Method for correcting grey matter influence of reservoir resistivity

Abstract

The invention provides a reservoir resistivity grey matter influence correction method, which comprises the following steps of: determining an influence threshold value of grey matter on resistivity by utilizing a rock core analysis grey matter content and resistivity intersection chart, and obtaining a continuous grey matter content and porosity curve; deducing a grey matter influence correction formula of the resistivity based on an Archie formula; respectively establishing calculation models of the grey matter influence correction factors of the resistivity of the water layer, the oil and / or gas water layer and the oil and / or gas layer; and distinguishing a water layer, an oil and / or gas water layer and an oil and / or gas layer to establish a resistivity grey matter influence correction model. The invention provides a resistivity grey matter influence correction method considering formation water resistivity and fluid properties.

Description

Technical Field

[0001] The invention belongs to the technical field of petroleum exploration, and in particular relates to a gray matter influence correction method for reservoir resistivity. Background Art

[0002] Ash-bearing (gray matter) reservoirs are widespread in my country. Ash matter exhibits "two highs and three lows" in conventional logging responses: high resistivity, high density, low acoustic transit time, low neutron intensity, and low natural gamma ray ray. When ash matter is present in a reservoir, resistivity logging values increase, creating the illusion of oil and gas. This can easily misidentify a water layer as containing oil (gas) and water, or vice versa. Therefore, ash matter correction is necessary to eliminate the influence of ash matter on reservoir resistivity and lay the foundation for subsequent saturation assessment. Currently, there are three main methods for correcting the gray matter effect on resistivity in limy sandstone reservoirs: First, using the relationship between deep lateral resistivity and gray matter content to determine the gray matter content threshold, and then using the intercept method to correct the resistivity by subtraction; second, taking the derivative of the functional relationship between gray matter content and resistivity for reservoirs with different fluid properties, calculating the average derivative, and then integrating it to establish a gray matter correction formula for resistivity; and third, using the functional relationship between gray matter content and the ratio of the resistivity of ash-bearing formations to the resistivity of ash-free formations to establish a gray matter correction formula for resistivity. None of these three methods analyzes the mechanism of gray matter's influence on resistivity; all are empirical formulas and do not consider the effects of formation water resistivity and water saturation.

[0003] Technical solution of prior art 1 The application number is CN201910760689.0, and the invention name is A method for calculating gas saturation in tight sandstone based on ash content correction, comprising: 1) obtaining the ash weight percentage of the tight sandstone reservoir based on well logging data and combining it with the formation element oxygen closure model; 2) using the tight sandstone multi-mineral rock skeleton model and obtaining the porosity of the tight sandstone reservoir based on the well logging data; 3) selecting a priori area in the tight sandstone reservoir, measuring the formation resistivity of the ash-containing section and the pure sandstone section in the priori area respectively, and fitting the priori area. The formation resistivity increase factor in the domain and the weight percentage of ash matter in the tight sandstone reservoir are used to obtain the corresponding relationship between the formation resistivity increase factor and the weight percentage of ash matter in the prior region, where the formation resistivity increase factor is the ratio of the formation resistivity of the ash-containing section to the formation resistivity of the pure sandstone section; 4) the formation resistivity increase factor is calculated based on the corresponding relationship between the formation resistivity increase factor and the weight percentage of ash matter, and the measured formation resistivity is corrected by the formation resistivity increase factor to obtain the corrected formation resistivity.

[0004] Disadvantages of the prior art 1 This technical solution has the following disadvantages: ①. This technical method does not analyze the mechanism of the influence of gray matter on resistivity and lacks theoretical support.

[0005] ②. This technical solution calculates the resistivity increase factor only by the resistivity ratio of the ash-containing section to the pure sandstone section, without considering the effects of porosity, formation water resistivity and fluid properties on resistivity.

