A method for correcting the influence of calcareous matter on reservoir resistivity

Abstract

The application provides a method for correcting the influence of lime on reservoir resistivity, which comprises the following steps: determining the influence threshold of lime on resistivity by using the crossplot of core analysis lime content and resistivity, and obtaining the continuous lime content and porosity curve; deducing the lime influence correction formula of resistivity based on the Archie formula; respectively establishing the calculation model of the lime influence correction factor of resistivity of water layer, oil and / or gas water layer and oil and / or gas layer; and establishing the resistivity lime influence correction model by distinguishing the water layer, oil and / or gas water layer and oil and / or gas layer. The application provides the resistivity lime influence correction method considering the resistivity of formation water and the properties of fluid.

Description

A method for correcting the influence of gray matter on reservoir resistivity Technical Field

[0001] This invention belongs to the field of petroleum exploration technology, and in particular relates to a method for correcting the influence of gray matter on reservoir resistivity. Background Technology

[0002] Ash-bearing (ash-bearing) reservoirs are widely distributed in my country. Ash-bearing reservoirs exhibit "two highs and three lows" characteristics in conventional logging responses: high resistivity, high density, low sonic transit time, low neutron count, and low natural gamma ray count. When a reservoir contains ash-bearing material, the resistivity logging value increases, creating the false impression of oil and gas presence. This can easily lead to misclassification of water layers as oil (gas)-water layers or vice versa. Therefore, it is necessary to correct for the influence of ash-bearing material on reservoir resistivity, eliminating its impact and laying the foundation for subsequent saturation assessment. Currently, there are three main methods for correcting the resistivity of calcareous sandstone reservoirs due to the influence of calcareous content: First, the relationship between deep lateral resistivity and calcareous content is used to determine the calcareous content threshold, and the intercept method is employed to correct the resistivity by subtraction. Second, the functional relationship between reservoir calcareous content and resistivity for different fluid properties is differentiated, the average derivative is calculated, and then integrated to establish a resistivity-calcareous content correction formula. Third, a resistivity-calcareous content correction formula is established using the functional relationship between calcareous content and the ratio of resistivity of calcareous formations to that of calcareous formations. None of these three methods analyze the mechanism of calcareous content's influence on resistivity; they are all empirical formulas and do not consider the influence of formation water resistivity and water saturation.

[0003] Technical solution of existing technology 1

[0004] Application number CN201910760689.0, invention title: A method for calculating gas saturation in tight sandstone based on ash content correction, comprising: 1) obtaining the ash weight percentage of tight sandstone reservoirs based on well logging data and a formation elemental oxygen closure model; 2) obtaining the porosity of tight sandstone reservoirs using a multi-mineral rock framework model of tight sandstone based on well logging data; 3) selecting a priori areas within the tight sandstone reservoir, measuring the formation resistivity of ash-bearing sections and pure sandstone sections within the priori areas respectively, and fitting the priori area... The formation resistivity increase factor and the weight percentage of ash in the tight sandstone reservoir within the region are used to obtain the correspondence between the formation resistivity increase factor and the weight percentage of ash in the tight sandstone reservoir in the prior area. Among them, the formation resistivity increase factor is the ratio of the formation resistivity of the ash-bearing section to the formation resistivity of the pure sandstone section. 4) The formation resistivity increase factor is calculated by the correspondence between the formation resistivity increase factor and the weight percentage of ash. The formation resistivity is corrected by correcting the measured formation resistivity with the formation resistivity increase factor.

[0005] Disadvantages of existing technology 1

[0006] The technical solution has the following drawbacks:

[0007] ①. This technical method does not analyze the mechanism of the influence of ash on resistivity and lacks theoretical support.

[0008] ②. The resistivity increase factor calculated by this technical solution is determined only by the resistivity ratio of the ash-bearing section to the pure sandstone section, without considering the influence of porosity, formation water resistivity and fluid properties on resistivity.

