Carbonate rock petrophysical modeling method and application, device, equipment and medium

Abstract

The present invention discloses a carbonate rock physics modeling method and application, device, equipment, and medium, belonging to the field of geophysical exploration. The modeling method of the present invention is: establishing a pore quantitative interpretation template through logging data, determining the pore type and pore parameters of each type of pore, adding the pores to the rock matrix to obtain a dry rock skeleton model, adding the fluid mixture to the dry rock skeleton model, and establishing a carbonate rock physics model; and using the rock physics model to estimate the longitudinal and shear wave velocities of the rock; the present invention also provides an apparatus, computer equipment, and computer-readable storage medium for implementing the above method. The present invention solves the problem of large differences in estimation results using conventional rock physics models due to the multiple pore structures of carbonate rocks, and can use the carbonate rock physics model to quickly and accurately obtain shear wave estimation information. The present invention can be applied to carbonate rock physics modeling and prestack inversion technology.

Description

Technical Field

[0001] The present invention belongs to the field of geophysical exploration and relates to a carbonate rock physical modeling technology, specifically a carbonate rock physical modeling method and application, device, equipment and medium. Background Art

[0002] Rock physics models bridge reservoir parameters and seismic attributes, providing a theoretical basis for lithology classification and oil and gas detection. Permeability is a key factor influencing oil and gas accumulation. Therefore, predicting the pore structure of rock models is crucial for identifying areas with favorable pore structure development and, in turn, for finding high-quality reservoirs with high porosity, permeability, and oil and gas saturation.

[0003] Due to the complex sedimentary environment and the influence of multiple factors such as weathering, leaching, and tectonic alteration, carbonate rocks have a wide variety of pore types, strong heterogeneity, and significant differences between different pore structures. Conventional rock physics modeling techniques are mostly used to predict the total porosity of rocks, but it is difficult to further subdivide the effective porosity of various pore types. Therefore, it is difficult to accurately establish the pore structure of carbonate rocks using conventional rock physics modeling methods. Prestack inversion has always been an effective means of reservoir prediction and fluid identification, but it requires accurate P- and S-wave information as support. However, in actual production, S-wave information is difficult to obtain due to high costs. Therefore, S-wave estimation has been a widely discussed issue.

[0004] In summary, given the characteristics of multiple pore development in carbonate rocks, there is an urgent need in production to develop a rock physics modeling method and its apparatus, computer equipment, and computer-readable storage medium that can effectively characterize the pore structure of carbonate rocks, and use this rock physics model for shear wave estimation. Summary of the Invention

[0005] To address the above deficiencies in the prior art, one objective of the present invention is to provide a method for modeling carbonate rock physics based on the multiple pore characteristics of carbonate rock, and an application for obtaining P- and S-wave data. Another objective of the present invention is to provide an apparatus, computer equipment, and computer-readable storage medium for running the above method and application. To achieve the above objectives, the technical solutions adopted by the present invention are as follows:

[0006] A carbonate rock physical modeling method comprises the following steps performed in sequence:

[0007] S1. Obtain the mineral components of the carbonate rock matrix and the volume content of each component, and calculate the total porosity of the carbonate rock;

[0008] S2. Using the mineral composition and total porosity of the carbonate rock matrix, establish a quantitative pore interpretation template with P-wave velocity as the ordinate and total porosity as the abscissa. Apply the well logging curves to the template to determine the pore type and pore parameters of each pore type. The templates are divided into limestone and dolomite pore interpretation templates. The pore parameters include porosity and pore aspect ratio.

[0009] S3. Establish a dry rock skeleton model using the pore parameters of the carbonate rock matrix and various pore types;

[0010] S4. Add the fluid mixture to the dry rock skeleton model to establish a carbonate rock physics model.

[0011] Furthermore, the step S2 is:

[0012] Based on the correspondence between the P-wave velocity and total porosity of each pore type of carbonate mineral components, a pore quantitative interpretation template is constructed to determine the pore types and pore parameters in the rock. Pore types include matrix pores, dissolved pores, and fractures, and pore parameters include porosity and pore aspect ratio.

[0013] S2a. Construction of a quantitative pore interpretation template: Based on the preset porosity and initial pore aspect ratio of the rock matrix mineral components, the P-wave velocity of each pore type is calculated using the differential equivalent medium model. A quantitative pore interpretation template is established with the P-wave velocity as the ordinate and the total porosity as the abscissa.

[0014] The calculation method of the P-wave velocity of each pore type is:

[0015] 1) For matrix pores, the Wyllie time-averaged equation is used to calculate the relationship between total porosity and P-wave velocity;

[0016] 2) For dissolved pores, the Hashin-Shtrikman upper bound formula is used to calculate the relationship between total porosity and P-wave velocity;

[0017] 3) For cracks, the Hashin-Shtrikman lower bound formula is used to calculate the relationship between total porosity and P-wave velocity;

[0018] Carbonate rocks can be divided into limestone and dolomite due to differences in sedimentary environments. The two have different mineral compositions: limestone is mainly composed of calcite, while dolomite is mainly composed of dolomite. Therefore, corresponding pore quantitative interpretation templates need to be established for limestone and dolomite respectively. The limestone pore quantitative interpretation template is suitable for areas where the carbonate rock mineral composition is calcite, while the dolomite pore quantitative interpretation template is suitable for areas where the carbonate rock mineral composition is dolomite.

