A method for establishing a fluid distribution model for a carbonate gas reservoir

Abstract

The application discloses a method for establishing a fluid distribution model of a carbonate gas reservoir, and comprises the following steps: S1, obtaining reservoir classification indexes, phase permeability curves and capillary pressure curves of each core sample according to experimental data; S2, analyzing the reservoir classification indexes of the core sample, establishing a reservoir classification standard, and classifying the core sample; S3, classifying and normalizing the phase permeability curves and classifying and normalizing the capillary pressure curves by using a J function; S4, establishing a gas reservoir geological model and classifying reservoir properties; and S5, corresponding assigning each type of the normalized phase permeability curves and each type of the normalized capillary pressure curves to the gas reservoir geological model to obtain reservoir permeation characteristics and gas reservoir fluid saturation distribution. The fluid saturation field of the complex biological reef gas reservoir established by the application fully reflects the heterogeneity of gas-water distribution of the gas reservoir, improves the rationality and reliability of the description of the gas reservoir fluid saturation distribution, and obtains a fine numerical simulation model of the gas-water distribution which is more consistent with the actual gas reservoir.

Description

Technical Field

[0001] This invention relates to the field of oil and gas development technology, and in particular to a method for establishing a fluid distribution model for carbonate gas reservoirs. Background Technology

[0002] my country possesses abundant carbonate gas reservoirs with enormous reserves. Typically, carbonate gas reservoirs exhibit strong heterogeneity and complex gas-water distribution. Accurately describing the reservoir's reservoir-permeability characteristics and formation fluid saturation distribution is crucial for simulating reservoir development dynamics, adjusting development plans, and efficiently developing the reservoir. Fine characterization of permeability features is fundamental to accurately describing gas-water distribution. Inaccurate descriptions of formation water distribution can affect the understanding of static formation water distribution and water intrusion dynamics, and even the assessment of gas reservoir reserves, leading to inaccurate simulations of reservoir development dynamics and impacting development efficiency.

[0003] Conventional methods for describing reservoir permeability characteristics and fluid saturation distribution are poorly suited to gas reservoirs with severe heterogeneity and cannot adequately depict the complex gas-water distribution characteristics of bioherm gas reservoirs. The conventional approach involves classifying reservoirs based on carbonate rock classification standards in the northeastern Sichuan Basin using relative permeability and capillary pressure experiments, and then using the experimental results to describe the fluid saturation distribution. This approach has two problems: first, conventional reservoir classification standards struggle to fully reflect the heterogeneity of complex bioherm reservoirs; second, conventional methods, when using relative permeability and capillary pressure curves for classification, generally categorize reservoirs simply by macroscopic regions, failing to adequately reflect the differences in microscopic pore throats and thus making it difficult to accurately describe the resulting gas-water saturation distribution within the gas reservoir. Consequently, the described gas-water saturation distribution does not accurately reflect the actual gas-water distribution in the gas reservoir.

[0004] Therefore, it is necessary to propose a method that can fully describe the differences in fluid saturation distribution caused by reservoir heterogeneity in complex bioherm gas reservoirs, so as to achieve a detailed description and characterization of gas-water saturation distribution and gas-water transition zone in gas reservoirs. This will provide technical and theoretical support for simulating gas reservoir development dynamics and carrying out scheme adjustments, and better ensure the continuous and stable production of gas reservoirs and improve gas recovery rate. Summary of the Invention

[0005] The purpose of this invention is to overcome the above-mentioned deficiencies in the prior art and provide a method for establishing a fluid distribution model of carbonate gas reservoirs. By finely characterizing the reservoir permeability characteristics and the distribution of gas reservoir fluid saturation, the rationality and reliability of describing the distribution of gas reservoir fluid saturation are improved, resulting in a fine numerical simulation model of gas-water distribution that is more consistent with the actual gas reservoir, thereby improving the accuracy of dynamic prediction of gas reservoir development.

[0006] To achieve the above-mentioned objectives, the present invention provides the following technical solution:

[0007] A method for establishing a fluid distribution model for carbonate gas reservoirs includes the following steps:

[0008] S1. Perform gas-water phase permeability test and high-pressure mercury injection test on the core samples, and obtain the reservoir classification index, phase permeability curve and capillary pressure curve of each core sample based on the experimental data. The reservoir classification index is one or more of the reservoir quality index (RQI), flow unit index (FZI) and physical property comprehensive index (Zs).

[0009] S2. Use cluster analysis to analyze the reservoir classification index of core samples and establish reservoir classification criteria. Classify the core samples according to the reservoir classification criteria.