[0006] Technical solution of existing technology 2 Research on gray matter correction method for resistivity of sandstone reservoir in A oil field (journal article), (Wang Min et al., 2009), records: 1) Using the acoustic time difference and microsphere focusing curve, a gray matter content calculation model was established by multivariate regression; 2) The intersection plot of gray matter content and resistivity was used to determine the threshold of the influence of gray matter on resistivity; 3) Different fluid properties were distinguished, and a linear relationship between resistivity value and gray matter content was established. Analysis showed that the fitting relationship between oil layer, water layer and oil-water layer was not much different; 4) The data points of oil layer, water layer and oil-water layer were fitted together to establish a linear relationship between resistivity and gray matter content; 5) The intercept method was used to determine the influence of gray matter on resistivity, and on this basis, the subtraction method was used to derive the resistivity gray matter influence correction formula.

[0007] Disadvantages of the second prior art: ①. This technical method takes into account the influence of fluid properties on resistivity, but does not consider the influence of formation water resistivity on formation resistivity.

[0008] ②. This technical method uses deep resistivity minus the resistivity increase to obtain the corrected resistivity, but lacks analysis of the mechanism of influence of gray matter on resistivity.

[0009] ③. This technical method unifies the resistivity correction formulas of oil layer, oil-water layer and water layer into one formula, which has certain errors.

[0010] Technical solution of existing technology three Research on the identification method of fluid in calcium-containing reservoirs (journal article), (Yang Xiaolei, 2017), records: 1) The influence of gray matter content on resistivity is analyzed by using the intersection plot of gray matter content and resistivity; 2) The gray matter content calculation model is established by using the acoustic time difference and deep resistivity curve and multiple regression; 3) Different fluid properties are distinguished and the resistivity change per unit gray matter content is calculated by the derivative method; 4) The derivatives of different fluid properties are approximately unified into an influencing formula by using the logarithmic average method; 5) The formula for resistivity affected by gray matter is integrated, and resistivity correction is performed by connecting gray matter in series with the reservoir.

[0011] Disadvantages of the existing technology three: ①. This technical method takes into account the influence of ash matter on resistivity under different fluid properties, but does not consider the influence of formation water resistivity on formation resistivity.

[0012] ②. This technical method uses the method of derivation and integration to remove the influence of gray matter on resistivity in the form of subtraction, but lacks analysis of the mechanism of the influence of gray matter on resistivity.

[0013] ③. This technical method unifies the resistivity correction formulas of oil layer, oil-water layer and water layer into one formula, which has certain errors.

[0014] Technical solution of existing technology 4 Application number CN201810705876.4, invention name: A resistivity curve correction method for ash-bearing formations, describes: 1) studying the logging response characteristics of calcium-bearing reservoirs and selecting logging curves sensitive to ash content; 2) using thin section analysis test data to establish a ash content calculation model based on sonic time difference, deep lateral resistivity curves and core porosity that are more sensitive to the influence of ash; 3) introducing a logRT increase factor parameter to study the resistivity changes of ash-bearing reservoirs and ash-free reservoirs, and establishing a linear regression equation based on the logRT increase factor of ash content in core analysis.

[0015] Disadvantages of the prior art four: ①. This technical method uses the resistivity curve to calculate the ash content. However, the increase in resistivity is not necessarily due to the influence of ash. When the reservoir contains oil (gas), the resistivity will also increase, resulting in a certain error in the calculated ash content.

[0016] ②. This technical method does not consider the impact of fluid properties and formation water resistivity on formation resistivity. Summary of the Invention

[0017] The purpose of the present invention is to solve the defects of the above-mentioned prior art and provide a method for correcting the gray matter effect on reservoir resistivity.

[0018] (1) Ash-bearing (gray) reservoirs are sedimentary rocks composed primarily of quartz, clay, and ash cement. They are typically deposited in shallow marine or lake environments, where quartz sand is first transported by water or wind. Subsequent sedimentary materials such as calcium carbonate dissolve in the pore water and precipitate between the sand grains, forming ash cement. This ash cement is primarily composed of bioclastic skeletons and dispersed calcite particles.