[0019] The corresponding relationship is as follows:

[0020] (1) For limestone:

[0021] ① When the pore type is 100% solution pore, the expression formula is: Y = 6627.2-5244.34*x+3449.7*x^2, and the corresponding pore aspect ratio is 0.8;

[0022] ② When the pore type is 80% solution pores and 20% matrix pores, the formula is Y = 6632.73-8326.18*x+12347.4*x^2-9692.21*x^3, and the corresponding pore aspect ratio is 0.6;

[0023] ③ When the pore type is 60% solution pores and 40% matrix pores, the formula is Y = 6626.65-10737.2*x+18213.1*x^2-15316.8*x^3, and the corresponding pore aspect ratio is 0.5;

[0024] ④ When the pore type is 40% solution pores and 60% matrix pores, the formula is Y = 6620.41-12891*x+23322.2*x^2-20280.2*x^3, and the corresponding pore aspect ratio is 0.4;

[0025] ⑤ When the pore type is 20% solution pores and 80% matrix pores, the formula is Y = 6614.4-14848.6*x+27847.7*x^2-24596*x^3, and the corresponding pore aspect ratio is 0.2;

[0026] ⑥ When the pore type is 100% matrix pores, the formula is Y = 6608.86-16656.4*x+31942.2*x^2-28300.3*x^3, and the corresponding pore aspect ratio is 0.1;

[0027] ⑦ When the pore types are 20% cracks and 80% matrix pores, the formula is Y = 6609.64-33960.1*x+125424*x^2-250840*x^3+206660*x^4, and the corresponding pore aspect ratio is 0.08;

[0028] ⑧ When the pore types are 40% cracks and 60% matrix pores, the formula is Y = 6595.48-45162*x+206858*x^2-466117*x^3+406744*x^4, and the corresponding pore aspect ratio is 0.06;

[0029] ⑨ When the pore type is 60% fractures and 40% matrix pores, the formula is Y = 6630.8-58481.4*x+378148*x^2-1.35135e+6*x^3+2.4885e+6*x^4-1.8367e+6*x^5, and the corresponding pore aspect ratio is 0.04;

[0030] ⑩ When the pore type is 80% cracks and 20% matrix pores, the formula is Y = 6616.97-66723.1*x+494932*x^2-1.96693e+6*x^3+3.91474e+6*x^4-3.0579e+6*x^5, and the corresponding pore aspect ratio is 0.02;

[0031] When the pore type is 100% cracks, the formula is Y=6600.7-73879*x+616178*x^2-3e+6*x^3+6e+6*x^4-5e+6*x^5, and the corresponding pore aspect ratio is 0.01.

[0032] (2) For dolomite:

[0033] ① When the pore type is 100% solution pore, the expression formula is Y = 7335.67-5497.03*x+3395.6*x^2, and the corresponding pore aspect ratio is 0.8;

[0034] ② When the pore type is 80% solution pores and 20% matrix pores, the formula is Y = 7340.54-8779.48*x+12312*x^2-9331.64*x^3, and the corresponding pore aspect ratio is 0.6;

[0035] ③ When the pore type is 60% solution pores and 40% matrix pores, the formula is Y = 7334.74-11474.7*x+18577*x^2-15176.9*x^3, and the corresponding pore aspect ratio is 0.5;

[0036] ④ When the pore type is 40% solution pores and 60% matrix pores, the formula is Y = y = 7328.54-13940.1*x + 24185.9*x^2-20504*x^3, and the corresponding pore aspect ratio is 0.4;

[0037] ⑤ When the pore type is 20% solution pores and 80% matrix pores, the formula is Y = 7322.34-16223.7*x+29273.2*x^2-25267.8*x^3, and the corresponding pore aspect ratio is 0.2;

[0038] ⑥ When the pore type is 100% matrix pores, the formula is Y = 7316.45-18364.4*x+33967.1*x^2-29457.2*x^3, and the corresponding pore aspect ratio is 0.1;

[0039] ⑦ When the pore types are 20% cracks and 80% matrix pores, the formula is Y = 7310.45-39342.3*x+145210*x^2-290649*x^3+240064*x^4, and the corresponding pore aspect ratio is 0.08;

[0040] ⑧ When the pore types are 40% cracks and 60% matrix pores, the formula is Y = 7289.01-53420.1*x+246445*x^2-556242*x^3+485751*x^4, and the corresponding pore aspect ratio is 0.06;

[0041] ⑨ When the pore type is 60% fractures and 40% matrix pores, the formula is Y = 7331.1-70216*x+460126*x^2-1.65193e+6*x^3+3.04961e+6*x^4-2.25523e+6*x^5, and the corresponding pore aspect ratio is 0.04;

[0042] ⑩ When the pore type is 80% cracks and 20% matrix pores, the formula is Y = 7314.19-80817.5*x+609036*x^2-2.4317e+6*x^3+4.84706e+6*x^4-3.78816e+6*x^5, and the corresponding pore aspect ratio is 0.02;

[0043] When the pore type is 100% cracks, the formula is Y = 7313.2-95751*x+934409*x^2-5e+6*x^3+2e+7*x^4-3e+7*x^5+2e+7x^6, and the corresponding pore aspect ratio is 0.01.

[0044] The closer the sample point is to the vertical coordinate of the preset equation in the pore quantitative interpretation template, the higher the probability; the farther the distance is, the lower the probability.

[0045] S2b. Applying well logging curves to the pore quantitative interpretation template: Given the total porosity and P-wave velocity of the rock, the well logging curves are superimposed on the pore quantitative interpretation template for comparative analysis. A computer algorithm automatically searches for the nearest pore quantitative interpretation template value to determine the pore structure.