[0009] Technical solution of existing technology 2

[0010] A study on resistivity correction method for sandstone reservoirs in oilfield A (journal article), (Wang Min et al., 2009), records: 1) Using acoustic transit time and microsphere focusing curves, a multiple regression model for calculating ash content was established; 2) The threshold of ash content influence on resistivity was determined using the cross-plot of ash content and resistivity; 3) Differentiating different fluid properties, a linear relationship between resistivity and ash content was established, and the fitting relationship between oil layer, water layer, and oil-water layer was found to be similar; 4) The data points of oil layer, water layer, and oil-water layer were jointly fitted to establish a linear relationship between resistivity and ash content; 5) The influence of ash on resistivity was determined using the intercept method, and the ash content correction formula was derived by subtraction.

[0011] Disadvantages of existing technology 2:

[0012] ①. This technical method considers the influence of fluid properties on resistivity, but does not consider the influence of formation water resistivity on formation resistivity.

[0013] ②. This technique uses the deep resistivity minus the resistivity increase to obtain the corrected resistivity, but lacks an analysis of the mechanism by which gray matter affects resistivity.

[0014] ③. This technical method unifies the resistivity correction formulas for oil layers, oil-water layers, and water layers into a single formula, which introduces a certain degree of error.

[0015] Technical solution of existing technology three

[0016] Research on Fluid Identification Methods in Calcium-Bearing Reservoirs (Journal Article), (Yang Xiaolei, 2017), records: 1) Analyzing the influence of ash content on resistivity using a cross-plot of ash content and resistivity; 2) Establishing a ash content calculation model using multiple regression with acoustic transit time and deep resistivity curves; 3) Differentiating different fluid properties and calculating the resistivity change per unit ash content using differentiation; 4) Approximating and unifying the derivatives of different fluid properties into a single influence formula using logarithmic averaging; 5) Integrating the formula for resistivity influence by ash and performing resistivity correction by connecting ash and reservoir in series.

[0017] The disadvantages of existing technology three:

[0018] ①. This technical method considers the influence of ash on resistivity under different fluid properties, but does not consider the influence of formation water resistivity on formation resistivity.

[0019] ②. This technique uses differentiation and integration to remove the influence of ash on resistivity by subtraction, but lacks an analysis of the mechanism of the influence of ash on resistivity.

[0020] ③. This technical method unifies the resistivity correction formulas for oil layers, oil-water layers, and water layers into a single formula, which introduces a certain degree of error.

[0021] Technical solution of existing technology four

[0022] Application number CN201810705876.4, invention title: A method for correcting resistivity curves of ash-bearing strata, describes: 1) studying the logging response characteristics of calcium-bearing reservoirs and selecting logging curves sensitive to ash content; 2) establishing a model for determining ash content using thin-section analysis of experimental data on sonic transit time, deep lateral resistivity curves, and core porosity, which are relatively sensitive to the influence of ash; 3) introducing the logRT amplification factor parameter to study the resistivity changes of ash-bearing and ash-free reservoirs, and establishing a linear regression equation by analyzing the ash content logRT amplification factor through core analysis.

[0023] The disadvantages of existing technology four:

[0024] ①. This technical method uses resistivity curves to calculate ash content, but an increase in resistivity is not necessarily due to the influence of ash. When the reservoir contains oil (gas), the resistivity will also increase, which will cause a certain error in the calculated ash content.

[0025] ②. This technical method does not take into account the influence of fluid properties and formation water resistivity on formation resistivity. Summary of the Invention

[0026] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a method for correcting the influence of gray matter on reservoir resistivity.

[0027] (1) Ash (ash-bearing) reservoirs are sedimentary rocks mainly composed of quartz, clay, and ash cement. They are generally formed in shallow marine or lacustrine environments, where quartz sand is first transported and deposited by water currents or wind. Subsequently, substances such as calcium carbonate in the sediments dissolve in pore water and precipitate between sand grains, forming ash cement. This ash cement mainly consists of a bioclastic framework and dispersed calcite particles.