[0010] S3. Classify and normalize the relative permeability curves of each type of core sample, and use the J function to classify and normalize the capillary pressure curves of each type of core sample.

[0011] S4. Establish a gas reservoir geological model based on seismic data, well logging data, and core physical property data, and classify the reservoir attributes of the established gas reservoir geological model according to the reservoir classification standard.

[0012] S5. The normalized relative permeability curves and capillary pressure curves of each type are assigned to the gas reservoir geological model to obtain the reservoir permeability characteristics and the distribution of gas reservoir fluid saturation.

[0013] The method of this invention obtains reservoir classification indices, relative permeability curves, and capillary pressure curves for each core sample based on experimental data. The reservoir classification index can be used as a discriminant for reservoir classification, and the established gas reservoir geological model should be able to fully describe the heterogeneity of reservoir physical properties. Using the method of this invention, a gas reservoir fluid distribution model can be established to determine the gas reservoir fluid saturation distribution for dynamic prediction of gas reservoir development. The established gas reservoir fluid distribution model can fully reflect the heterogeneity of gas-water distribution in the gas reservoir, improve the rationality and reliability of describing the gas reservoir fluid saturation distribution, and obtain a more refined numerical simulation model of gas-water distribution that better matches the actual gas reservoir.

[0014] As a preferred embodiment of the present invention, in step S1, the core samples are taken from different types of gas reservoirs. Testing samples from different types of reservoirs can more comprehensively connect the gas reservoirs and make better use of reservoir classification.

[0015] As a preferred embodiment of the present invention, in step S1, the flow unit index is obtained according to formula 1, formula 2 and formula 3, the reservoir quality index is obtained according to formula 2, and the comprehensive physical property index is obtained according to formula 4.

[0016]

[0017]

[0018]

[0019]

[0020] Where φ e denoted as the effective porosity of the core, dimensionless; K is the core permeability, in mD.

[0021] As a preferred embodiment of the present invention, the specific steps for classifying and normalizing the relative permeability curves of each type of core sample in step S3 are as follows:

[0022] S311. The relative permeability endpoints of the core sample are standardized according to Formula 6 to obtain...

[0023] According to formula 5, we get curve, To standardize the relative permeability of the aqueous phase, for

[0024] Standardized gas phase relative permeability, To standardize water saturation;

[0025] S312, to Perform regression fitting to obtain a and b;

[0026] S313, for each type of core sample, a, b, S wi S gr We will average the results to obtain the average value. Given S wD The average relative permeability curves for each type of core sample were obtained according to Formula 7.

[0027] S314. The average relative permeability curve of each type of core sample obtained in step S313 is standardized according to formula 8 to obtain the average relative permeability curve of each type of core sample.

[0028]

[0029]

[0030]

[0031]

[0032] Among them, K rg S represents the relative permeability of the gas phase.w For water saturation, K rw Let S be the relative permeability of the aqueous phase, a and b be regression constants, and S be the relative permeability of the aqueous phase. wi Initial water saturation, S gr S represents the residual gas saturation. wD The water saturation is a constant value, ranging from 0 to 1.

[0033] As a preferred embodiment of the present invention, the capillary pressure curves of each type of core sample are classified and normalized using the J function, including the following steps:

[0034] S321. Establish the JS of the movable water saturation of each core sample. wn The relationships are shown in formulas 9 and 10.

[0035]

[0036]

[0037] Where P c S is the capillary pressure value, σ is the fluid interfacial tension, and θ is the wetting angle; wc φ represents the critical water saturation, φ represents the core porosity (dimensionless), and A and B are constants.

[0038] S322, JS wn The J function is obtained by regression fitting of the relation. Let A be the movable water saturation of core sample k. k B k The constant k in the J-Swn relation for the core sample is used.

[0039] S323. Average the constants A and B of the core samples belonging to each category to obtain representative values ​​for each category. function,

[0040] As a preferred embodiment of the present invention, in step S5, the gas reservoir fluid saturation distribution is obtained, i.e., S is obtained according to formula 11. wn Then, the water saturation S is obtained by standardization according to formula 10. w Formula 11 is as follows:

[0041]

[0042] Among them, P c,res σ represents the actual capillary pressure value of the reservoir. res For the actual fluid interfacial tension in the reservoir, θ res The actual wetting angle of the reservoir, φ is the rock porosity, and K is the permeability.