[0046] S2c. In the pore quantitative interpretation template, the P-wave velocity-total porosity equations corresponding to each pore type are hierarchically sorted, and the difference between the P-wave velocity of the rock and the P-wave velocity of each pore type is calculated step by step. The pore structure corresponding to the minimum square value of the difference is found to determine the pore type of the rock.

[0047] S2d obtains the volume percentage and pore aspect ratio corresponding to different pore types according to the pore type;

[0048] First, the corresponding equations of each P-wave velocity and total porosity under different pore structures are ranked: the pore type is all dissolved pores, which corresponds to level I; the pore type is 80% dissolved pores and 20% matrix pores, which corresponds to level II; the pore type is 60% dissolved pores and 40% matrix pores, which corresponds to level III; the pore type is 40% dissolved pores and 60% matrix pores, which corresponds to level IV; the pore type is 20% dissolved pores and 80% matrix pores, which corresponds to level The corresponding pore type is 5%, which is % of the matrix pores; the corresponding pore type is 6%, which is 20% of the matrix pores; the corresponding pore type is 80% of the matrix pores, which is 7% of the matrix pores; the corresponding pore type is 40% of the matrix pores, which is 60% of the matrix pores, which is 8% of the matrix pores; the corresponding pore type is 80% of the matrix pores, which is 20% of the matrix pores; the corresponding pore type is 10%, which is 11% of the matrix pores.

[0049] According to the above classification, the square of the difference between the P-wave velocity of the rock and the P-wave velocity of each pore type is calculated step by step. The formula is as follows:

[0050] E i =(Y sample -Y i ) 2 , i∈(Ⅰ,Ⅱ,Ⅲ,Ⅳ,Ⅴ,Ⅵ,Ⅶ,Ⅷ,Ⅸ,Ⅹ,Ⅺ)

[0051] According to the above formula, the square values ​​Ei of the differences in all 11 arrays are compared, and the i value corresponding to the minimum Ei is taken to obtain the pore structure corresponding to the i value, and the pore type of the rock is obtained, and then the volume percentage and pore aspect ratio corresponding to different pore types are determined.

[0052] S2e. Determine the porosity of the pores based on the volume percentage of each pore type, where the relationship is:

[0053] (1) Total porosity = effective porosity + clay porosity;

[0054] (2) Effective porosity = matrix pore porosity + solution pore porosity + fracture porosity;

[0055] (3) Matrix pore effective porosity = total porosity * matrix pore volume percentage;

[0056] (4) Effective porosity of dissolved pores = total porosity * percentage of dissolved pore volume;

[0057] (5) Effective porosity of fracture = total porosity * percentage of fracture volume.

[0058] Furthermore, the step S1 is:

[0059] S1a. Establishing a connection with an external data system and obtaining mineral composition and well logging curves of carbonate rocks based on the external data system, wherein the well logging curves include at least one of compensated neutron logging curves, acoustic time difference curves, density curves, and gamma curves;

[0060] S1b. Establishing a logging response equation by selecting a logging curve;

[0061] S1c. Calculating the volume content of each of the mineral components by the logging response equation;

[0062] S1d. Calculate the bulk modulus and shear modulus of the mixed mineral components using a preset rock modulus model;

[0063] Wherein, the preset rock modulus model includes the Voigt-Reuss-Hil average modulus model;

[0064] S1e. Then determine the equivalent mineral modulus and total porosity of carbonate rocks.

[0065] The step S3 is:

[0066] By using the differential equivalent medium model in multiple iterations, the pores obtained in step S2 are added to the rock matrix in step S1 to establish a dry rock skeleton model, thereby obtaining the bulk modulus and shear modulus of the dry rock skeleton.

[0067] The step S4 is:

[0068] Based on the equivalent mineral modulus of the carbonate rock, the bulk modulus and the shear modulus of the dry rock skeleton, the fluid mixture of the carbonate rock is added to the dry rock skeleton obtained in step S3 to obtain a carbonate rock petrophysical model.

[0069] Furthermore, in step S4,

[0070] Given the complex pore structure of carbonate rocks, to ensure the accuracy of fluid replacement results, it is important to consider the impact of microfractures on Gassmann fluid replacement in carbonate rocks. Microfractures are extremely small and have very low local permeability, which limits or slows down pore fluid pressure relaxation. Fluids are often trapped in these microfractures and unable to flow, resulting in lower predicted Gassmann fluid replacement rates compared to actual measurements. Therefore, the fluid mixture is added as follows: Gassmann fluid replacement is used for matrix pores, solution pores, and fractures other than microfractures, and Brie model fluid replacement is used for microfractures.

[0071] The present invention also provides an application of a carbonate rock physical modeling method, which uses the carbonate rock physical model to calculate the shear wave velocity and longitudinal wave velocity of the carbonate rock.

[0072] Furthermore, the specific steps of this application are:

[0073] Sa. Calculate the bulk modulus and shear modulus of the rock based on the carbonate rock physics model;

[0074] Sb based on the bulk modulus and shear modulus of the rock, the elastic response characteristics of the rock;

[0075] Sc. Determining the shear wave velocity and the longitudinal wave velocity of the carbonate rock based on the elastic response characteristics of the rock.