[0028] (2) Correction for the influence of ash on resistivity refers to eliminating the influence of ash on resistivity. Ash cementation reduces the porosity of rock formations and narrows pore channels, complicates pore structure, and reduces conductive cross-section. This results in significantly higher resistivity logging responses, making it difficult to distinguish whether the influence is from oil and gas or ash cementation. The process of correcting for the influence of ash on resistivity generally involves first calculating the ash content through statistical regression, then analyzing the correlation between resistivity and ash content to obtain the resistivity increase under different ash contents, and finally subtracting or dividing the resistivity increase due to ash influence from the deep lateral resistivity to eliminate the influence of ash.

[0029] The present invention adopts the following technical solution:

[0030] A method for correcting the influence of gray matter on reservoir resistivity includes the following steps:

[0031] S1. The threshold of the influence of ash content on resistivity was determined by using the cross plot of ash content and resistivity from core analysis, and continuous ash content and porosity curves were obtained.

[0032] S2. Derive the formula for correcting the gray matter effect of resistivity based on Archie's formula;

[0033] S3. Establish calculation models for the gray matter influence correction factor of resistivity in water layers, oil and / or gas-water layers, and oil and / or gas layers, respectively;

[0034] S4. Establish a resistivity gray matter influence correction model to distinguish between water layers, oil and / or gas-water layers, and oil and / or gas layers.

[0035] Furthermore, in step S1, firstly, by combining core data and conventional logging curve data, the resistivity curve value of the depth point corresponding to the ash content of the core analysis is extracted. Then, the threshold R of the influence of ash on resistivity is determined by the cross-plot of the ash content and resistivity of the core analysis. That is, when the ash content < R, the influence of ash on resistivity is not obvious, and when the ash content ≥ R, the ash has a significant influence on resistivity.

[0036] Secondly, a rock physical volume model consisting of pores, clay, and rock skeleton was established. Natural gamma, resistivity, acoustic transit time, compensated neutron, compensated density, and photoelectric absorption cross-section exponential curves were selected. The ash content and porosity were solved using a simultaneous volume equation optimization method. (1); (2); (3); (4);

[0037] In the formula, —Sonic logging value, μs / ft; — Fluid acoustic logging values ; —Porosity, decimal; —Mudstone acoustic wave value, μs / ft; — Acoustic skeleton value of the i-th mineral, μs / ft; —The content of the i-th mineral, as a decimal; — Neutron porosity, decimal; —Numerical value in fluid neutrons, decimal; —Neutron value in mudstone, decimal; —The skeletal neutron value of the i-th mineral, in decimal form; —Density logging value, g / cm³ 3 ; —Fluid density value, g / cm³ 3 ; —Density of mudstone, g / cm³ 3 ; —Skeleton density of the i-th mineral, g / cm³ 3 V sh —Mud content, decimal.

[0038] Furthermore, in step S2, according to Archie's formula, the following relationship is obtained for any given ash-bearing reservoir: (5); (6); (7);

[0039] In the formula, —The cementation index of any ash-bearing reservoir, dimensionless; —Structural factors of any ash-bearing reservoir, dimensionless; —Porosity, decimal; —Resistivity of rocks containing 100% saturated formation water and ash content, in Ω·m; — Formation water resistivity, Ω·m; —Resistivity logging value, Ω.m; —Water saturation, decimal; —Saturation index, dimensionless;

[0040] Similarly, the corresponding ash-free reservoirs satisfy the following relationship: (8); (9); (10);

[0041] In the formula, —The cementation index corresponding to reservoirs without ash, dimensionless; —Corresponds to formation factors without ash-rich reservoirs, dimensionless; —Porosity, decimal; —Resistivity of rock with 100% saturated formation water and no ash content, in Ω·m; — Formation water resistivity, Ω·m; —Resistivity after correction for the influence of gray matter, Ω.m; —Water saturation, decimal; —Saturation index, dimensionless;

