Method for explaining real permeability of reservoir in flower-plaque carbonate rocks

Abstract

The invention relates to a method for explaining the real permeability of a reservoir in mottled carbonate rock. The method comprises the following steps: constructing a color standard of a compact part in a core of the mottled carbonate rock; identifying the core sample meeting the color standard; scanning the cross section of the core sample, calibrating a scanning result according to a core sample identification result, and calculating a reservoir proportion and a reservoir volume proportion of each cross section of the core sample; measuring the surface volume and the rock skeleton volume of the rock core sample, and correcting the real reservoir porosity of the rock core sample in combination with the reservoir volume ratio; measuring the permeability of the rock core sample, and correcting the real reservoir permeability of the rock core sample in combination with the reservoir proportion; and constructing a reservoir real porosity and reservoir real permeability chart, calculating the total porosity of the reservoir in the mottled carbonate rock according to the logging curve, and constructing a reservoir real permeability interpretation model in the mottled carbonate rock by combining the chart. According to the method, the blank of porosity and permeability logging interpretation of the patchy carbonate reservoir is filled up.

Description

Technical Field

[0001] The invention belongs to the technical field of oil and gas field development, and particularly relates to a method for interpreting the true permeability of reservoirs in piebald carbonate rocks. Background Art

[0002] Marine carbonate rocks are rich in oil and gas resources, but marine carbonate rock formations are extremely heterogeneous, and marine carbonate rock formations of considerable scale show special "patchwork" heterogeneity characteristics. "Patchwork" is named based on the shape and meaning of the rock structural morphological characteristics. Patchwork carbonate rocks usually show patches of white, dark gray and other colors; patchwork carbonate formations usually show complex porosity-permeability relationships in core sample testing and analysis, and the microscopic pore structure of patchwork carbonate rocks usually shows multimodal. Marine patchwork carbonate formations have similar surface characteristics but different geological and production characteristics: some marine patchwork carbonate formations show poor reservoirs with low production capacity in both logging and production; some marine patchwork carbonate formations show tight reservoirs or non-reservoirs in logging, but show high-yield layers in production.

[0003] Through thin-section microscopic identification, the development of mottled carbonate rocks is not controlled by lithology, and white and dark gray patches are developed in all types of lithology. Microscopic observation of pore structure shows that the pores between the clastic particles of white patch carbonate rocks are not developed or isolated pores are developed, and the pore positions are cemented by spar calcite. The spar calcite cementation of dark patch carbonate rocks is weak, and the pores between the clastic particles are developed. The dark patches in the mottled carbonate formation are reservoirs, which are developed between the white tubercle-like patches of non-reservoir layers. Through thin-section microscopic identification, the development width of the dark patch reservoir is mostly between 1-2 cm, while the diameter of the cylindrical core samples used for laboratory determination of porosity and permeability is usually 2.5 cm or 3.8 cm, which is larger than the development width of the dark patches. The reservoir core samples drilled from the core samples include reservoirs (dark patches) and non-reservoir layers (white patches). Therefore, the influence of white non-reservoir patches is not eliminated when the porosity and permeability are measured in the laboratory, which results in that the porosity and permeability measured in the laboratory cannot reflect the true porosity and permeability of the reservoir (dark patches) in the mottled carbonate formation.

[0004] In addition, logging interpretation of porosity and permeability is an important part of reservoir characterization research. The number of coring wells in an oil field and the coverage of the oil field are far less than those of non-coring wells, and almost all wells have logging curves. To conduct a more objective three-dimensional characterization of the entire reservoir, it is often necessary to calibrate the core logging and then use the logging curve interpretation to calculate the porosity and permeability. The well logging of the mottled carbonate development section reflects the comprehensive electrical characteristics of the reservoir (dark patches) and non-reservoir (white patches). The current logging interpretation means and methods cannot eliminate the influence of non-reservoir (white patches) and accurately interpret the porosity and permeability of the reservoir (dark patches). Summary of the invention

[0005] In view of the above problems, the technical solution adopted by the present invention is as follows: a method for interpreting the true permeability of a reservoir in a mottled carbonate rock, the method comprising the following steps:

[0006] S1. Construct the color standard of the dense part of the core of the piebald carbonate rock;

[0007] S2, identifying core samples that meet the color standard;