[0076] The present invention also provides a carbonate rock physical modeling device, which is characterized by comprising:

[0077] Rock information acquisition unit: used to obtain the mineral components of the carbonate rock matrix and the volume content of each component, and calculate the equivalent mineral modulus and total porosity of the carbonate rock;

[0078] Pore ​​type determination unit: used to determine the pore type and pore parameters of various pores based on the pore quantitative interpretation template;

[0079] Dry rock skeleton model building unit: used to add various pores into the carbonate rock matrix to build a dry rock skeleton model;

[0080] Carbonate rock physical model building unit: used to add the fluid mixture of carbonate rock to the dry rock skeleton model to obtain the carbonate rock physical model.

[0081] The present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, any of the above-mentioned carbonate rock physical modeling methods is implemented.

[0082] The present invention also provides a computer-readable storage medium storing a computer program for executing any one of the above-mentioned carbonate rock physical modeling methods.

[0083] The principle of the present invention is:

[0084] Classical rock physics models establish the relationships between rock-forming minerals, the rock skeleton, porosity, and pore fluids. In rock physics modeling of carbonate reservoirs, the rock can be simplified into a two-phase medium: one phase is the rock skeleton, composed of a single or combined mineral; the other phase is the pore fluid within the rock skeleton, composed of liquid or gas. Regarding the mineral composition of the rock skeleton, the primary method for calculating mineral content is optimization logging interpretation. Regarding rock structure, the theoretical models involved can be roughly divided into three categories: porous media volume-averaged theory, such as the Wood equation and the Wyllie time-averaged equation, is used to account for mineral properties; adaptive theories, such as the Gassmann model, are used to account for the influence of spherical pores, ellipsoidal pores, and fractures within the rock on rock properties; and elastic contact theories, such as the Hertz contact theory, are used to account for the contact relationships between rock particles. This present invention, based primarily on these theories, establishes a carbonate rock physics model by clarifying rock pore types and pore parameters, and an equivalent dry rock skeleton.

[0085] Due to the adoption of the above technical solution, the present invention has the following beneficial effects compared with the prior art:

[0086] (1) The present invention targets the structural characteristics of multiple pores in carbonate rocks. By only acquiring conventional well logging data and clarifying the proportions of the main rock matrix components, the construction of a carbonate rock physics model can be quickly achieved.

[0087] (2) The present invention establishes an equivalent pore structure model by constructing a quantitative pore interpretation template, linking the pore type and the pore parameters of each pore, and solving technical problems in the prior art such as the difficulty in fine modeling due to the strong heterogeneity of carbonate rocks and the complex pore structure;

[0088] (3) The quantitative interpretation template of pores constructed by the present invention selects different rock types for estimation, and the prediction results are more reasonable than those of a single template. After testing, in the case of limestone, different pore types interpreted by three sections of imaging logging were selected and tested with the program. When the total porosity was 5% and the P-wave velocity was 4500 m / s, the predicted pores contained 60% fractures and 40% matrix pores; when the total porosity was 10% and the P-wave velocity was 5400 m / s, the predicted pores contained 20% dissolved pores and 80% matrix pores; when the total porosity was 15% and the P-wave velocity was 5380 m / s, the predicted pores contained 60% dissolved pores and 40% matrix pores. The test results are basically consistent with the imaging logging interpretation results;

[0089] (4) The present invention points out the influence of fracture scale on Gassmann fluid replacement, analyzes the complex situation caused by the influence of filling on fractures, determines the influence and effect of fracture fluid replacement, and further improves the accuracy of fluid replacement and shear wave prediction;

[0090] (5) The carbonate rock physics modeling method of the present invention can quickly and accurately obtain P- and S-wave estimation results. Since it integrates calculation formulas corresponding to a variety of different lithologic proportions, it has universal applicability for S-wave estimation of carbonate rocks under multiple geological conditions. The correlation between the prediction results and the measured S-waves reaches over 90%, which is highly reliable and provides workers with the basic data required for pre-stack reservoir prediction.

[0091] (6) The device, computer equipment and computer-readable storage medium provided by the present invention can quickly and effectively construct a carbonate rock physical model. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] The present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.

[0093] Figure 1 This is a template diagram for quantitative interpretation of pores in limestone in Example 1, where the abscissa represents total porosity and the ordinate represents P-wave velocity;

[0094] Figure 2 This is a template diagram for quantitative interpretation of porosity of dolomite in Example 1, where the abscissa represents total porosity and the ordinate represents P-wave velocity;

[0095] Figure 3 This is a diagram showing the shape division of different pore types in Example 1, where: Figure 3 a is the solution pore, Figure 3 b is the matrix pore, Figure 3 c is a crack;

[0096] Figure 4This is a diagram of the operation steps of multiple iterations of the differential equivalent medium model in Example 1;

[0097] Figure 5 This is a quantitative interpretation chart of the pore structure of the carbonate reservoir in Example 1;

[0098] Figure 6 This is a comparison chart for verifying the fluid replacement effect in Example 1, where: Figure 6 a is the cross-plot when all fractures are replaced by Gassmann fluid. Figure 6 b is the cross-plot of the macropore using Gassmann fluid replacement and the microcrack using the equivalent medium model;

[0099] Figure 7 This is a diagram verifying the effect of carbonate rock pore structure prediction in Example 1, where: Figure 7 a is the pore structure diagram interpreted by imaging logging in real wells, Figure 7 b is the model diagram of the predicted pore structure parameters;

[0100] Figure 8 A comparison diagram of the P-wave and S-wave velocity curves predicted in Example 2 and the P-wave and S-wave velocity curves of the measured wells;

[0101] Figure 9 This is an error analysis diagram of the predicted curve relative to the measured curve in Example 2, where: Figure 9 a is the error diagram of the longitudinal wave curve, Figure 9 b is the error diagram of the shear wave curve;

[0102] Figure 10 This is a flow chart of the carbonate rock physical model device in Example 2, including: 1. rock information acquisition unit; 2. pore type determination unit; 3. dry rock skeleton model establishment unit; 4. carbonate rock rock physical model establishment unit. DETAILED DESCRIPTION

[0103] The present invention will be further described in detail below through specific embodiments. It should be understood that the preferred embodiments described herein are only used to illustrate and understand the present invention and are not intended to limit the present invention.