[0019] (2) Gray matter effect correction of resistivity refers to eliminating the effect of gray matter on resistivity. On the one hand, gray matter cementation reduces the porosity of the rock formation, and on the other hand, it narrows the pore channel, complicates the pore structure, reduces the conductive cross section, and causes the resistivity logging response to show a significantly high value, making it difficult to distinguish whether it is the gray matter affected by oil and gas or gray matter cementation. The gray matter effect correction process of resistivity is generally to first calculate the gray matter content through statistical regression, then analyze the correlation between resistivity and gray matter content to obtain the resistivity increase under different gray matter contents, and finally, subtract or divide the resistivity increase caused by the gray matter effect from the deep lateral resistivity to eliminate the gray matter effect.

[0020] The present invention adopts the following technical solutions: A method for correcting gray matter effects on reservoir resistivity comprises the following steps: S1. Use the cross-plot of ash content and resistivity in core analysis to determine the threshold of the ash content's effect on resistivity and obtain a continuous ash content and porosity curve. S2. Derivation of gray matter effect correction formula for resistivity based on Archie's formula; S3. Calculation models for gray matter effect correction factors of resistivity of water layer, oil and / or gas-water layer, and oil and / or gas layer are established respectively; S4. Distinguish between water layers, oil and / or gas-water layers, and oil and / or gas layers and establish a resistivity gray matter effect correction model.

[0021] Furthermore, in step S1, the core data and conventional logging curve data are first combined to extract the resistivity curve value of the depth point corresponding to the gray matter content of the core analysis, and then the threshold R of the influence of the gray matter on the resistivity is determined through the intersection diagram of the gray matter content of the core analysis and the resistivity. That is, when the gray matter content is less than R, the influence of the gray matter on the resistivity is not obvious, and when the gray matter content is greater than or equal to R, the gray matter has a significant influence on the resistivity.

[0022] Secondly, a rock physics volume model consisting of pores, mud, and rock skeleton was established. Natural gamma, resistivity, acoustic transit time, compensated neutron, compensated density, and photoelectric absorption cross-section index curves were selected, and the ash content and porosity were solved by the optimization method of the simultaneous volume equations: (1); (2); (3); (4); Where, —Acoustic logging value, μs / ft; —Fluid acoustic logging value, ; ——porosity, decimal; —Mudstone acoustic wave value, μs / ft; —sonic skeleton value of mineral in item i, μs / ft; —Content of mineral type i, decimal; —neutron porosity, decimal; —fluid neutron value, decimal; —Neutron value of mudstone, decimal; —Skeleton neutron value of the i-th mineral, decimal; —Density logging value, g / cm 3 ; —Fluid density, g / cm 3 ; —Mudstone density, g / cm 3 ; —Skeleton density of the i-th mineral, g / cm 3 ; V sh —Mud content, decimal.