[0008] S3, scanning the cross section of the core sample, calibrating the scanning result according to the core sample identification result, and calculating the reservoir proportion and reservoir volume proportion of each cross section of the core sample;

[0009] S4. Determine the surface volume and rock skeleton volume of the core sample, and correct the true reservoir porosity of the core sample in combination with the reservoir volume ratio;

[0010] S5. Determine the permeability of the core sample, and correct the true reservoir permeability of the core sample in combination with the reservoir proportion;

[0011] S6. Constructing a map of reservoir true porosity and reservoir true permeability;

[0012] S7. Calculate the total porosity of the reservoir in the piebald carbonate rock according to the well logging curve, and construct a true permeability interpretation model of the reservoir in the piebald carbonate rock in combination with the above-mentioned plate.

[0013] Further, step S1 includes: selecting core samples including white oil-free reservoirs and brown oil-containing reservoirs to make casting thin sections, and observing the casting thin sections under a microscope;

[0014] Circle the distribution range of the white oil-free reservoir on the casting thin section, extract the color characteristics of the white oil-free reservoir, and construct the color standard of the white oil-free reservoir.

[0015] Further, step S2 includes:

[0016] According to the HIS color model, component histogram distribution is made for the three components of hue H, saturation S and brightness I;

[0017] According to the component histogram distribution, the weights of the three components of hue H, saturation S and brightness I are determined;

[0018] Set the color recognition result threshold;

[0019] The pixel points of the core image are calculated. If the calculation result is greater than the threshold, the core is identified as a white oil-free reservoir.

[0020] Further, step S3 includes:

[0021] Scan the core sample, scan n cross sections at equal distances in the horizontal direction, and select two mutually perpendicular longitudinal sections in the vertical direction to obtain a scanned grayscale image;

[0022] The scanned grayscale image is calibrated according to the core recognition result, and the grayscale image segmentation threshold is defined;

[0023] When the threshold reaches the effect of reservoir and non-reservoir areas in carbonate rocks circled by thin section observation, this threshold is used as the division standard for other sections;

[0024] Count the area ratio of reservoir to non-reservoir in each section, and calculate the proportion of reservoir in each section A i , where: i = 1, 2, ..., n; and calculate the reservoir volume percentage m.

[0025] Furthermore, the definition of the grayscale image segmentation threshold includes:

[0026] Assuming that F(i, j) represents the gray value of the image pixel, the pixel with a gray value of 1 after separation represents the target object, and the pixel with a gray value of 0 represents the image background. The target object is obtained by the following formula:

[0027]

[0028] Among them, g(i, j) is the value of the target object; i, j are the pixel positions in the x and y directions respectively; M, N are the number of pixels of the image in the x and y directions respectively; T is the threshold.

[0029] Furthermore, the reservoir volume ratio m is calculated as:

[0030]

[0031] Among them, V c is the volume of the reservoir; V f is the total volume of the core sample; L is the length of the core sample; n is the number of cross sections scanned at equal distances in the horizontal direction; A iis the proportion of reservoir in each cross section.

[0032] Further, step S4 includes:

[0033] The apparent volume of the core sample is: Among them, V f It represents the surface volume of the core sample, D represents the diameter of the core sample, and L represents the length of the core sample;

[0034] The rock skeleton volume Vs is determined by the gas expansion method;

[0035] The true porosity of the reservoir is:

[0036] φ=V p / (V1+V p )×100=(V f -V s ) / (m·V f +(V f -V s ))×100, where φ represents the true porosity of the reservoir; V p represents the rock pore volume, V p =V f -V s ; V1 is the rock skeleton volume of the reservoir.

[0037] Further, step S5 includes:

[0038] The permeability k was determined by gas measurement method. g for: Wherein, p1 represents the inlet pressure; p2 represents the outlet pressure; p0 represents the atmospheric pressure; μ represents the gas viscosity; Q0 ​​represents the volume flow rate of the gas under the atmospheric pressure p0; A represents the cross-sectional area of ​​the core sample; L represents the length of the core sample;

[0039] Assuming that the permeability of each reservoir is equal, the reservoir proportion of each cross section is A. i , and A i > 0, where: i = 1, 2, ..., n; the calculation formula for the true permeability k of the reservoir derived from the Darcy formula is:

[0040]

[0041] Further, step S6 includes: constructing a two-dimensional plane map of the reservoir true porosity and the reservoir true permeability according to the reservoir true porosity and the reservoir true permeability, and the regression relationship of the two-dimensional plane map is: k = a·e b·φ ; Among them, a and b are constants obtained through formula regression of the two-dimensional plane plate.