[0104] Unless otherwise specified, the materials and reagents used in the examples of the present invention can be obtained from commercial sources. Experimental methods without specific conditions in the examples are generally performed under conventional conditions or the conditions recommended by the manufacturer.

[0105] Example 1 A method for rock physics modeling of carbonate rocks

[0106] This embodiment provides a method for rock physics modeling of carbonate rocks, including the following steps performed in sequence:

[0107] First, a carbonate well was selected and identified, and its logging data was actually tested for subsequent use. Because acoustic waves are affected by both the physical properties of the rock and the pore fluid, to ensure the model more closely resembles the actual rock characteristics and minimize errors caused by these factors, the original pore fluid was replaced with a single fluid environment saturated with brine before this study. After obtaining the bulk modulus and shear modulus corresponding to the dry rock skeleton, the original pore fluid was then replaced to simulate the shear wave velocity under realistic formation conditions.

[0108] S1. Obtain the mineral components of carbonate rock and the volume content of each component, and calculate the equivalent mineral modulus and total porosity of carbonate rock:

[0109] S1a. Because carbonate rocks often contain quartz and clay minerals, they should also be considered as optional mineral components during modeling. In the volume interpretation model, V0 represents the volume fraction of pores, V1 represents the volume fraction of calcite, V2 represents the volume fraction of dolomite, V3 represents the volume fraction of quartz, V4 represents the volume fraction of feldspar, and V5 represents the volume fraction of clay minerals.

[0110] Under the condition of known porosity, four logging curves are selected: acoustic transit time curve (AC), density curve (DEN), compensated neutron logging curve (NPHI) and gamma curve (GR).

[0111] S1b. Establish appropriate logging response equations by selecting the four well logging curves mentioned above. The principle of the multivariate fitting optimization calculation method is based on the fact that multiple basic well logging curves can reflect the reservoir's lithology, physical properties, electrical properties, and hydrocarbon content. Using reservoir parameters and mineral relative volumes as independent variables, the matrix is ​​used to jointly solve each logging response equation. Based on the principles of nonlinear weighted least squares and error theory, the actual reservoir parameters and relative mineral content of the formation are inversely calculated, resulting in the optimized logging interpretation results.

[0112] S1c. Calculating the volume content of each of the mineral components by the logging response equation;

[0113] Carbonate rocks can be divided into limestone and dolomite. The main mineral component of limestone is calcite, which sometimes contains dolomite, clay minerals, and detrital minerals. The main mineral component of limestone is dolomite, which is often mixed with quartz, feldspar, calcite, and clay minerals. The logging parameter values ​​of each mineral component selected in the calculation of the volume content of each mineral component in a well selected in this example are shown in Table 1.

[0114] Table 1 Logging parameter values ​​of mineral components

[0115]

[0116] The present invention uses an optimization interpretation algorithm for rock volume components and reservoir parameters, and solves the problem based on the principle of nonlinear weighted least squares method, so that the volume content value that satisfies the error condition of the objective function value is used as the content of each mineral component of the carbonate rock. Among them, due to the complexity of the mineral composition, porosity structure and oil and gas content of the formation, the characteristic value of the logging curve is often a comprehensive response of multiple characteristics of the formation. Moreover, due to the influence of factors such as the measurement environment, the characteristic value of the logging curve often has unpredictable problems. In this case, it is necessary to allow a certain error (Err) between the fitting curve and the input curve. The logging response equation is:

[0117] AC=AC0*V0+AC1*V1+AC2*V2+AC3*V3+AC4*V4+AC5*V5+Err1

[0118] DEN=DEN0*V0+DEN1*V1+DEN2*V2+DEN3*V3+DEN4*V4+DEN5*V5+Err2

[0119] NPHI=NPHI0*V0+NPHI1*V1+NPHI2*V2+NPHI3*V3+NPHI4*V4+NPHI5*V5+Err3

[0120] GR=GR0*V0+GR1*V1+GR2*V2+GR3*V3+GR4*V4+GR5*V5+Err4

[0121] V0+V1+V2+V3+V4+V5=1

[0122] Where: AC0, AC1, AC2, AC3, AC4, AC5 are the acoustic time differences of the above six components, DEN0, DEN1, DEN2, DEN3, DEN4, DEN5 are the densities of the above six components, NPHI0, NPHI1, NPHI2, NPHI3, NPHI4, NPHI5 are the compensated neutron porosities of the above six components, GR0, GR1, GR2, GR3, GR4, GR5 are the gamma values ​​of the above six components, V0, V1, V2, V3, V4, V5 are the volume content of each component. The constraint condition of rock component content is: 0≦V i ≦1.

[0123] S1d. Calculate the bulk modulus and shear modulus of mixed mineral components using the Voigt-Reuss-Hil average modulus model;

[0124] S1e. Then determine the equivalent mineral modulus and total porosity of carbonate rocks.