[0023] Furthermore, in step S2, according to Archie's formula, it is obtained that for any determined ash-bearing reservoir, the following relationship is satisfied: (5); (6); (7); Where, —cementation index of any ash-bearing reservoir, dimensionless; —Any stratigraphic factor of a limy reservoir, dimensionless; —porosity, decimal; —Resistivity of rock containing lime and 100% saturated with formation water, Ω.m; — formation water resistivity, Ω.m; —Resistivity logging value, Ω.m; —water saturation, decimal; —saturation index, dimensionless; Similarly, the corresponding reservoir without gray matter satisfies the following relationship: (8); (9); (10); Where, —cementation index corresponding to reservoir without ash matter, dimensionless; —The stratigraphic factor corresponding to the reservoir without gray matter, dimensionless; —porosity, decimal; —Resistivity of rock corresponding to 100% saturation of formation water without ash, Ω.m; — formation water resistivity, Ω.m; —Resistivity after correction of gray matter effect, Ω.m; —water saturation, decimal; —saturation index, dimensionless; The gray matter effect correction factor of resistivity is defined in the form of formula (11): : (11); Where, —cementation index of any ash-bearing reservoir, dimensionless; —cementation index corresponding to reservoir without ash matter, dimensionless; Substituting equations (5), (6), (8), and (9) into equation (7) yields the following relationship: (12); Where, —Resistivity of rock corresponding to 100% saturation of formation water without ash, Ω.m; — formation water resistivity, Ω.m; —Resistivity of rock containing lime and 100% saturated with formation water, Ω.m; — formation water resistivity, Ω.m; —Correction factor for gray matter effect on resistivity, dimensionless; According to equations (7), (9), and (12), we can obtain the following relationship: (13); Where, —Resistivity after correction of gray matter effect, Ω.m; — formation water resistivity, Ω.m; —Resistivity logging value, Ω.m; —water saturation, decimal; —saturation index, dimensionless; —gray matter effect correction factor for resistivity, dimensionless; In formula (13), the gray matter effect correction factor of resistivity is affected by both the gray matter content and the fluid properties. Therefore, it is necessary to distinguish between oil and / or gas layers, oil and / or gas-water layers, and water layers. In a reservoir with certain fluid properties, formula (13) becomes: (14); Where, —Resistivity after correction of gray matter effect, Ω.m; — formation water resistivity, Ω.m; —Resistivity logging value, Ω.m; —Dimensionless correction factor for the gray matter effect on the resistivity of a reservoir with a certain fluid property.

[0024] Furthermore, in step S3, the porosity and ash content obtained in step S1 are applied, with deep resistivity as the ordinate, porosity as the abscissa, and ash content as the color scale. First, data points of the water layer are selected to establish resistivity-porosity cross-plots with and without ash, respectively; Select a data point a without ash at the bottom envelope of the plate with ash content equal to 0, read the porosity and deep resistivity value of point a, at this time the deep resistivity value of point a is considered to be the resistivity without ash at this porosity, then select data points b, c, d with different ash contents at the same porosity on the plate with ash content greater than 0, and read their deep resistivity and ash content values, at this time the deep resistivity of points b, c, d is considered to be the resistivity value of point a with different ash contents, then the ash influence correction factor of the resistivity with different ash contents is obtained according to formula (14): Repeat the above steps to obtain the resistivity correction factor of the water layer Relationship with gray matter content: ; Where, —Correction factor for gray matter effect on resistivity under water layer conditions, dimensionless; —Gray matter content, decimal; 、 —Undetermined coefficient, dimensionless.

[0025] Secondly, the data points of the oil and / or gas-water layer are selected in the same way to obtain the resistivity-porosity cross-plot of the oil and / or gas-water layer with and without ash, and further obtain the resistivity correction factor of the oil and / or gas-water layer. Relationship with gray matter content: ; Where, —Correction factor for gray matter effect on resistivity under oil and / or gas-water conditions, dimensionless; —Gray matter content, decimal; 、 —Undetermined coefficient, dimensionless.

[0026] Finally, the data points of the oil and / or gas layer are selected in the same way to obtain the resistivity-porosity cross-plot of the oil and / or gas layer with and without ash, and further obtain the resistivity correction factor of the oil and / or gas layer. Relationship with gray matter content: ; Where, —Correction factor for gray matter effect on resistivity under oil and / or gas conditions, dimensionless; —Gray matter content, decimal; 、 —Undetermined coefficient, dimensionless.

[0027] Furthermore, in step S4, based on the resistivity gray matter effect correction formula (14) obtained in S2 and the relationship between the correction factor K and the gray matter content of the oil and / or gas layer, the oil and / or gas-water layer and the water layer obtained in S3, a resistivity gray matter effect correction model is established: Water layer: (18); Oil and / or gas-water layers: (19); Oil and / or gas reservoirs: (20); Where, —Resistivity after correction of gray matter effect, Ω.m; ——formation water resistivity, Ω.m; —Resistivity logging value, Ω.m; —gray matter content, decimal; —Undetermined coefficient, dimensionless.