[0042] Further, step S7 includes: extracting density logging characteristic parameters of the white oil-free reservoir section, and establishing a calculation formula for the development ratio of effective reservoirs in the piebald carbonate rock:

[0043] Where x represents the effective reservoir development ratio in the piebald carbonate rock; RHOB represents the density logging value of the piebald reservoir development section; RHOB 非花斑状 Indicates the density logging value of the reservoir adjacent to the non-patchwork reservoir development section;

[0044] The total porosity is calculated based on the well logging curve. Based on the total porosity and the development ratio of effective reservoirs in the piebald carbonate rock, the true porosity of the reservoir in the piebald carbonate rock is calculated as follows:

[0045] Φ 有效 =φ 总 / x, where Φ 有效 represents the real porosity of the effective reservoir in the piebald carbonate rock, φ 总 represents the total porosity;

[0046] The true permeability logging interpretation model of the effective reservoir of the piebald carbonate rock is:

[0047] Among them, k 有效 It represents the true permeability of the effective reservoir of the piebald carbonate rock.

[0048] Compared with the prior art, the present invention has the following beneficial effects: compared with the conventional laboratory rock porosity and permeability determination methods, the present invention fills the gap in the porosity and permeability logging interpretation of the mottled carbonate reservoir, and improves the accuracy of porosity and permeability interpretation, which specifically includes the following aspects:

[0049] (1) Thin sections prepared from small cylindrical samples were used for thin section identification to delineate the distribution range of reservoirs (dark patches) and non-reservoir layers (white patches) in the mottled carbonate rocks and calculate their area percentages;

[0050] (2) The distribution range of reservoirs (dark patches) and non-reservoir layers (white patches) delineated by core thin sections is used to calibrate the CT scan images, determine the grayscale image segmentation thresholds of reservoirs (dark patches) and non-reservoir layers (white patches), and combine multiple CT scan cross-sectional images to calculate the volume ratios of reservoirs (dark patches) and non-reservoir layers (white patches);

[0051] (3) Corrected the porosity and permeability values ​​of the reservoir (dark patches) in the mottled carbonate rocks;

[0052] (4) This method can be widely used in the logging interpretation of porosity and permeability of mottled carbonate reservoirs.

[0053] Other features and advantages of the present invention will be described in the following description, and part of them will become obvious from the description, or be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained through the description and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0055] Figure 1 A schematic diagram of a method for interpreting the true permeability of a reservoir in a piebald carbonate rock;

[0056] Figure 2a , Figure 2b Schematic diagram of the core sample sampling locations for the white patch reservoir and the oil-bearing brown reservoir, respectively;

[0057] Figure 3 Schematic diagram of thin section identification results of the distribution of rock structures of piebald carbonate reservoirs (dark patches) and non-reservoir (white patches);

[0058] Figure 4 This is a schematic diagram of the distribution of rock structures of mottled carbonate reservoirs (dark patches) and non-reservoir (white patches) in CT scan grayscale images;

[0059] Figure 5 Schematic diagram of the location selection and CT scanning method for core thin section samples;

[0060] Figure 6 This is a schematic diagram of the experimental device for testing the gas expansion method;

[0061] Figure 7a , Figure 7b The porosity-permeability relationship of rock before and after porosity correction measured in the laboratory is shown.

[0062] Figure numerals: 1, core chamber; 2, standard chamber; 3, pressure regulating valve; 4, gas source valve; 5, sample valve; 6, vent valve; 7, gas supply valve; 8, gas source. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] like Figure 1 As shown, the present invention proposes a method for interpreting the true permeability of a reservoir in a piebald carbonate rock, the method comprising the following steps:

[0065] S1. Construct the color standard of the dense part of the core of the piebald carbonate rock;

[0066] S2, identifying core samples that meet the color standard;

[0067] S3, scanning the cross section of the core sample, calibrating the scanning result according to the core sample identification result, and calculating the reservoir proportion and reservoir volume proportion of each cross section of the core sample;

[0068] S4. Determine the surface volume and rock skeleton volume of the core sample, and correct the true reservoir porosity of the core sample in combination with the reservoir volume ratio;

[0069] S5. Determine the permeability of the core sample, and correct the true reservoir permeability of the core sample in combination with the reservoir proportion;

[0070] S6. Constructing a map of reservoir true porosity and reservoir true permeability;

[0071] S7. Calculate the total porosity of the reservoir in the piebald carbonate rock according to the well logging curve, and construct a true permeability interpretation model of the reservoir in the piebald carbonate rock in combination with the above-mentioned plate.