[0042] The gray matter influence correction factor of resistivity is defined according to the form of equation (11). : (11);

[0043] In the formula, —The cementation index of any ash-bearing reservoir, dimensionless; —The cementation index corresponding to reservoirs without ash, dimensionless;

[0044] Substituting equations (5), (6), (8), and (9) into equation (7) yields the following relationship: (12);

[0045] In the formula, —Resistivity of rock with 100% saturated formation water and no ash content, in Ω·m; — Formation water resistivity, Ω·m; —Resistivity of rocks containing 100% saturated formation water and ash content, in Ω·m; — Formation water resistivity, Ω·m; —Resistivity gray matter influence correction factor, dimensionless;

[0046] Based on equations (7), (9), and (12), the following relationships are obtained: (13);

[0047] In the formula, —Resistivity after correction for the influence of gray matter, Ω.m; — Formation water resistivity, Ω·m; —Resistivity logging value, Ω.m; —Water saturation, decimal; —Saturation index, dimensionless; —A dimensionless correction factor for the gray matter effect of resistivity;

[0048] In equation (13), the gray matter influence correction factor of resistivity is affected by both gray matter content and fluid properties. Therefore, it is necessary to distinguish between oil and / or gas layers, oil and / or gas-water layers, and water layers. Within a reservoir with specific fluid properties, equation (13) becomes: Correction factor (14);

[0049] In the formula, —Resistivity after correction for the influence of gray matter, Ω.m; — Formation water resistivity, Ω·m; —Resistivity logging value, Ω.m; —A dimensionless correction factor for the influence of gray matter on the resistivity of a reservoir with a given fluid property.

[0050] Furthermore, in step S3, the porosity and ash content obtained in step S1 are used, with deep resistivity as the vertical axis, porosity as the horizontal axis, and ash content as the color scale. First, data points of the water layer are selected, and resistivity-porosity cross plots with and without ash are established respectively.

[0051] Select a data point 'a' without gray matter at the bottom envelope of the plate with a gray matter content of 0, and read the porosity and deep resistivity values ​​of point 'a'. The deep resistivity value of point 'a' is considered to be the resistivity without gray matter at that porosity. Then, select data points 'b', 'c', and 'd' with different gray matter contents at the same porosity on the plate with a gray matter content greater than 0, and read their deep resistivity and gray matter content values. The deep resistivity of points 'b', 'c', and 'd' is considered to be the resistivity value of point 'a' with different gray matter contents. Then, obtain the gray matter influence correction factor for resistivity with different gray matter contents according to equation (14). By repeatedly performing the above steps, the resistivity correction factor of the water layer can be obtained. Relationship with ash content: ;

[0052] In the formula, —A dimensionless correction factor for the influence of gray matter on resistivity under water layer conditions; — Ash content, decimal; , —Undetermined coefficients, dimensionless.

[0053] Secondly, data points for oil and / or gas-water layers were selected using the same method to obtain resistivity-porosity cross-plots of oil and / or gas-water layers with and without ash, and the resistivity correction factor for oil and / or gas-water layers was further obtained. Relationship with ash content: ;

[0054] In the formula, —A dimensionless correction factor for the gray matter effect of resistivity under oil and / or gas-water layer conditions; — Ash content, decimal; , —Undetermined coefficients, dimensionless.

[0055] Finally, data points for oil and / or gas layers were selected using the same method to obtain resistivity-porosity cross-plots of oil and / or gas layers with and without ash, and resistivity correction factors for oil and / or gas layers were further obtained. Relationship with ash content: ;

[0056] In the formula, —A dimensionless correction factor for the gray matter effect of resistivity under oil and / or gas layer conditions; — Ash content, decimal; , —Undetermined coefficients, dimensionless.