[0028] Beneficial effects of the present invention: The present invention derives a gray matter effect correction formula for resistivity based on the mechanism of gray matter effect on resistivity. The formula is not an empirical formula but is universal and can be widely used.

[0029] The present invention establishes a gray matter effect correction model for resistivity that takes into account fluid properties and formation water resistivity. It can reasonably correct the gray matter effect on resistivity, so that the resistivity curve can more realistically reflect the oil (gas) content of the reservoir, and provide technical support for the subsequent saturation evaluation of gray (gray matter) reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a cross-plot of the resistivity and ash content of the core analysis of the present invention; Figure 2 is the water layer resistivity correction factor Cross-plot with gray matter content; Figure 3 is the resistivity correction factor of oil (gas) and water layers Cross-plot with gray matter content; Figure 4 is the oil (gas) layer resistivity correction factor Cross-plot with gray matter content; Figure 5 This is the gray matter effect correction result of resistivity of Well A; Figure 6 It is a flow chart of the steps of the present invention. DETAILED DESCRIPTION

[0031] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0032] like Figure 6 As shown, a gray matter effect correction method for reservoir resistivity of the present invention includes the following steps: S1. Use the cross-plot of ash content and resistivity in core analysis to determine the threshold of the ash content's effect on resistivity and obtain a continuous ash content and porosity curve. S2. Derive the gray matter effect correction formula for resistivity based on Archie's formula; S3. Calculation models for gray matter effect correction factors of resistivity of water layer, oil and / or gas-water layer, and oil and / or gas layer are established respectively; S4. Distinguish water layers, oil and / or gas-water layers, and oil and / or gas layers and establish a gray matter effect correction model for resistivity.

[0033] Furthermore, in S1, the core data and conventional logging curve data are first combined to extract the resistivity curve value of the depth point corresponding to the ash content of the core analysis. Then, the threshold value R of the influence of ash content on resistivity is determined by the intersection diagram of ash content and resistivity of the core analysis. It is 5%, that is, when the ash content is less than 5%, the influence of ash on resistivity is not obvious. When the ash content is ≥5%, the ash has a significant influence on resistivity, such as Figure 1 shown.

[0034] Secondly, a rock physics volume model consisting of pores, mud, and rock skeleton was established. Natural gamma, resistivity, acoustic transit time, compensated neutron, compensated density, and photoelectric absorption cross-section index curves were selected, and the ash content and porosity were solved by the optimization method of the simultaneous volume equations: (1); (2); (3); (4); Where, —Acoustic logging value, μs / ft; —Fluid acoustic logging value, ; ——porosity, decimal; —Mudstone acoustic wave value, μs / ft; —sonic skeleton value of mineral in item i, μs / ft; —Content of mineral type i, decimal; —neutron porosity, decimal; —fluid neutron value, decimal; —Neutron value of mudstone, decimal; —Skeleton neutron value of the i-th mineral, decimal; —Density logging value, g / cm 3 ; —Fluid density, g / cm 3 ; —Mudstone density, g / cm3 ; —Skeleton density of the i-th mineral, g / cm 3 ; V sh —Mud content, decimal.

[0035] Furthermore, in S2, according to Archie's formula, it can be obtained that for any determined ash-bearing reservoir, the following relationship is satisfied: (5); (6); (7); Where, —cementation index of any ash-bearing reservoir, dimensionless; —Any stratigraphic factor of a limy reservoir, dimensionless; —porosity, V / V; —Resistivity of rock containing lime and 100% saturated with formation water, Ω.m; — formation water resistivity, Ω.m; —Resistivity logging value, Ω.m; —water saturation, V / V; —Saturation index, dimensionless.