[0072] Specifically, in step S1, the core sample is selected from the piebald carbonate rock development section (such as Figure 2a The red frame) was selected, and the core samples including white patches and brown patches were selected (such as Figure 2b As shown, Figure 2b Shown from Figure 2a The core taken from the red frame in the middle was used to make a casting thin section, and the casting thin section was observed under a microscope. Figure 3 As shown, Figure 3 is from Figure 2b The thin slices made from the rock in the red box. Figure 3 It can be seen that the white patch part has undeveloped pores under a microscope, while the brown patch part has developed pores under a microscope; the distribution range of the white oil-free tight reservoir is observed, the color of the white oil-free tight reservoir is extracted, and the color standard is established.

[0073] In step S1, the purpose of observing the thin section under a microscope is to clarify the pore characteristics of the white oil-free tight reservoir under the microscope, and to ensure that the circled white oil-free tight reservoir is a non-effective reservoir with no or very few connected pores.

[0074] In step S1, the HSI model is used to establish a color standard. The HSI model includes three components: hue H, saturation S and brightness I. Chroma H is the characteristic that distinguishes colors from each other. It is determined by the wavelength of each component in the visible light spectrum, which is what we usually call red, green, blue, etc.; saturation S refers to the purity of the color, reflecting the intensity of the color. The saturation of pure white is zero, while the saturation of pure spectral colors is the highest; brightness I refers to the intensity of light stimulation caused by light to the human eye. Obviously, it is related to the energy of light. The brightness of light is the brightness of the color to humans. The conversion of the same color from RGB (representing the colors of the three channels of red, green, and blue) to HSI is a nonlinear change. For any three R, G, and B values ​​in the range of [0,1], the I, S, and H components of the corresponding HSI model can be calculated by the following formula:

[0075]

[0076]

[0077]

[0078]

[0079] In step S2, according to the extracted white oil-free tight reservoir color standard, the fuzzy cluster analysis method is used to identify the cores that meet the standard color. First, the extracted color is subjected to the HIS model, and the component histogram distribution is made for the three components H, I, and S respectively, and its membership function can be specified as: Among them, u0 is the three components of H, I, and S; u mean In order to extract the expectation of the three components H, I, and S in color, the mean value can be used instead in practical applications, u fchis the variance of the sample. Secondly, determine the weights of the three components in the H, I, and S color spaces; in the H, I, and S color spaces, I changes from black (0) at the bottom to white (1) at the top, reflecting the brightness information of the image; the default weights of the three feature quantities (H, I, and S) are set to 0.3, 0.4, and 0.3, respectively. Thirdly, determine the threshold of the color judgment result; after actually running this system, it is found that after learning a certain amount of acquisition points, the program can distinguish different colors with a difference of more than 85%, and after setting a threshold of 0.90, the program can recognize more than 80% of the colors at a time, and the recognition rate reaches more than 95%, so the threshold is defined as 0.90 here. Finally, perform color recognition to determine whether the core image belongs to a white, oil-free, tight reservoir. Judge and calculate each pixel:

[0080] A=0.3×μ(H)+0.4×μ(I)+0.3×μ(S), where A represents the similarity between the color of the pixel and the extracted color standard. If A>0.9, the pixel A belongs to the white oil-free tight reservoir, otherwise it does not belong to the white oil-free tight reservoir.