[0057] Furthermore, in step S4, based on the resistivity gray matter influence correction formula (14) obtained in S2 and the relationship between the correction factor K and gray matter content of oil and / or gas layers, oil and / or gas-water layers and water layers obtained in S3, a resistivity gray matter influence correction model is established:

[0058] Water layer: (18);

[0059] Oil and / or gas-water layer: (19);

[0060] Oil and / or gas layers: (20);

[0061] In the formula, —Resistivity after correction for the influence of gray matter, Ω.m; — Formation water resistivity, Ω·m; —Resistivity logging value, Ω.m; — Ash content, decimal; —Undetermined coefficients, dimensionless.

[0062] The beneficial effects of this invention are:

[0063] This invention derives a formula for correcting the influence of ash matter on resistivity based on the mechanism of the influence of ash matter on resistivity. This formula is not an empirical formula, but rather a universal one that can be widely used.

[0064] This invention establishes a gray matter influence correction model for resistivity that considers fluid properties and formation water resistivity. This model can reasonably correct the gray matter influence on resistivity, enabling the resistivity curve to more accurately reflect the oil (gas) content of the reservoir and providing technical support for subsequent saturation evaluation of gray (gray matter) reservoirs. Attached Figure Description

[0065] Figure 1 is a cross-plot of resistivity and ash content from core analysis according to the present invention.

[0066] Figure 2 shows the water layer resistivity correction factor. Cross-plot with gray matter content;

[0067] Figure 3 shows the oil (gas) water layer resistivity correction factor. Cross-plot with gray matter content;

[0068] Figure 4 shows the oil (gas) reservoir resistivity correction factor. Cross-plot with gray matter content;

[0069] Figure 5 shows the correction results for the influence of resistivity on gray matter in well A.

[0070] Figure 6 is a flowchart of the steps of the present invention. Detailed Implementation

[0071] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention are described clearly and completely below. Obviously, the described embodiments are only some embodiments of this invention, not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0072] As shown in Figure 6, a method for correcting the influence of gray matter on reservoir resistivity according to the present invention includes the following steps:

[0073] S1. The threshold of the influence of ash content on resistivity was determined by using the cross plot of ash content and resistivity from core analysis, and continuous ash content and porosity curves were obtained.

[0074] S2. Derive the formula for correcting the influence of resistivity gray matter based on Archie's formula;

[0075] S3. Establish calculation models for the gray matter influence correction factor of resistivity in water layers, oil and / or gas-water layers, and oil and / or gas layers, respectively;

[0076] S4. Establish a gray matter correction model for resistivity by distinguishing between water layers, oil and / or gas-water layers, and oil and / or gas layers.

[0077] Furthermore, in S1, firstly, by combining core data and conventional logging curve data, the resistivity curve values ​​of the depth points corresponding to the ash content of the core analysis are extracted. Then, the threshold R of the influence of ash content on resistivity is determined by the cross-plot of core analysis ash content and resistivity, which is 5%. That is, when the ash content is <5%, the influence of ash on resistivity is not obvious, and when the ash content is ≥5%, the ash has a significant influence on resistivity, as shown in Figure 1.

[0078] Secondly, a rock physical volume model consisting of pores, clay, and rock skeleton was established. Natural gamma, resistivity, acoustic transit time, compensated neutron, compensated density, and photoelectric absorption cross-section exponential curves were selected. The ash content and porosity were solved using a simultaneous volume equation optimization method. (1); (2); (3); (4);

[0079] In the formula, —Sonic logging value, μs / ft; — Fluid acoustic logging values ; —Porosity, decimal; —Mudstone acoustic wave value, μs / ft; — Acoustic skeleton value of the i-th mineral, μs / ft; —The content of the i-th mineral, as a decimal; — Neutron porosity, decimal; —Numerical value in fluid neutrons, decimal; —Neutron value in mudstone, decimal; —The skeletal neutron value of the i-th mineral, in decimal form; —Density logging value, g / cm³ 3 ; —Fluid density value, g / cm³ 3 ; —Density of mudstone, g / cm³ 3 ; —Skeleton density of the i-th mineral, g / cm³ 3 V sh —Mud content, decimal.