[0036] Similarly, the corresponding reservoir without gray matter satisfies the following relationship: (8); (9); (10); Where, —cementation index corresponding to reservoir without ash matter, dimensionless; —The stratigraphic factor corresponding to the reservoir without gray matter, dimensionless; —porosity, decimal; —Resistivity of rock corresponding to 100% saturation of formation water without ash, Ω.m; — formation water resistivity, Ω.m; —Resistivity after correction of gray matter effect, Ω.m; —water saturation, decimal; —Saturation index, dimensionless.

[0037] The gray matter effect correction factor of resistivity is defined in the form of formula (11): : (11); Where, —cementation index of any ash-bearing reservoir, dimensionless; —Cementation index corresponding to reservoir without ash matter, dimensionless.

[0038] Substituting equations (5), (6), (8), and (9) into equation (12), we can obtain the following relationship: (12); Where, —Resistivity of rock corresponding to 100% saturation of formation water without ash, Ω.m; — formation water resistivity, Ω.m; —Resistivity of rock containing lime and 100% saturated with formation water, Ω.m; — formation water resistivity, Ω.m; —Correction factor for gray matter effect on resistivity, dimensionless.

[0039] According to equations (7), (9), and (12), the following relationship can be obtained: (13); Where, —Resistivity after correction of gray matter effect, Ω.m; — formation water resistivity, Ω.m; —Resistivity logging value, Ω.m; —water saturation, decimal; —saturation index, dimensionless; —Correction factor for gray matter effect on resistivity, dimensionless.

[0040] In formula (13), the gray matter effect correction factor of resistivity is affected by both the gray matter content and the fluid properties. Therefore, it is necessary to distinguish between oil and / or gas layers, oil and / or gas-water layers, and water layers. In a reservoir with certain fluid properties, formula (13) becomes: (14); Where, —Resistivity after correction of gray matter effect, Ω.m; — formation water resistivity, Ω.m; —Resistivity logging value, Ω.m; —Dimensionless correction factor for the gray matter effect on the resistivity of a reservoir with a certain fluid property.

[0041] Furthermore, in step S3, based on the porosity and ash content obtained in S1, with deep resistivity as the ordinate, porosity as the abscissa, and ash content as the color scale, firstly select the data points of the water layer, and establish the resistivity-porosity cross-plots with and without ash, respectively.

[0042] Select a data point a without ash at the bottom envelope of the plate with ash content equal to 0, read the porosity and deep resistivity value of point a, at this time the deep resistivity value of point a can be considered as the resistivity without ash when the porosity is 0.08, then select data points b, c, d with different ash contents at the same porosity on the plate with ash content greater than 0, and read their deep resistivity and ash content values, at this time the deep resistivity of points b, c, d can be considered as the resistivity value of point a when it contains different ash contents, and then according to formula (10) the ash influence correction factor of the resistivity with different ash contents can be obtained Repeat the above steps to get the correction factor of the water layer. Relationship with gray matter content, such as Figure 2 Similarly, by selecting the data points of the oil (gas) water layer and the oil (gas) layer, the corresponding resistivity-porosity cross-plots can be obtained, and then the correction factors of the oil (gas) water layer and the oil (gas) layer can be obtained. Relationship with gray matter content, such as Figure 3-Figure 4 shown.

[0043] Finally, according to formula (14), the gray matter effect correction formula for the resistivity of water layer, oil-water layer, and oil layer can be obtained: Water layer: (15); Oil (gas) and water layers: (16); Oil (gas) layer: (17); Where, —Resistivity after correction of gray matter effect, Ω.m; ——formation water resistivity, Ω.m; —Resistivity logging value, Ω.m; —Gray matter content, decimal; It can be seen from the above formula that when the ash content is 0, the resistivity after correcting the influence of ash is equal to the formation resistivity value, that is, the resistivity does not change, indicating that the model is accurate.