[0081] In step S3, the existing core micrometer CT scanning technology is used to perform CT scanning on the small cylindrical core sample, such as Figure 5 As shown in Figure 1, n cross sections are scanned at equal distances in the horizontal direction, and two mutually perpendicular longitudinal sections are selected in the vertical direction. After performing noise reduction processing on the scanned image, the following is obtained: Figure 4 The grayscale image of the CT scan is shown in the figure. The darker the color (dark patches), the lower the density of the area, which means the area is a "speckled" carbonate reservoir. The brighter the color (white patches), the greater the density and the denser the area, which means the area is a "speckled" carbonate non-reservoir. The first cross-sectional grayscale image of the CT scan is calibrated by observing the range of the "speckled" carbonate reservoir (dark patches) and non-reservoir (white patches) circled by thin sections, which serves as the basis for determining the grayscale image segmentation threshold.

[0082] The grayscale image segmentation threshold is defined as follows: Assuming F(i, j) represents the grayscale value of the image pixel, after separation, the pixel with a grayscale value of 1 represents the target object, and the pixel with a grayscale value of 0 represents the image background. The target object is obtained by the following formula:

[0083]

[0084] Among them, g(i, j) is the value of the target object; i, j are the pixel positions in the x and y directions respectively; M, N are the number of pixels of the image in the x and y directions respectively; T is the threshold. When the threshold is set to achieve the effect of the reservoir (dark patches) and non-reservoir (white patches) areas in the "speckled" carbonate rock calibrated by thin section observation, this threshold is used as the division standard for other sections. Count the area ratio of the reservoir and non-reservoir drawn in each section, and calculate the reservoir (dark patches) proportion Ai of each section, where: i=1, 2,..., n; calculate the reservoir (dark patches) volume proportion m, 0<m≤1, and the non-reservoir (white patches) volume proportion is 1-m. The calculation formula for the reservoir volume proportion m is:

[0085]

[0086] Among them, V c is the volume of the reservoir; V f is the total volume of the core sample; L is the length of the core sample; n is the number of cross sections scanned at equal distances in the horizontal direction; A i is the proportion of reservoir in each cross section.

[0087] In step S4, the apparent volume of the core small cylindrical sample is: Among them, V f represents the surface volume of the core sample, D represents the diameter of the core sample, and L represents the length of the core sample. The rock skeleton volume Vs is determined by the gas expansion method; the gas expansion method uses an experimental device such as Figure 6 As shown, it is known that the volume of core chamber 1 is V, and the volume of rock skeleton is Vs; the remaining volume after the core is placed is V-Vs, and the pressure of core chamber 1 is P0; the volume of standard chamber 2 is ΔV, and the indoor pressure of standard chamber 2 is P2 (relative). A sample valve 5 is connected between core chamber 1 and standard chamber 2, and a vent valve 6, a gas supply valve 7, a pressure regulating valve 3 and a gas source valve 4 are connected between standard chamber 2 and gas source 8. Open the sample valve 5, and close the gas source valve 4, the pressure regulating valve 3, the gas supply valve 7 and the vent valve 6 at the same time, so that the pressure of standard chamber 2 expands toward core chamber 1, and the final pressure balance is P1 (relative). Assuming that the process is an isothermal process, according to Boyle's law, it can be obtained that:

[0088] ΔV·P2=(V-Vs+ΔV)·P1; Vs=V-ΔV(P2-P1) / P1;

[0089] The surface volume V of the small cylindrical sample obtained according to the above steps f , rock skeleton volume Vs, reservoir (dark patch) volume proportion m, correct the porosity value, and calculate the true porosity of the reservoir:

[0090] φ=V p / (V1+V p)×100=(V f -V s ) / (m·V f +(V f -V s ))×100, where φ represents the true porosity of the reservoir; V p represents the rock pore volume, V p =V f -V s ; V1 is the rock skeleton volume of the reservoir.

[0091] In step S5, according to GB / T 29172-2012 standard, domestic oil fields mainly use gas logging method to determine the conventional core permeability k g This method uses pressurized gas to establish a pressure difference at both ends of the rock being tested and measures the gas flow rate at the outlet. Core permeability k g The calculation formula is: Among them, p1 represents the inlet pressure; p2 represents the outlet pressure; p0 represents the atmospheric pressure; μ represents the gas viscosity; Q0 ​​represents the volume flow rate of the gas under the atmospheric pressure p0; A represents the cross-sectional area of ​​the core sample; L represents the length of the core sample. According to the following assumptions: ① The permeability of the reservoir (dark patches) is equal, which is k; ② The non-reservoir (white patches) is impermeable; ③ The reservoir (dark patches) in each section in step 2 accounts for A i , and A i > 0, where: i = 1, 2, ..., n. The calculation formula for the true permeability k of the reservoir (dark patches) is derived from the Darcy formula:

