line.

6. The calculation method of rock pore-throat coordination number based on pore fractal dimension according to claim 1, characterized in that The interval calculation result in step S5 includes: Minimum pore throat coordination number, maximum pore throat coordination number, average pore throat coordination number.

7. The calculation method of rock pore throat coordination number based on pore fractal dimension according to claim 6, characterized in that The expression of the minimum pore throat coordination number is: The expression of the maximum pore throat coordination number is: n max = D - 2; The expression of the average pore throat coordination number is: Among them, n min is the minimum pore-throat coordination number, D is the pore fractal dimension, and n max is the maximum pore-throat coordination number, and n avre is the average pore-throat coordination number.

8. A device for calculating the pore-throat coordination number of a rock based on the pore fractal dimension, characterized in that, Including: Acquisition module: used to obtain the mercury intrusion curve of the rock sample through mercury intrusion experiments to obtain the dynamic parameters of mercury intrusion at multiple test points; Logarithmic calculation module: used to calculate the logarithmic values of the dynamic parameters of mercury intrusion according to the mercury intrusion curve of the rock sample; Fitting module: used to fit the logarithmic values of the dynamic parameters of mercury intrusion to obtain a linear regression fitting line; Dimension calculation module: used to calculate the pore fractal dimension of the rock according to the slope of the linear regression fitting line; Coordination number calculation module: used to calculate the pore throat coordination number of the rock according to the pore fractal dimension to obtain the interval calculation result of the pore throat coordination number of the rock.

9. A rock pore-throat coordination number calculation device based on pore fractal dimension, characterized in that, Including: A memory and at least one processor, wherein instructions are stored in the memory; At least one of the processors calls the instructions in the memory so that a device for calculating the pore throat coordination number of a rock based on the pore fractal dimension executes a method for calculating the pore throat coordination number of a rock based on the pore fractal dimension according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, Instructions are stored on the computer-readable storage medium, and when the instructions are executed by the processor, a method for calculating the pore throat coordination number of a rock based on the pore fractal dimension according to any one of claims 1-7 is implemented.

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