[0080] Furthermore, in S2, according to Archie's formula, the following relationship can be obtained for any given ash-bearing reservoir: (5); (6); (7);

[0081] In the formula, —The cementation index of any ash-bearing reservoir, dimensionless; —Structural factors of any ash-bearing reservoir, dimensionless; —Porosity, V / V; —Resistivity of rocks containing 100% saturated formation water and ash content, in Ω·m; — Formation water resistivity, Ω·m; —Resistivity logging value, Ω.m; —Water saturation, V / V; —Saturation index, dimensionless.

[0082] Similarly, the corresponding ash-free reservoirs satisfy the following relationship: (8); (9); (10);

[0083] In the formula, —The cementation index corresponding to reservoirs without ash, dimensionless; —Corresponds to formation factors without ash-rich reservoirs, dimensionless; —Porosity, decimal; —Resistivity of rock with 100% saturated formation water and no ash content, in Ω·m; — Formation water resistivity, Ω·m; —Resistivity after correction for the influence of gray matter, Ω.m; —Water saturation, decimal; —Saturation index, dimensionless.

[0084] The gray matter influence correction factor of resistivity is defined according to the form of equation (11). : (11);

[0085] In the formula, —The cementation index of any ash-bearing reservoir, dimensionless; —The cementation index corresponding to reservoirs without ash, dimensionless.

[0086] Substituting equations (5), (6), (8), and (9) into equation (12) yields the following relationship: (12);

[0087] In the formula, —Resistivity of rock with 100% saturated formation water and no ash content, in Ω·m; — Formation water resistivity, Ω·m; —Resistivity of rocks containing 100% saturated formation water and ash content, in Ω·m; — Formation water resistivity, Ω·m; —A dimensionless correction factor for the gray matter effect of resistivity.

[0088] Based on equations (7), (9), and (12), the following relationships can be obtained: (13);

[0089] In the formula, —Resistivity after correction for the influence of gray matter, Ω.m; — Formation water resistivity, Ω·m; —Resistivity logging value, Ω.m; —Water saturation, decimal; —Saturation index, dimensionless; —A dimensionless correction factor for the gray matter effect of resistivity.

[0090] In equation (13), the gray matter influence correction factor of resistivity is affected by both gray matter content and fluid properties. Therefore, it is necessary to distinguish between oil and / or gas layers, oil and / or gas-water layers, and water layers. Within a reservoir with specific fluid properties, equation (13) becomes: (14);

[0091] In the formula, —Resistivity after correction for the influence of gray matter, Ω.m; — Formation water resistivity, Ω·m; —Resistivity logging value, Ω.m; —A dimensionless correction factor for the influence of gray matter on the resistivity of a reservoir with a given fluid property.

[0092] Furthermore, in step S3, based on the porosity and ash content obtained in S1, with deep resistivity as the vertical axis, porosity as the horizontal axis, and ash content as the color scale, data points of the water layer are first selected to establish resistivity-porosity cross-plots for ash-containing and ash-free layers respectively.

[0093] Select a data point 'a' without gray matter at the bottom envelope of the plate with a gray matter content of 0, and read the porosity and deep resistivity values ​​of point 'a'. The deep resistivity value of point 'a' can be considered as the resistivity without gray matter when the porosity is 0.08. Then, select data points 'b', 'c', and 'd' with different gray matter contents at the same porosity on the plate with a gray matter content greater than 0, and read their deep resistivity and gray matter content values. The deep resistivity of points 'b', 'c', and 'd' can be considered as the resistivity values ​​of point 'a' with different gray matter contents. Then, according to equation (10), the gray matter influence correction factor for resistivity with different gray matter contents can be obtained. By repeating the above steps, the correction factor for the water layer can be obtained. The relationship with ash content is shown in Figure 2. Similarly, by selecting data points from the oil (gas) water layer and the oil (gas) layer, corresponding resistivity-porosity cross plots can be obtained, and thus the correction factors for the oil (gas) water layer and the oil (gas) layer can be obtained. The relationship with ash content is shown in Figures 3 and 4.