[0092] In step S6, a two-dimensional plane map is established based on the reservoir true porosity φ calculated in step S4 and the reservoir true permeability k calculated in step S5, as shown in FIG. Figure 7b As shown, the relationship between the two-dimensional plane plate regression is: k = ae b·φ ; where a and b are constants obtained by regression of the two-dimensional plane graph. Compare the graph obtained by fitting the porosity and permeability before correction (such as Figure 7a As shown in the figure, the corrected reservoir true porosity φ and reservoir true permeability k have better fitting effects, and the porosity-permeability relationship is significantly improved, laying a foundation for the subsequent reservoir permeability logging interpretation.

[0093] In step S7, the density logging characteristic parameters of the white oil-free reservoir section are extracted, and the known carbonate skeleton density (2.71 g / cm 3 ), the formula for calculating the development ratio of effective reservoirs in piebald carbonate rocks is established as follows: Where x represents the effective reservoir development ratio in the piebald carbonate rock; RHOB represents the density logging value of the piebald reservoir development section; RHOB 非花斑状 Indicates the density logging value of the reservoir adjacent to the non-patchwork reservoir development section; the total porosity is calculated based on the logging curve, and the total porosity calculation formula is:

[0094] Among them, φ 总 represents the total porosity; RHOB represents the density logging value of the piebald reservoir development section; RHOB 地层水 Indicates the density of formation water.

[0095] According to the total porosity and the development ratio of effective reservoirs in the piebald carbonate rock, the true porosity of the reservoir in the piebald carbonate rock is calculated as: 有效 =φ 总 / x, where Φ 有效 Indicates the true porosity of the effective reservoir in the piebald carbonate rock, Φ 总 represents the total porosity; the true permeability logging interpretation model of the effective reservoir of the piebald carbonate rock is: Among them, k 有效 It represents the true permeability of the effective reservoir of the piebald carbonate rock.

[0096] In summary, the method proposed in the present invention adds the links of casting thin section identification and CT scanning image recognition calculation on the basis of the traditional laboratory determination of rock porosity and permeability, and depicts the volume proportion m of the reservoir (dark patch) by calibrating the CT scanning image with casting thin section. Combined with the porosity and permeability obtained by conventional traditional methods, the laboratory determination of rock porosity and permeability correction formulas for "speckled" carbonate reservoirs are established; and the laboratory determination of rock porosity and permeability methods and logging interpretation methods for "speckled" carbonate reservoirs are improved, providing more objective porosity and permeability values ​​for reservoir reserve calculation, laying the foundation for objectively evaluating the economic value of oil reservoirs and formulating development strategies.

[0097] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions 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 method for interpreting the true permeability of reservoirs in piebald carbonate rocks, characterized in that: The method comprises the following steps: S1. Construct the color standard of the dense part of the core of the piebald carbonate rock; S2, identifying core samples that meet the color standard; S3, scanning the cross section of the core sample, calibrating the scanning result according to the core sample identification result, and calculating the reservoir proportion and reservoir volume proportion of each cross section of the core sample; S4. Determine the surface volume and rock skeleton volume of the core sample, and correct the true reservoir porosity of the core sample in combination with the reservoir volume ratio; S5. Determine the permeability of the core sample, and correct the true reservoir permeability of the core sample in combination with the reservoir proportion; S6. Constructing a map of reservoir true porosity and reservoir true permeability; S7. Calculate the total porosity of the reservoir in the piebald carbonate rock according to the well logging curve, and construct a true permeability interpretation model of the reservoir in the piebald carbonate rock in combination with the above-mentioned plate.

2. The method according to claim 1, characterized in that: Step S1 includes: Core samples including white oil-free reservoirs and brown oil-bearing reservoirs were selected to prepare casting thin sections, and the casting thin sections were observed under a microscope; Circle the distribution range of the white oil-free reservoir on the casting thin section, extract the color characteristics of the white oil-free reservoir, and construct the color standard of the white oil-free reservoir.