[0044] Application examples: The above resistivity gray matter effect correction model is applied to Well A to correct the resistivity gray matter effect. Well A is a core well with heavy gray matter. The effect of gray matter on resistivity makes subsequent water saturation evaluation difficult. Therefore, it is necessary to correct the resistivity gray matter effect of Well A. The corresponding resistivity gray matter effect correction formula is applied to the oil layer, oil-water layer and water layer of Well A respectively. The resistivity correction results are as follows: Figure 5 As shown in the figure, the ash content calculated by the optimization model is in good agreement with the ash content from the lithologic analysis. The resistivity after ash lithologic correction decreases significantly in areas with higher ash content, and the results are relatively reasonable.

[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. 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. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A gray matter effect correction method for reservoir resistivity, characterized in that: The following steps are involved: S1. Use the cross-plot of ash content and resistivity in core analysis to determine the threshold of the ash content's effect on resistivity and obtain a continuous ash content and porosity curve. S2. Derivation of gray matter effect correction formula for resistivity based on Archie's formula; S3. Calculation models for gray matter effect correction factors of resistivity of water layer, oil and / or gas-water layer, and oil and / or gas layer are established respectively; S4. Distinguish between water layers, oil and / or gas-water layers, and oil and / or gas layers and establish a resistivity gray matter effect correction model.

2. The method according to claim 1, characterized in that In step S1, the core data and conventional logging curve data are first combined to extract the resistivity curve value of the depth point corresponding to the gray matter content of the core analysis. Then, the threshold value R of the influence of gray matter on resistivity is determined through the intersection diagram of gray matter content and resistivity of the core analysis. That is, when the gray matter content is less than R, the influence of gray matter on resistivity is not obvious. When the gray matter content is greater than or equal to R, the gray matter has a significant influence on resistivity. Secondly, a rock physics volume model consisting of pores, mud, and rock skeleton was established. Natural gamma, resistivity, acoustic transit time, compensated neutron, compensated density, and photoelectric absorption cross-section index curves were selected, and the ash content and porosity were solved by the optimization method of the simultaneous volume equations: (1); (2); (3); (4); Where, —Acoustic logging value, μs / ft; —Fluid acoustic logging value, ; ——porosity, decimal; —Mudstone acoustic wave value, μs / ft; —sonic skeleton value of mineral in item i, μs / ft; —Content of mineral type i, decimal; —neutron porosity, decimal; —fluid neutron value, decimal; —Neutron value of mudstone, decimal; —Skeleton neutron value of the i-th mineral, decimal; —Density logging value, g / cm 3 ; —Fluid density, g / cm 3 ; —Mudstone density, g / cm 3 ; —Skeleton density of the i-th mineral, g / cm 3 ; V sh —Mud content, decimal.