[0094] Finally, the correction formulas for the resistivity and gray matter effects of water layer, oil-water layer, and oil layer can be obtained according to equation (14):

[0095] Water layer: (15);

[0096] Oil (gas) water layer: (16);

[0097] Oil (gas) layer: (17);

[0098] In the formula, —Resistivity after correction for the influence of gray matter, Ω.m; — Formation water resistivity, Ω·m; —Resistivity logging value, Ω.m; — Ash content, decimal;

[0099] As can be seen from the above formula, when the ash content is 0, the resistivity after correcting for the influence of ash is equal to the formation resistivity value, that is, the resistivity has not changed, indicating that the model is accurate.

[0100] Application examples:

[0101] The resistivity-gray matter influence correction model described above was applied to correct the resistivity-gray matter influence on Well A. Well A is a core well with a high gray matter content. The influence of gray matter on resistivity makes subsequent water saturation evaluation difficult; therefore, resistivity-gray matter influence correction is necessary for Well A. The corresponding resistivity-gray matter influence correction formulas were applied to the oil layer, oil-water layer, and water layer of Well A. The resistivity correction results are shown in Figure 5. The gray matter content calculated using the optimization model agrees well with the gray matter content in the lithological analysis. The resistivity after gray matter-lithological correction shows a significant decrease in areas with high gray matter content, indicating that the results are reasonable.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions 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 correcting the influence of gray matter on reservoir resistivity, characterized in that, Includes the following steps: S1. Determine the threshold of the influence of ash on resistivity using the cross plot of ash content and resistivity from core analysis, and obtain continuous ash content and porosity curves; S2. Derive the ash influence correction formula for resistivity based on Archie's formula; S3. Establish calculation models for the ash influence correction factor of resistivity for water layers, oil and / or gas-water layers, and oil and / or gas layers, respectively. S4. Differentiate between water layers, oil and / or gas-water layers, and oil and / or gas layers, and establish a resistivity gray matter influence correction model; In step S4, based on the resistivity gray matter influence correction formula obtained in S2 and the relationship between the resistivity correction factor K and gray matter content of oil and / or gas layers, oil and / or gas-water layers, and water layers obtained in S3, establish a resistivity gray matter influence correction model: Water layer: (18) Oil and / or gas-water layer: (19) Oil and / or gas reservoirs: In equation (20), —Resistivity after correction for the influence of gray matter, Ω.m; — Formation water resistivity, Ω·m; —Resistivity logging value, Ω.m; — Ash content, decimal; —Undetermined coefficients, dimensionless.

2. The method according to claim 1, characterized in that, In step S1, firstly, by combining core data and conventional logging curve data, the resistivity curve value of the depth point corresponding to the ash content of the core analysis is extracted. Then, the threshold R of the influence of ash on resistivity is determined by the cross-plot of ash content and resistivity of the core analysis. That is, when the ash content < R, the influence of ash on resistivity is not obvious, and when the ash content ≥ R, the ash has a significant influence on resistivity. Secondly, a rock physical volume model consisting of pores, clay, and rock skeleton was established. Natural gamma, resistivity, acoustic transit time, compensated neutron, compensated density, and photoelectric absorption cross-section exponential curves were selected. The ash content and porosity were solved using a simultaneous volume equation optimization method. （1） （2） （3） (4) In the formula, —Sonic logging value, μs / ft; — Fluid acoustic logging values ； —Porosity, decimal; —Mudstone acoustic wave value, μs / ft; — Acoustic skeleton value of the i-th mineral, μs / ft; —The content of the i-th mineral, as a decimal; — Neutron porosity, decimal; —Numerical value in fluid neutrons, decimal; —Neutron value in mudstone, decimal; —The skeletal neutron value of the i-th mineral, in decimal form; —Density logging value, g / cm³ 3 ; —Fluid density value, g / cm³ 3 ; —Density of mudstone, g / cm³ 3 ; —Skeleton density of the i-th mineral, g / cm³ 3 V sh —Mud content, decimal.