3. The method according to claim 1, characterized in that Step S2 includes: According to the HIS color model, component histogram distribution is made for the three components of hue H, saturation S and brightness I; According to the component histogram distribution, the weights of the three components of hue H, saturation S and brightness I are determined; Set the color recognition result threshold; The pixel points of the core image are calculated. If the calculation result is greater than the threshold, the core is identified as a white oil-free reservoir.

4. The method according to claim 3, characterized in that: Step S3 includes: Scan the core sample, scan n cross sections at equal distances in the horizontal direction, and select two mutually perpendicular longitudinal sections in the vertical direction to obtain a scanned grayscale image; The scanned grayscale image is calibrated according to the core recognition result, and the grayscale image segmentation threshold is defined; When the threshold reaches the effect of reservoir and non-reservoir areas in carbonate rocks circled by thin section observation, this threshold is used as the division standard for other sections; Count the area ratio of reservoir to non-reservoir in each section, and calculate the proportion of reservoir in each section A i , where: i = 1, 2, ..., n; and calculate the reservoir volume percentage m.

5. The method according to claim 4, characterized in that Defining the grayscale image segmentation threshold includes: Assuming that F(i, j) represents the gray value of the image pixel, the pixel with a gray value of 1 after separation represents the target object, and the pixel with a gray value of 0 represents the image background. The target object is obtained by the following formula: Among them, g(i, j) is the value of the target object; i, j are the pixel positions in the x and y directions respectively; M, N are the number of pixels of the image in the x and y directions respectively; T is the threshold.

6. The method according to claim 4, characterized in that The calculation formula of reservoir volume proportion m is: Among them, V c is the volume of the reservoir; V f is the total volume of the core sample; L is the length of the core sample; n is the number of cross sections scanned at equal distances in the horizontal direction; A i is the proportion of reservoir in each cross section.

7. The method according to claim 6, characterized in that Step S4 includes: The apparent volume of the core sample is: Among them, V f It represents the surface volume of the core sample, D represents the diameter of the core sample, and L represents the length of the core sample; The rock skeleton volume Vs is determined by the gas expansion method; The true porosity of the reservoir is: φ=V p / (V1+V p )×100=(V f -V s ) / (m·V f +(V f -V s ))×100, where φ represents the true porosity of the reservoir; V p represents the rock pore volume, V p =V f -Vs; V1 is the rock skeleton volume of the reservoir.

8. The method according to claim 7, characterized in that Step S5 includes: The permeability k is measured by gas measurement method g for: Wherein, p1 represents the inlet pressure; p2 represents the outlet pressure; p0 represents the atmospheric pressure; μ represents the gas viscosity; Q0 ​​represents the volume flow rate of the gas under the atmospheric pressure p0; A represents the cross-sectional area of ​​the core sample; L represents the length of the core sample; Assuming that the permeability of each reservoir is equal, the reservoir proportion of each cross section is A. i , and A i > 0, where: i = 1, 2, ..., n; the calculation formula for the true permeability k of the reservoir derived from the Darcy formula is:

9. The method according to claim 8, characterized in that Step S6 includes: According to the reservoir true porosity and reservoir true permeability, a two-dimensional plane map of the reservoir true porosity and reservoir true permeability is constructed. The regression relationship of the two-dimensional plane map is: k = ae b·φ ; Among them, a and b are constants obtained through formula regression of the two-dimensional plane plate.

10. The method according to claim 9, characterized in that Step S7 includes: The density logging characteristic parameters of the white oil-free reservoir section were extracted, and the calculation formula for the development ratio of effective reservoirs in the piebald carbonate rock was established as follows: Among them, x represents the development ratio of effective reservoirs in the piebald carbonate rock; RHOB represents the density logging value of the piebald reservoir development section; RHOB non-piebald represents the density logging value of the reservoir adjacent to the non-piebald reservoir development section; The total porosity is calculated based on the well logging curve. Based on the total porosity and the development ratio of effective reservoirs in the piebald carbonate rock, the true porosity of the reservoir in the piebald carbonate rock is calculated as follows: Φ 有效 =φ 总 / x, where Φ 有效 represents the real porosity of the effective reservoir in the piebald carbonate rock, φ 总 represents the total porosity; The true permeability logging interpretation model of the effective reservoir of the piebald carbonate rock is: Among them, k 有效 It represents the true permeability of the effective reservoir of the piebald carbonate rock.

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