Interpretation method of true permeability of reservoirs in piebald carbonate rocks

Abstract

The present invention relates to a method for interpreting the true permeability of reservoirs in piebald carbonate rocks. The method comprises: establishing a color standard for dense portions of a piebald carbonate rock core; identifying a core sample that meets the color standard; scanning a cross section of the core sample, calibrating the scan result based on the core sample identification result, and calculating the reservoir fraction and reservoir volume fraction of each cross section of the core sample; measuring the surface volume and rock skeleton volume of the core sample, and correcting the true reservoir porosity of the core sample based on the reservoir volume fraction; measuring the permeability of the core sample, and correcting the true reservoir permeability of the core sample based on the reservoir fraction; constructing a true reservoir porosity and true reservoir permeability chart; calculating the total porosity of the reservoir in the piebald carbonate rock based on a well logging curve; and constructing a true permeability interpretation model for the reservoir in the piebald carbonate rock based on the chart. This method fills a gap in well logging interpretation of porosity and permeability in piebald carbonate reservoirs.

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 formations are extremely heterogeneous, with considerable areas exhibiting a distinctive "mottled" heterogeneity. "Mottled" is a name derived from the morphological characteristics of the rock structure. Mottled carbonate rocks typically exhibit patches of white, dark gray, and other colors. Core sample testing and analysis of mottled carbonate formations often reveal complex porosity-permeability relationships, and the microscopic pore structure of mottled carbonate rocks is often multimodal. Marine mottled carbonate formations have similar surface characteristics but differ greatly in their geological and production characteristics: some marine mottled carbonate formations appear as poor reservoirs with low productivity in both well logging and production; some marine mottled carbonate formations appear as tight reservoirs or non-reservoirs in well logging, but highly productive in production.

[0003] Thin-section microscopy reveals that the development of piebald carbonates is not controlled by lithology, with white and dark gray patches occurring across all lithologies. Microscopic observation of the pore structure reveals that in the white patches, intergranular pores are absent or isolated, cemented by sparry calcite. In the dark patches, cementation is weak, with sparry calcite and intergranular pores. The dark patches in the piebald carbonate formation represent reservoirs, occurring between white, nodular patches that are not reservoirs. Thin-section microscopy reveals that the reservoirs in these dark patches are typically 1-2 cm wide. However, the cylindrical core samples used for laboratory porosity and permeability measurements are typically 2.5 cm or 3.8 cm in diameter, which is larger than the dark patches. Reservoir core samples extracted from the core samples include both reservoir (dark patches) and non-reservoir (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 the porosity and permeability measured in the laboratory not reflecting the true porosity and permeability of the reservoir (dark patches) in the mottled carbonate formation.

[0004] Furthermore, well logging interpretation of porosity and permeability is a crucial component of reservoir characterization. The number of coring wells and the extent of field coverage are far less than those of non-coring wells, and nearly all wells have logs. A more objective three-dimensional characterization of the entire reservoir often requires core calibration and logging, followed by calculation of porosity and permeability using log interpretation. Well logging of sections with piebald carbonate formations reflects the combined electrical characteristics of both the reservoir (dark patches) and non-reservoir (white patches). Current logging interpretation techniques and methods are unable to 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 response to the above problems, the present invention adopts the following technical solution: a method for interpreting the true permeability of a reservoir in a piebald carbonate rock, the method comprising the following steps:

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

[0007] S2. Identify core samples that meet the color standard;

[0008] S3. Scan the cross section of the core sample, calibrate the scan result according to the core sample identification result, and calculate the reservoir proportion and reservoir volume proportion of each cross section of the core sample;

[0009] S4. Determine the total volume and rock skeleton volume of the core sample, and correct the true reservoir porosity of the core sample based on the reservoir volume ratio;

[0010] S5. Measure the permeability of the core sample and correct the true reservoir permeability of the core sample based on 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 chart.

[0013] Furthermore, step S1 includes: selecting core samples including a white oil-free reservoir and a brown oil-bearing reservoir to prepare a casting thin section, and observing the casting thin section 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] Furthermore, 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] Furthermore, 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] Calibrate the scanned grayscale image according to the core recognition results and define the grayscale image segmentation threshold;

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

[0024] Count the area ratio of reservoir and 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 proportion m.

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

[0026] Assume that F(i, j) represents the gray value of the image pixel. After separation, the pixel with a gray value of 1 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 in the image in the x and y directions respectively; T is the threshold.

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

[0030] ;

[0031] in, is the volume of the reservoir; is the total volume of the core sample; is the length of the core sample; is the number of cross sections scanned at equal distances in the transverse direction; is the proportion of reservoir in each section.