3. The method according to claim 1, characterized in that In step S2, based on Archie's formula, it is obtained that for any determined ash-bearing reservoir, the following relationship is satisfied: (5); (6); (7); Where, —cementation index of any ash-bearing reservoir, dimensionless; —Any stratigraphic factor of a limy reservoir, dimensionless; —porosity, decimal; —Resistivity of rock containing lime and 100% saturated with formation water, Ω.m; — formation water resistivity, Ω.m; —Resistivity logging value, Ω.m; —water saturation, decimal; —saturation index, dimensionless; Similarly, the corresponding reservoir without gray matter satisfies the following relationship: (8); (9); (10); Where, —cementation index corresponding to reservoir without ash matter, dimensionless; —The stratigraphic factor corresponding to the reservoir without gray matter, dimensionless; —porosity, decimal; —Resistivity of rock corresponding to 100% saturation of formation water without ash, Ω.m; — formation water resistivity, Ω.m; —Resistivity after correction of gray matter effect, Ω.m; —water saturation, decimal; —saturation index, dimensionless; The gray matter effect correction factor of resistivity is defined in the form of formula (11): : (11); Where, —cementation index of any ash-bearing reservoir, dimensionless; —cementation index corresponding to reservoir without ash matter, dimensionless; Substituting equations (5), (6), (8), and (9) into equation (11), we obtain the following relationship: (12); Where, —Resistivity of rock corresponding to 100% saturation of formation water without ash, Ω.m; — formation water resistivity, Ω.m; —Resistivity of rock containing lime and 100% saturated with formation water, Ω.m; — formation water resistivity, Ω.m; —gray matter effect correction factor for resistivity, dimensionless; According to equations (7), (10), and (12), we can obtain the following relationship: (13); Where, —Resistivity after correction of gray matter effect, Ω.m; — formation water resistivity, Ω.m; —Resistivity logging value, Ω.m; —water saturation, decimal; —saturation index, dimensionless; —gray matter effect correction factor for resistivity, dimensionless; In formula (13), the gray matter effect correction factor of resistivity is affected by both the gray matter content and the fluid properties. Therefore, it is necessary to distinguish between oil and / or gas layers, oil and / or gas-water layers, and water layers. In a reservoir with certain fluid properties, formula (13) becomes: (14); Where, —Resistivity after correction of gray matter effect, Ω.m; — formation water resistivity, Ω.m; —Resistivity logging value, Ω.m; —Dimensionless correction factor for the gray matter effect on the resistivity of a reservoir with a certain fluid property.

4. The method according to claim 3, characterized in that In step S3, the porosity and ash content obtained in step S1 are applied, with deep resistivity as the ordinate, porosity as the abscissa, and ash content as the color scale. First, data points of the water layer are selected to establish resistivity-porosity cross-plots with and without ash, respectively. A data point a without ash is selected at the bottom envelope of the plate with ash content equal to 0, and the porosity and deep resistivity values of point a are read. At this time, the deep resistivity value of point a is considered to be the resistivity without ash at this porosity. Data points b, c, and d with different ash contents are selected at the same porosity on the plate with ash content greater than 0, and their deep resistivity and ash content values are read. At this time, the deep resistivities of points b, c, and d are considered to be the resistivity values of point a when it contains different ash contents. Then, according to formula (10), the ash influence correction factor of the resistivity with different ash contents is obtained: Repeat the above steps to obtain the resistivity correction factor of the water layer Relationship with gray matter content: ; Where, —Correction factor for gray matter effect on resistivity under water layer conditions, dimensionless; —Gray matter content, decimal; 、 —Undetermined coefficient, dimensionless; Secondly, the data points of the oil and / or gas-water layer are selected in the same way to obtain the resistivity-porosity cross-plot of the oil and / or gas-water layer with and without ash, and the resistivity correction factor of the oil and / or gas-water layer is obtained. Relationship with gray matter content: ; Where, —Correction factor for gray matter effect on resistivity under oil and / or gas-water conditions, dimensionless; —Gray matter content, decimal; 、 —Undetermined coefficient, dimensionless; Finally, the data points of the oil and / or gas layer are selected in the same way to obtain the resistivity-porosity cross-plot of the oil and / or gas layer with and without ash, and the resistivity correction factor of the oil and / or gas layer is obtained. Relationship with gray matter content: ; Where, —Correction factor for gray matter effect on resistivity under oil and / or gas conditions, dimensionless; —Gray matter content, decimal; 、 —Undetermined coefficient, dimensionless.

5. The method according to claim 4, characterized in that In step S4, based on the resistivity gray matter effect correction formula (14) obtained in step S2 and the relationship between the resistivity correction factor K and the gray matter content of the oil and / or gas layer, the oil and / or gas-water layer and the water layer obtained in step S3, a gray matter effect correction model for resistivity is established: Water layer: (18) Oil and / or gas-water layers: (19) Oil and / or gas reservoirs: (20) Where, —Resistivity after correction of gray matter effect, Ω.m; ——formation water resistivity, Ω.m; —Resistivity logging value, Ω.m; —gray matter content, decimal; —Undetermined coefficient, dimensionless.

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