[0043] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0044] This invention selects reservoir classification indices as the discriminant for reservoir classification. It utilizes cluster analysis to analyze the classification indices of each core sample and establishes reservoir classification standards, better reflecting the heterogeneity of complex bioherm gas reservoirs. Based on the use of relative permeability curves and capillary pressure curves for gas reservoir model classification, the J-function method is employed to consider the differences in reservoir micropore throats. The resulting heterogeneous distribution of fluid saturation shows good agreement with well logging interpretations, and also explains the inconsistency between the production dynamics of producing wells and previous geological understandings. Through this invention's refined description of reservoir permeability characteristics and gas reservoir fluid saturation, the rationality and reliability of describing the distribution of gas reservoir fluid saturation are improved, resulting in a more accurate numerical simulation model of gas-water distribution that better matches actual gas reservoirs, thus enhancing the accuracy of gas reservoir development dynamic prediction. Attached image description:

[0045] Figure 1 A schematic diagram of the method for establishing a fluid distribution model of a carbonate gas reservoir according to the present invention;

[0046] Figure 2 Cluster analysis diagram of reservoir quality index and flow unit index of experimental core in Reef A in this embodiment of the invention;

[0047] Figure 3 A normalized classification result diagram of the relative permeability curves of core samples from Reef Group A in this embodiment of the invention;

[0048] Figure 4 In this embodiment of the invention, core sample JS from Reef Group A wn Relationship curve;

[0049] Figure 5 A cross-sectional view of reservoir properties classification in Reef Group A of this invention;

[0050] Figure 6 A cross-sectional view of the gas saturation distribution of Reef Group A in this embodiment of the invention. Detailed Implementation

[0051] The present invention will be further described in detail below with reference to experimental examples and specific embodiments. However, this should not be construed as limiting the scope of the above-mentioned subject matter of the present invention to the following embodiments; all technologies implemented based on the content of the present invention fall within the scope of the present invention.

[0052] Example 1

[0053] like Figure 1 As shown, a method for establishing a fluid distribution model of a carbonate gas reservoir includes the following steps:

[0054] S1. Perform gas-water phase permeability test and high-pressure mercury injection test on the core samples, and obtain the reservoir classification index, phase permeability curve and capillary pressure curve of each core sample based on the experimental data. The reservoir classification index is one or more of the reservoir quality index RQI, flow unit index FZI and physical property comprehensive index Zs.

[0055] S2. Use cluster analysis to analyze the reservoir classification index of core samples and establish reservoir classification criteria. Classify the core samples according to the reservoir classification criteria.

[0056] S3. Classify and normalize the relative permeability curves of each type of core sample, and use the J function to classify and normalize the capillary pressure curves of each type of core sample.

[0057] S4. Establish a gas reservoir geological model based on seismic data, well logging data, and core physical property data, and classify the reservoir attributes of the established gas reservoir geological model according to the reservoir classification standard.

[0058] S5. The normalized relative permeability curves and capillary pressure curves of each type are assigned to the gas reservoir geological model to obtain the reservoir permeability characteristics and the distribution of gas reservoir fluid saturation.

[0059] This embodiment takes a complex bioherm gas reservoir in a certain area as an example. This bioherm gas reservoir belongs to the bioherm deposits on the edge of the platform. It has developed 4 reef zones, 21 reef groups and 90 individual reef bodies. The individual bioherms are small in scale. They have developed in multiple stages in the vertical direction and multiple reef bodies are superimposed in the horizontal direction. It has the geological characteristics of "one super, three high and five complex". It is a tectonic-lithologic gas reservoir with high sulfur content, local edge (bottom) water, and controlled by reef shoal bodies.

[0060] In step S1, 62 mercury injection core samples and 25 gas-water permeability core samples from the biogenic reef zone were selected. The experimental results were compared and analyzed using well logging interpretation, core analysis, and production dynamics data, concluding that the samples represent most reservoir types in this reef group. After the experiments, reservoir classification indices, permeability curves, and capillary pressure curves were obtained for each core sample. The reservoir quality index and flow unit index within the reservoir classification indices are shown below. Figure 2 As shown.

[0061] The flow unit index is obtained according to formulas 1, 2 and 3, the reservoir quality index is obtained according to formula 2, and the comprehensive physical property index is obtained according to formula 4.

[0062]

[0063]

[0064]

[0065]

[0066] Where FZI is the flow unit index, RQI is the reservoir quality index, and Z is the reservoir quality index. s φ is a comprehensive index of physical properties. e denoted as the effective porosity of the core, dimensionless; K is the core permeability, in mD.