[0032] Furthermore, step S4 includes:

[0033] The total volume of the core sample is: ,in, V f represents the total volume of the core sample, D Indicates the diameter of the core sample; L Indicates 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] , where φ represents the true porosity of the reservoir; V p represents the rock pore volume, ; V1 is the rock skeleton volume of the reservoir.

[0037] Furthermore, step S5 includes:

[0038] The permeability was measured by gas measurement method for: ,in, Indicates inlet pressure; Indicates outlet pressure; Indicates atmospheric pressure; Indicates gas viscosity; Indicates atmospheric pressure The volume flow rate of the gas below; Indicates the cross-sectional area of ​​the core sample; Indicates the length of the core sample;

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

[0040] Furthermore, 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: ; Among them, a and b are constants obtained through formula regression on the two-dimensional plane.

[0041] Furthermore, step S7 includes extracting density logging characteristic parameters of the white oil-free reservoir section and establishing a calculation formula for the effective reservoir development ratio in the piebald carbonate rock:

[0042] ,in, x It indicates the development ratio of effective reservoir in the piebald carbonate rock; Indicates the density logging value of the section where the piebald reservoir is developed; Density logging values ​​of reservoirs adjacent to the non-patchwork reservoir development section;

[0043] 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:

[0044] ,in, Indicates the true porosity of the effective reservoir in the piebald carbonate rock, represents the total porosity;

[0045] The true permeability logging interpretation model of the effective reservoir of the piebald carbonate rock is:

[0046] ,in, It represents the true permeability of the effective reservoir of the piebald carbonate rock.

[0047] Compared with the existing technology, the present invention has the following advantages: compared with the conventional laboratory methods for measuring rock porosity and permeability, this method fills the gap in the interpretation of porosity and permeability of piebald carbonate reservoirs through logging, and improves the accuracy of porosity and permeability interpretation, which specifically includes the following aspects:

[0048] (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 piebald carbonate rocks and calculate their area percentages;

[0049] (2) Using the distribution range of reservoirs (dark patches) and non-reservoir layers (white patches) delineated by core thin sections, the CT scan images were calibrated to determine the grayscale image segmentation thresholds of reservoirs (dark patches) and non-reservoir layers (white patches). Multiple CT scan cross-sectional images were combined to calculate the volume ratios of reservoirs (dark patches) and non-reservoir layers (white patches);

[0050] (3) Corrected the porosity and permeability values ​​of the reservoir (dark patches) in the mottled carbonate rock;

[0051] (4) This method can be widely used in the interpretation of porosity and permeability logging in variegated carbonate reservoirs.

[0052] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will 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

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to 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 any creative work.

[0054] Figure 1 A schematic diagram of a method for interpreting true permeability of reservoirs in piebald carbonate rocks;

[0055] Figure 2a 、 Figure 2b Schematic diagrams of the core sample sampling locations for the white patch reservoir and the oil-bearing brown reservoir, respectively;

[0056] Figure 3 Schematic diagram of thin section identification results of the distribution of rock structures in the piebald carbonate reservoir (dark patches) and non-reservoir (white patches);

[0057] Figure 4 Schematic diagram of the distribution of rock structures of mottled carbonate reservoirs (dark patches) and non-reservoir layers (white patches) in CT scan grayscale images;

[0058] Figure 5 Schematic diagram of the location selection and CT scanning method for core thin section samples;

[0059] Figure 6 Schematic diagram of the experimental device for testing the gas expansion method;

[0060] Figure 7a 、 Figure 7b The porosity-permeability relationship of rock porosity before and after correction was measured in the laboratory.

[0061] 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

[0062] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0063] 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:

[0064] S1. Construct a color standard for the dense part of the core of a piebald carbonate rock;

[0065] S2. Identify core samples that meet the color standard;

[0066] S3. Scan the cross section of the core sample, calibrate the scan result according to the core sample identification result, and calculate the reservoir proportion and reservoir volume proportion of each cross section of the core sample;

[0067] S4. Determine the total volume and rock skeleton volume of the core sample, and correct the true reservoir porosity of the core sample based on the reservoir volume ratio;

[0068] S5. Measure the permeability of the core sample and correct the true reservoir permeability of the core sample based on the reservoir proportion;

[0069] S6. Constructing a map of reservoir true porosity and reservoir true permeability;

[0070] 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 chart.

[0071] Specifically, in step S1, the core sample is selected from the piebald carbonate rock development section of the coring well (such as Figure 2a In the red frame), select the core sample including white patches and brown patches (such as Figure 2b As shown, Figure 2b Shown from Figure 2a The core was taken from the red frame in the middle) to make a casting thin section, and the casting thin section was observed under a microscope. Figure 3 As shown, Figure 3 It is from Figure 2b The thin slice made from the rock in the red box. Figure 3 It can be seen that the white patch part has no developed pores under the microscope, while the brown patch part has developed pores under the 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.