3. The method according to claim 1, characterized in that, In step S2, based on Archie's formula, the following relationship is obtained for any given ash-bearing reservoir: （5） （6） In equation (7), —The cementation index of any ash-bearing reservoir, dimensionless; —Structural factors of any ash-bearing reservoir, dimensionless; —Porosity, decimal; —Resistivity of rocks containing 100% saturated formation water and ash content, in Ω·m; — Formation water resistivity, Ω·m; —Resistivity logging value, Ω.m; —Water saturation, decimal; —Saturation index, dimensionless; similarly, the corresponding ash-free reservoir satisfies the following relationship: （8） （9） In equation (10), —The cementation index corresponding to reservoirs without ash, dimensionless; —Corresponds to formation factors without ash-rich reservoirs, dimensionless; —Porosity, decimal; —Resistivity of rock with 100% saturated formation water and no ash content, in Ω·m; — Formation water resistivity, Ω·m; —Resistivity after correction for the influence of gray matter, Ω.m; —Water saturation, decimal; —Saturation index, dimensionless; The gray matter influence correction factor of resistivity is defined according to the form of equation (11). ： In formula (11), —The cementation index of any ash-bearing reservoir, dimensionless; —The cementation index corresponding to the ash-free reservoir is dimensionless; substituting equations (5), (6), (8), and (9) into equation (11) yields the following relationship: (12) Based on equations (7), (10), and (12), the following relationship is obtained: In equation (13), the gray matter influence correction factor of resistivity is affected by both gray matter content and fluid properties. Therefore, it is necessary to distinguish between oil and / or gas layers, oil and / or gas-water layers, and water layers. Within a reservoir with specific fluid properties, equation (13) becomes: In equation (14), —Resistivity after correction for the influence of gray matter, Ω.m; — Formation water resistivity, Ω·m; —Resistivity logging value, Ω.m; —A dimensionless correction factor for the influence of gray matter on the resistivity of a reservoir with a given fluid property.

4. The method according to claim 3, characterized in that, In step S3, using the porosity and ash content obtained in step S1, with deep resistivity as the vertical axis, porosity as the horizontal axis, and ash content as the color scale, data points of the water layer are first selected, and resistivity-porosity cross plots with and without ash are established respectively; at the bottom envelope of the plate where the ash content is equal to 0, a data point a without ash is selected, 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 under this porosity. At the same porosity on the plate where the ash content is greater than 0, data points b, c, and d with different ash contents are selected, and their deep resistivity and ash content values ​​are read. At this time, the deep resistivity of points b, c, and d is considered to be the resistivity value of point a when it contains different ash contents. Then, according to equation (11), the ash influence correction factor of resistivity with different ash contents is obtained. By repeatedly performing the above steps, the resistivity correction factor of the water layer can be obtained. Relationship with ash content: In the formula, —A dimensionless correction factor for the influence of gray matter on resistivity under water layer conditions; — Ash content, decimal; 、 —Undetermined coefficients, dimensionless; Secondly, data points for oil and / or gas-water layers were selected using the same method to obtain resistivity-porosity cross-plots of oil and / or gas-water layers with and without ash, and resistivity correction factors for oil and / or gas-water layers were obtained. Relationship with ash content: In the formula, —A dimensionless correction factor for the gray matter effect of resistivity under oil and / or gas-water layer conditions; — Ash content, decimal; 、 —Undetermined coefficients, dimensionless; Finally, data points for oil and / or gas layers are selected using the same method to obtain resistivity-porosity cross-plots of oil and / or gas layers with and without ash, and the resistivity correction factor for oil and / or gas layers is obtained. Relationship with ash content: In the formula, —A dimensionless correction factor for the gray matter effect of resistivity under oil and / or gas layer conditions; — Ash content, decimal; 、 —Undetermined coefficients, dimensionless.

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