[0067] In step S2, cluster analysis is used to analyze the reservoir classification index of each core sample, and a reservoir classification standard is established. The core samples are then classified according to the reservoir classification standard. Table 1 shows a comparison between the reservoir classification standard of this invention and the original reservoir classification standard.

[0068] Table 1 Comparison of Reservoir Classification Standards

[0069]

[0070] In step S3, the relative permeability curves of each type of core sample are classified and normalized, and the capillary pressure curves are classified and normalized using the J function.

[0071] Based on the classification results of the core reactivity test, and combined with the pore structure and seepage behavior, the classification and adjustment are carried out. The specific steps for classifying and normalizing the reactivity curves of each type of core sample are as follows:

[0072] S311. The relative permeability endpoints of each type of core sample are standardized according to Formula 6 to obtain... According to formula 5, we get curve;

[0073] S312, to Perform regression fitting to obtain a and b;

[0074] S313, for each type of core sample, a, b, S wi S gr We take the average and get the average value a. Given S wD The average relative permeability curves for each type of core sample were obtained according to Formula 7.

[0075] S314. The average relative permeability of water under residual gas saturation and the average relative permeability of gas under bound water saturation obtained in step S313 are standardized according to Formula 8 to obtain the average relative permeability curve of each type of core sample, namely gas-water phase permeability and water saturation.

[0076]

[0077]

[0078]

[0079]

[0080] Among them, K rg S represents the relative permeability of the gas phase. w For water saturation, K rw Let S be the relative permeability of the aqueous phase, a and b be regression constants, and S be the relative permeability of the aqueous phase. wi Initial water saturation, S gr S represents the residual gas saturation. wD The water saturation is a constant value, ranging from 0 to 1.

[0081] like Figure 3 As shown, after normalization, the endpoint values ​​of the relative permeability curves for sample I are as follows: bound water saturation of 38.49%, gas phase permeability under bound water of 0.560, gas saturation at isotonic point of 23.72%, and relative permeability at isotonic point of 0.109; bound water saturation of sample II is 41.34%, gas phase permeability under bound water of 0.334, gas saturation at isotonic point of 21.91%, and relative permeability at isotonic point of 0.073; and bound water saturation of sample III is 53.52%, gas phase permeability under bound water of 0.061, gas saturation at isotonic point of 13.15%, and relative permeability at isotonic point of 0.021.

[0082] The JS function is used to process the capillary pressure curves of each type of core sample and then classify and normalize them, thus establishing the core sample's JS function. wn The relationship includes the following steps:

[0083] S321. Establish the JS of the movable water saturation of each core sample. wn The relationships are shown in formulas 9 and 10.

[0084]

[0085]

[0086] Where P c S is the capillary pressure value, σ is the fluid interfacial tension, and θ is the wetting angle; wc The critical water saturation is given by A and B, which are constants.

[0087] S322, JS wn The J function is obtained by regression fitting of the relation.

[0088] S323. Average the constants A and B of the core samples belonging to each category to obtain representative values ​​for each category. function,

[0089] It is known that the contact angle between mercury and air in the laboratory is 140° and the interfacial tension is 480 mN / m; under formation conditions, the gas-water interface contact angle is 0°. Since interfacial tension is affected by temperature and pressure, it is calculated from the difference in gas-water interfacial tension under different temperature and pressure conditions. The temperature of the Yuanba Changxing Formation gas reservoir is generally around 152℃ and the formation pressure is around 68 MPa, resulting in an interfacial tension of 35.68 mN / m for the gas and water phases under these conditions.

[0090] After standardizing and regressing various types of core samples, the average values ​​of regression parameters a and b are obtained, resulting in the JS. wn The JS values ​​after averaging the relational expressions are obtained as the average of the Class I samples. wn Relationship; JS after averaging of type II samples wn Relationship; JS after averaging of Class III samples wn Relationship.

[0091] In step S4, a gas reservoir geological model is established, and the reservoir attributes of the established three-dimensional gas reservoir geological model are classified according to the established classification criteria, such as... Figure 6 As shown;

[0092] In step S5, the various relative permeability curves and capillary pressure curves after classification and normalization are combined and applied to various reservoirs in different regions. The J-Swn relationship under various reservoir conditions is established to finely characterize the complex gas-water distribution.

[0093] According to formula 11, S is obtained. wn Then, the water saturation S is obtained by standardization according to formula 10. w Formula 11 is as follows:

[0094]

[0095] Among them, P c,res σ represents the actual capillary pressure value of the reservoir. res For the actual fluid interfacial tension in the reservoir, θ res The actual wetting angle of the reservoir, φ is the rock porosity, and K is the permeability.