[0072] 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 an ineffective reservoir with no or very few connected pores.

[0073] 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 and reflects the intensity of the color. Pure white has zero saturation, while pure spectral colors have the highest saturation; 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 corresponding I, S, and H components of the HSI model can be calculated by the following formula:

[0074] ;

[0075] ;

[0076] ;

[0077] ;

[0078] 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 generated for the three components H, I, and S respectively, and its membership function can be specified as: ;in, There are three components: H, I, and S; In order to extract the expectation of the three components H, I, and S in color, the mean can be used instead in practical applications. is the variance of the sample. Secondly, determine the weights of the three components in the H, I, and S color space; in the H, I, and S color space, I changes from black at the bottom (0) to white at the top (1), 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 was 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:

[0079] , 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.

[0080] In step S3, the existing core micron CT scanning technology is used to perform CT scanning on the small cylindrical core sample, such as Figure 5 As shown in the figure, 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 a CT scan is shown. Darker colors (dark patches) indicate lower density, indicating a "mottled" carbonate reservoir. Brighter colors (white patches) indicate greater density and compactness, indicating a non-reservoir layer within the "mottled" carbonate. Thin-section observations were used to demarcate the first cross-sectional grayscale image of the CT scan, defining the reservoir (dark patches) and non-reservoir (white patches) areas within the "mottled" carbonate. This serves as the basis for determining the grayscale image segmentation threshold.

[0081] 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:

[0082] ;

[0083] Where g(i, j) is the value of the target object; i and j are the pixel positions in the x and y directions, respectively; M and N are the number of pixels in the image in the x and y directions, respectively; and T is the threshold. When the threshold is set to achieve the effect of "patterned" carbonate rock reservoir (dark patches) and non-reservoir (white patches) areas, the threshold is used as the demarcation standard for other sections. The area ratio of reservoir to non-reservoir areas in each section is calculated, and the reservoir (dark patches) proportion A of each section is calculated. i , where: i=1,2,...,n; calculate the volume proportion of the reservoir (dark patch) m, 0<m≤1, and the volume proportion of the non-reservoir (white patch) is 1-m. The calculation formula for the reservoir volume proportion m is:

[0084] ;

[0085] in, is the volume of the reservoir; is the total volume of the core sample; is the length of the core sample; is the number of cross sections scanned at equal distances in the transverse direction; is the proportion of reservoir in each section.

[0086] In step S4, the total volume of the core small cylindrical sample is: ,in, V f represents the total volume of the core sample, D Indicates the diameter of the core sample; 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, the volume of core chamber 1 is V, and the volume of the rock skeleton is Vs. After the core is placed, the remaining volume is V-Vs, and the pressure in core chamber 1 is P0. The volume of standard chamber 2 is △V, and the pressure in 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, air supply valve 7, pressure regulating valve 3, and gas source valve 4 are connected between standard chamber 2 and gas source 8. Opening sample valve 5 and simultaneously closing gas source valve 4, pressure regulating valve 3, air supply valve 7, and vent valve 6 causes the pressure in standard chamber 2 to expand toward core chamber 1, ultimately balancing to P1 (relative). Assuming this process is isothermal, Boyle's law yields: ; ;

[0087] The total volume of the small cylindrical sample obtained according to the above steps , rock skeleton volume Vs, reservoir (dark patch) volume ratio m, correct the porosity value, and calculate the true porosity of the reservoir:

[0088] , where φ represents the true porosity of the reservoir; V p represents the rock pore volume, ; V1 is the rock skeleton volume of the reservoir.

[0089] In step S5, according to GB / T 29172-2012 standard, domestic oil fields mainly use gas logging method to measure conventional core permeability 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. The calculation formula is: ,in, Indicates inlet pressure; Indicates outlet pressure; Indicates atmospheric pressure; Indicates gas viscosity; Indicates atmospheric pressure The volume flow rate of the gas below; Indicates the cross-sectional area of ​​the core sample; = represents the length of the core sample. Based on 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 true permeability of the reservoir (dark patches) is derived from the Darcy formula The calculation formula is: .

[0090] In step S6, the reservoir true porosity φ calculated in step S4 and the reservoir true permeability calculated in step S5 are calculated. , create a two-dimensional plane version, such as Figure 7b As shown, the regression equation for the two-dimensional plane graph is: ; where a and b are constants obtained by regression of the two-dimensional plane plate. Compare the plate obtained by fitting the porosity and permeability before correction (such as Figure 7a (shown as follows), the corrected reservoir true porosity φ and reservoir true permeability The fitting effect is better and the porosity-permeability relationship is significantly improved, laying the foundation for the subsequent reservoir permeability logging interpretation.