[0125] S2. Establish a quantitative pore interpretation template and determine the pore types and pore parameters of each type of pore:

[0126] S2a. Construction of pore quantitative interpretation template: According to the different mineral components in carbonate rocks, pore quantitative interpretation templates for limestone and dolomite were established respectively, such as Figure 1 and Figure 2 As shown in the figure, the horizontal axis is the total porosity of the rock, the vertical axis is the longitudinal wave velocity of each pore type, and each curve in the figure represents each pore type. The pore type and pore parameters in the rock are determined based on the pore quantitative interpretation template. The pore types include: matrix pores, solution pores and cracks. The shapes of the three pores are divided as follows: Figure 3 As shown, Figure 3 a is the solution pore, Figure 3 b is the matrix pore, Figure 3 c is a crack; pore parameters include porosity and pore aspect ratio;

[0127] In rock physics modeling, pore type is generally defined by the pore's "aspect ratio", which refers to the ratio of the length of the pore's minor axis to its major axis. In general, the aspect ratio of a fracture is "α crack " is close to 0.01, and the aspect ratio of the circular pore "α stiff " is close to 1, the aspect ratio of the intergranular pores "α inter ” Mostly between 0.08 and 0.15.

[0128] To construct the interpretation scale, it is necessary to calculate the P-wave velocity and porosity corresponding to each pore type based on the preset porosity and initial pore aspect ratio, while clarifying the rock matrix composition. This allows the volume components and aspect ratios corresponding to different pore combinations to be determined. For a specific carbonate matrix composition, the corresponding equations for different P-wave velocities, total porosities, pore structures, and pore aspect ratios are shown in S2a of the Summary of the Invention.

[0129] S2b. Applying well logging curves to the pore quantitative interpretation template: Given the total porosity and P-wave velocity of the rock, the well logging curves are superimposed on the pore quantitative interpretation template for comparative analysis. A computer algorithm automatically searches for the nearest pore quantitative interpretation template value to determine the pore structure.

[0130] S2c. After determining the main rock type, in the pore quantitative interpretation template, the P-wave velocity-total porosity equations corresponding to each pore type are hierarchically sorted, with the vertical coordinate distance between the input curve sample point and the preset nonlinear equation representing each pore structure representing the probability. The closer the sample point is to the vertical coordinate of the preset equation in the pore quantitative interpretation template, the higher the probability, and the closer the sample point is to the vertical coordinate of the preset equation in the pore quantitative interpretation template, the lower the probability. Then, the difference between the P-wave velocity of the rock and the P-wave velocity of each pore type is calculated step by step, and the pore structure corresponding to the case where the square value of the difference is minimized is found to obtain the pore type of the rock;

[0131] In the device, the primary carbonate rock type (limestone / dolomite) is determined first, and then the acoustic and total porosity curves are loaded into the corresponding worksheets. The principle and method for determining the volume fraction and aspect ratio of pores using the program are as follows:

[0132] First, the corresponding equations of each longitudinal wave velocity and total porosity under different pore structures are ranked: the pore type is all dissolved pores, which corresponds to level I; the pore type is 80% dissolved pores and 20% intergranular pores, which corresponds to level II; the pore type is 60% dissolved pores and 40% intergranular pores, which corresponds to level III; the pore type is 40% dissolved pores and 60% intergranular pores, which corresponds to level IV; the pore type is 20% dissolved pores and 80% intergranular pores, which corresponds to level The corresponding pore type is 5 when the pore type is all intergranular pores; the corresponding pore type is VI when the pore type is 20% cracks and 80% intergranular pores; the corresponding pore type is VII when the pore type is 40% cracks and 60% intergranular pores; the corresponding pore type is IX when the pore type is 60% cracks and 40% intergranular pores; the corresponding pore type is X when the pore type is 80% cracks and 20% intergranular pores; the corresponding pore type is XI when the pore type is all cracks. According to the classification, the square of the difference between the P-wave velocity of the rock and the P-wave velocity of each pore type is calculated level by level, and the formula is as follows:

[0133] E i =(Y sample -Y i ) 2 , i∈(Ⅰ,Ⅱ,Ⅲ,Ⅳ,Ⅴ,Ⅵ,Ⅶ,Ⅷ,Ⅸ,Ⅹ,Ⅺ)

[0134] According to the above formula, the square value E of the difference in all 11 arrays is i For comparison, take E i The i value corresponding to the minimum case can be used to obtain the pore structure corresponding to the i value, and the pore type of the rock can be obtained, thereby determining the volume percentage and pore aspect ratio corresponding to different pore types.

[0135] S2d obtains the volume percentage and pore aspect ratio corresponding to different pore types according to the pore type;

[0136] S2e. Determining the porosity of the pores based on the volume percentage of each pore type, wherein:

[0137] Total porosity = effective porosity + clay porosity;

[0138] Effective porosity = matrix porosity + fracture porosity + solution pore porosity;

[0139] Matrix effective porosity = total porosity * mud volume fraction;

[0140] Fracture effective porosity = total porosity * fracture volume component;

[0141] Effective porosity of dissolved pores = total porosity * dissolved pore volume.

[0142] S3. Building a dry rock skeleton model

[0143] Apply the Xu-Payne model and adopt the differential equivalent medium model to iterate multiple times, and add the pores obtained in step S2 to the rock matrix in step S1. The operation steps are as follows: Figure 4 As shown in Figure 3, a dry rock skeleton model is established, and the bulk modulus and shear modulus of the dry rock skeleton are obtained.