[0096] The capillary pressure under gas reservoir conditions is obtained using the actual interfacial tension σ of the reservoir fluid, the wetting angle θ, and the porosity φ and permeability K of the rock. Substituting the three types of J-Swn relationships, we obtain the capillary pressure values ​​for Zone 1 (i.e., Zone III). Zone 2 (i.e., Category II) Zone 3 (i.e., Category I)

[0097] By combining the endpoint values ​​of the three types of relative permeability curves, the water saturation of each grid in different types of reservoirs can be determined, achieving a precise characterization of the initial fluid saturation. The gas reservoir fluid distribution model established using the method of this invention can fully reflect the heterogeneity of gas-water distribution in gas reservoirs, and it matches the actual situation well in terms of water saturation distribution, reserves and water body size, and production dynamics.

[0098] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for establishing a fluid distribution model for carbonate gas reservoirs, characterized in that, The carbonate gas reservoir is a complex bioherm gas reservoir, comprising the following steps: S1. Perform gas-water phase permeability test and high-pressure mercury injection test on the core samples, and obtain the reservoir classification index, phase permeability curve and capillary pressure curve of each core sample based on the experimental data. The reservoir classification index is one or more of the reservoir quality index, flow unit index and physical property comprehensive index. S2. Use cluster analysis to analyze the reservoir classification index of core samples and establish reservoir classification criteria. Classify the core samples according to the reservoir classification criteria. S3. Classify and normalize the relative permeability curves of each type of core sample, and use the J function to classify and normalize the capillary pressure curves of each type of core sample; the specific steps for classifying and normalizing the relative permeability curves of each type of core sample are as follows: S311. The relative permeability endpoints of the core sample are standardized according to Formula 6 to obtain... , , According to Formula 5, we get , curve; S312, to , Perform regression fitting to obtain a and b; S313, for each type of core sample, a, b, S wi S gr We will average the results to obtain the average value. , , , Given The average relative permeability curves for each type of core sample were obtained according to Formula 7. S314. The average relative permeability curve of each type of core sample obtained in step S313 is standardized according to formula 8 to obtain the average relative permeability curve of each type of core sample. （5） （6） （7） （8） Among them, K rg S represents the relative permeability of the gas phase. w For water saturation, K rw Let S be the relative permeability of the aqueous phase, a and b be regression constants, and S be the relative permeability of the aqueous phase. wi Initial water saturation, S gr Residual gas saturation, The water saturation is a constant value, ranging from 0 to 1. The JS function is used to process the capillary pressure curves of each type of core sample and then classify and normalize them, thus establishing the core sample's JS function. wn The relationship includes the following steps: S321. Establish the mobile water saturation of each core sample. J- The relationships are shown in Formulas 9 and 10. （9） （10） in, P represents the saturation level of mobile water. c σ is the capillary pressure value, σ is the fluid interfacial tension, and θ is the wetting angle; Core porosity The critical water saturation is given by A and B, which are constants. S322, J- The J function is obtained by regression fitting of the relation. ; S323. Average the constants A and B of the core samples belonging to each category to obtain representative values ​​for each category. function, ; S4. Establish a gas reservoir geological model based on seismic data, well logging data, and core physical property data, and classify the reservoir attributes of the established gas reservoir geological model according to the reservoir classification standard. S5. Assign the normalized relative permeability curves and capillary pressure curves of each category to the gas reservoir geological model to obtain the reservoir permeability characteristics and gas reservoir fluid saturation distribution. The gas reservoir fluid saturation distribution is obtained according to Formula 11. Then, the water saturation is obtained by standardization according to formula 10. Formula 11 is as follows: （11） in, This represents the actual capillary pressure value of the reservoir. This represents the actual interfacial tension of the reservoir fluid. Actual wetting angle of the reservoir.

2. The method for establishing a fluid distribution model of a carbonate gas reservoir according to claim 1, characterized in that, In step S1, core samples are taken from different types of gas reservoirs.

3. The method for establishing a fluid distribution model of a carbonate gas reservoir according to claim 1, characterized in that, In step S1, the flow unit index is obtained according to formulas 1, 2 and 3, the reservoir quality index is obtained according to formula 2, and the comprehensive physical property index is obtained according to formula 4. （1） （2） （3） （4） in, For flow unit index, This is the reservoir quality index. It is a comprehensive index of physical properties. denoted as the effective porosity of the core, dimensionless; K is the core permeability, in mD.

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