[0091] In step S7, the density logging characteristic parameters of the white oil-free reservoir section are extracted, and the known carbonate rock skeleton density (2.71 g / cm 3 ), the formula for calculating the development ratio of effective reservoirs in piebald carbonate rocks is established as: ,in, xIt indicates the development ratio of effective reservoir in the piebald carbonate rock; Indicates the density logging value of the section where the piebald reservoir is developed; The density logging value of the reservoir adjacent to the non-patterned reservoir development section is shown. The total porosity is calculated based on the logging curve. The total porosity calculation formula is: ,in, 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.

[0092] According to the total porosity and the development ratio of effective reservoirs in the piebald carbonate rocks, the true porosity of the reservoirs in the piebald carbonate rocks is calculated as: ,in, Indicates the true porosity of the effective reservoir in the piebald carbonate rock, represents the total porosity; the true permeability logging interpretation model of the effective reservoir of the piebald carbonate rock is: ,in, It represents the true permeability of the effective reservoir of the piebald carbonate rock.

[0093] In summary, the method proposed in this paper builds upon traditional laboratory measurements of rock porosity and permeability by incorporating cast thin section identification and CT scan image recognition and calculation. CT scan images are calibrated with cast thin sections to delineate the reservoir volume (m), representing the dark patch. By combining porosity and permeability obtained using conventional testing methods, correction formulas for laboratory-derived rock porosity and permeability in "mottled" carbonate reservoirs were established. Furthermore, improved laboratory porosity and permeability determination methods and well logging interpretation methods for "mottled" carbonate reservoirs were developed, providing more objective porosity and permeability values ​​for reservoir reserve calculations, laying the foundation for objectively evaluating the economic value of reservoirs and formulating development strategies.

[0094] 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 replacements for some of the technical features therein; and these modifications or replacements do not cause the essence of the corresponding technical solutions to 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 a reservoir in a piebald carbonate rock, characterized in that: The method comprises the following steps: S1. Construct a color standard for the dense part of the core of a piebald carbonate rock; S2. Identify core samples that meet the color standard; S3. Scan the cross section of the core sample, calibrate the scan result according to the core sample identification result, and calculate the reservoir proportion and reservoir volume proportion of each cross section of the core sample; S4. Determine the total volume and rock skeleton volume of the core sample, and correct the true reservoir porosity of the core sample based on the reservoir volume ratio; S5. Measure the permeability of the core sample and correct the true reservoir permeability of the core sample based on 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 chart.

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 make 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; Calibrate the scanned grayscale image according to the core recognition results and define the grayscale image segmentation threshold; When the threshold reaches the effect of the reservoir and non-reservoir areas in the carbonate rock circled by thin section observation, this threshold is used as the division standard for other sections; Count the area ratio of reservoir and 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 proportion m.

5. The method according to claim 4, characterized in that Defining the grayscale image segmentation threshold includes: Assume that F(i, j) represents the gray value of the image pixel. After separation, the pixel with a gray value of 1 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 in 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 for reservoir volume proportion m is: ； in, is the volume of the reservoir; is the total volume of the core sample; is the length of the core sample; is the number of cross sections scanned at equal distances in the transverse direction; is the proportion of reservoir in each section.

7. The method according to claim 6, characterized in that Step S4 includes: The total volume of the core sample is: ,in, V f represents the total volume of the core sample, D Indicates the diameter of the core sample; L Indicates 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: , where φ represents the true porosity of the reservoir; V p represents the rock pore volume, ; V1 is the rock skeleton volume of the reservoir.

8. The method according to claim 7, characterized in that Step S5 includes: Determination of permeability by gas measurement for: ,in, Indicates inlet pressure; Indicates outlet pressure; Indicates atmospheric pressure; Indicates gas viscosity; Indicates atmospheric pressure The volume flow rate of the gas below; Indicates the cross-sectional area of ​​the core sample; Indicates the length of the core sample; Assuming that the permeability of each reservoir is equal, the reservoir proportion of each section is A i , and A i >0, where: i=1,2,...,n; the true permeability of the reservoir is derived from the Darcy formula The calculation 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: ; Among them, a and b are constants obtained through formula regression on the two-dimensional plane.

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 effective reservoir development ratio in the piebald carbonate rock was established as follows: ,in, x It indicates the development ratio of effective reservoir in the piebald carbonate rock; Indicates the density logging value of the section where the piebald reservoir is developed; Density logging values ​​of reservoirs adjacent to the non-patchwork 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: ,in, Indicates the true porosity of the effective reservoir in the piebald carbonate rock, represents the total porosity; The true permeability logging interpretation model of the effective reservoir of the piebald carbonate rock is: ,in, It represents the true permeability of the effective reservoir of the piebald carbonate rock.

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