[0144] S4. Establishing a carbonate rock physics model

[0145] Based on the equivalent mineral modulus of carbonate rock, the bulk modulus and shear modulus of the dry rock skeleton, the fluid mixture of carbonate rock is added to the dry rock skeleton obtained in step S3. Gassmann fluid is used to replace matrix pores, dissolved pores and cracks other than microcracks, and Brie model fluid is used to replace microcracks to obtain a carbonate rock physical model. The quantitative interpretation chart of the pore structure of the carbonate reservoir is shown in Figure 2. Figure 5 As shown by Figure 5 It can be seen that the method of the present invention can obtain the relationship between P-wave impedance, P-wave velocity ratio, pore type and pore structure, among which P-wave impedance is positively correlated with porosity, and the P-wave velocity ratio of fractured pores is relatively higher, which indicates that shear waves are more easily affected by cracks than hard pores; cracks in muddy formations are more developed, and matrix pores and solution pores contribute the most to the oil and gas content of the reservoir.

[0146] Effect verification

[0147] 1) Verification of fluid replacement effect

[0148] Experimental group 1: Gassmann fluid was used to replace all fractures. The experimental results are as follows: Figure 6 As shown in a;

[0149] Experimental group 2: Gassmann fluid was used to replace all cracks except microcracks, and Brie model fluid was used to replace microcracks. The experimental results are shown in Figure 2. Figure 6 As shown in b;

[0150] Depend on Figure 6 a and Figure 6 As can be seen from Figure 2, the measured P-wave velocity of experimental group 2 has a better fit with the fitted P-wave velocity, indicating that the method of using Gassmann fluid replacement for fractures other than microfractures and Brie model fluid replacement for microfractures in the present invention is more consistent with the actual carbonate rock physics model.

[0151] 2) Verification of the prediction effect of carbonate rock pore structure

[0152] In the case of limestone as the main lithology, different pore types interpreted from three sections of imaging logging of the well were selected, such as Figure 7 As shown in a, the predicted pore structure was tested, and the test results are shown in Figure 7 As shown in Figure (b), at a total porosity of 5% and a P-wave velocity of 4500 m / s, the predicted porosity consists of 60% fractures and 40% matrix pores. At a total porosity of 10% and a P-wave velocity of 5400 m / s, the predicted porosity consists of 20% dissolved pores and 80% matrix pores. At a total porosity of 15% and a P-wave velocity of 5380 m / s, the predicted porosity consists of 60% dissolved pores and 40% matrix pores. These test results are generally consistent with the imaging logging interpretation.

[0153] Example 2 Application of a Carbonate Rock Physics Modeling Method

[0154] Elastic curves bridge the gap between rock and seismic data. The purpose of rock physics modeling is to obtain rock elastic parameters, such as P-wave and S-wave velocities. Simulating P-wave and S-wave velocities under different conditions by varying rock composition or fluid properties allows analysis of the P-wave and S-wave velocity variations resulting from these changes, providing a reliable quantitative basis for parameter selection for subsequent reservoir characterization studies.

[0155] The specific steps for calculating the shear wave velocity and longitudinal wave velocity of the rock using the carbonate rock physics model are as follows:

[0156] Sa. Calculate the bulk modulus and shear modulus of the rock based on the carbonate rock physics model;

[0157] Sb based on the bulk modulus and shear modulus of the rock, the elastic response characteristics of the rock;

[0158] Sc. Determining the shear wave velocity and the longitudinal wave velocity of the carbonate rock based on the elastic response characteristics of the rock.

[0159] Effect verification

[0160] Compare the P-wave and S-wave velocities predicted by the modeling method of the present invention with the P-wave and S-wave velocities of the measured wells. Figure 8 As shown in Figure 2, it can be seen that the trends of the measured and predicted P- and S-wave velocity curves are completely consistent; Figure 9 is the error analysis of the predicted curve relative to the measured curve, where Figure 9 a is the error of the longitudinal wave curve, Figure 9 b is the error of the shear wave curve. It can be seen that the errors of the shear wave velocity and longitudinal wave velocity predicted by the present invention are both within 10%. Taking the longitudinal wave velocity as an example, the error calculation formula is:

[0161] (σ|predicted Vp - measured Vp|≤ε, ε≤10%)

[0162] In the above formula, K is the bulk modulus, dimensionless; μ is the shear modulus, dimensionless; ρ is the density, unit is g / cm 3 ; Vp is the longitudinal wave velocity, unit is m / s.

[0163] Example 3 A rock physics modeling device for carbonate rocks

[0164] Figure 10 A flow chart of a carbonate rock physics modeling device according to one embodiment of the present invention is shown. The carbonate rock physics modeling device includes:

[0165] Rock information acquisition unit 1: used to obtain the mineral components of the carbonate rock matrix and the volume content of each component, and calculate the equivalent mineral modulus and total porosity of the carbonate rock;

[0166] Pore ​​type determination unit 2: used to determine the pore type and pore parameters of various pores based on the pore quantitative interpretation template;

[0167] Dry rock skeleton model building unit 3: used to add various pores into the carbonate rock matrix to build a dry rock skeleton model;

[0168] Carbonate rock physical model building unit 4: used for adding the fluid mixture of carbonate rock into the dry rock skeleton model to obtain the carbonate rock physical model.

[0169] Example 4: A computer device

[0170] This embodiment provides a computer device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor to implement the above-mentioned carbonate rock physical modeling.

[0171] The memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), a hard disk, flash memory, etc.

[0172] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. The processor is configured to execute the computer-readable instructions stored in the memory.

[0173] Those skilled in the art should understand that in order to solve the technical problem of how to obtain a good user experience, this embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the scope of protection of this disclosure.

[0174] For detailed description of this embodiment, please refer to the corresponding description in the aforementioned embodiments, which will not be repeated here.

[0175] Example 5 A computer-readable storage medium

[0176] This embodiment provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the carbonate rock physical modeling is implemented.

[0177] The computer-readable storage medium stores non-transitory computer-readable instructions, which, when executed by a processor, execute all or part of the steps of the aforementioned methods.

[0178] The above-mentioned computer-readable storage media include, but are not limited to, optical storage media (e.g., CD-ROMs and DVDs), magneto-optical storage media (e.g., MOs), magnetic storage media (e.g., magnetic tapes or mobile hard disks), media with built-in rewritable non-volatile memory (e.g., memory cards), and media with built-in ROM (e.g., ROM cartridges).

[0179] It should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art may still modify the technical solutions described in the above embodiments or replace some of the technical features therein with equivalents. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A carbonate rock physical modeling method, characterized in that: The process includes the following steps: S1. Obtain the mineral components of the carbonate rock matrix and the volume content of each component, and calculate the equivalent mineral modulus and total porosity of the carbonate rock; S1a obtains the mineral composition of the carbonate rock matrix and the well logging curve, the well logging curve includes at least one of the compensated neutron logging curve, the acoustic wave time difference curve, the density curve and the gamma curve; S1b. Establishing a logging response equation by selecting a logging curve; S1c. Calculating the volume content of each of the mineral components by the logging response equation; S1d. Calculate the bulk modulus and shear modulus of the mixed mineral components using a preset rock modulus model; S1e. Determine the equivalent mineral modulus and total porosity of carbonate rocks from the bulk modulus and shear modulus of mixed mineral components; S2. Using the mineral composition and total porosity of the carbonate rock matrix, a pore quantitative interpretation template is established with the P-wave velocity as the ordinate and the total porosity as the abscissa. The well logging curve is applied to the pore quantitative interpretation template to determine the pore type and pore parameters of each type of pore. The pore parameters include: porosity and pore aspect ratio; S2a. Construction of a quantitative pore interpretation template: Based on the preset porosity and initial pore aspect ratio of the rock matrix mineral components, the P-wave velocity of each pore type is calculated using the differential equivalent medium model. A quantitative pore interpretation template is established with the P-wave velocity as the ordinate and the total porosity as the abscissa. Among them, based on the different properties of carbonate rock matrix, the pore quantitative interpretation template is divided into limestone pore quantitative interpretation template and dolomite pore quantitative interpretation template; S2b. Applying well logging curves to the pore quantitative interpretation template: Given the total porosity and P-wave velocity of the rock, the well logging curves are superimposed on the pore quantitative interpretation template for comparative analysis. A computer algorithm automatically searches for the nearest pore quantitative interpretation template value to determine the pore structure. S2c. In the pore quantitative interpretation template, the P-wave velocity-total porosity equations corresponding to each pore type are hierarchically sorted, and the difference between the P-wave velocity of the rock and the P-wave velocity of each pore type is calculated step by step. The pore structure corresponding to the minimum square value of the difference is found to determine the pore type of the rock. S2d obtains the volume percentage and pore aspect ratio corresponding to different pore types according to the pore type; S2e based on the volume percentage of each pore type to determine the porosity of the pores; S3. Establish a dry rock skeleton model using the pore parameters of the carbonate rock matrix and various pore types; By using the differential equivalent medium model in multiple iterations, the pores obtained in step S2 are added to the rock matrix in step S1 to establish a dry rock skeleton model; S4. adding the fluid mixture to the dry rock skeleton model to establish a carbonate rock physics model; The fluid mixture of carbonate rock is added to the dry rock skeleton obtained in step S3 to obtain a carbonate rock physical model.

2. The carbonate rock physical modeling method according to claim 1, characterized in that: In step S4, the fluid mixture is added in the following manner: for matrix pores, solution pores and cracks other than microcracks, Gassmann fluid is used for replacement; for microcracks, Brie model fluid is used for replacement.

3. The carbonate rock physical modeling method according to claim 1, wherein: In step S1a, the logging curve is a compensated neutron logging curve or an acoustic time difference curve.

4. An application of the carbonate rock physical modeling method according to any one of claims 1 to 3, characterized in that: The carbonate rock physical model is used to calculate the shear wave velocity and the longitudinal wave velocity of the carbonate rock.

5. A carbonate rock physical modeling device according to any one of claims 1 to 3, characterized in that: include: Rock information acquisition unit: used to obtain the mineral components of the carbonate rock matrix and the volume content of each component, and calculate the equivalent mineral modulus and total porosity of the carbonate rock; Pore ​​type determination unit: used to determine the pore type and pore parameters of various pores based on the pore quantitative interpretation template; Dry rock skeleton model building unit: used to add various pores into the carbonate rock matrix to build a dry rock skeleton model; Carbonate rock physical model building unit: used to add the fluid mixture of carbonate rock to the dry rock skeleton model to obtain the carbonate rock physical model.

6. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the rock physical modeling method of carbonate rock according to any one of claims 1 to 3 is implemented.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program for executing the carbonate rock physical modeling method according to any one of claims 1 to 3.

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