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

Abstract

The invention discloses a carbonate rock physical modeling method, application, a device, equipment and a medium, and belongs to the field of geophysical exploration. The modeling method comprises the following steps: establishing a pore quantitative interpretation template through logging data, determining pore types and pore parameters of various pores, adding the pores into a rock matrix to obtain a dry rock skeleton model, adding a fluid mixture into the dry rock skeleton model, and establishing a carbonate rock physical model; estimating the longitudinal and transverse wave velocities of the rock by using the rock physical model; the invention further provides a device for implementing the method, computer equipment and a computer readable storage medium. According to the method, the problem that the difference of estimation results by using a conventional rock physical model is large due to a carbonate rock multi-pore structure is solved, and meanwhile, the transverse wave estimation information can be quickly and accurately obtained by using the carbonate rock physical model. The method can be applied to rock physical modeling and pre-stack inversion technologies of carbonate rocks.

Description

Technical Field

[0001] The 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] The rock physics model is a bridge between reservoir parameters and seismic attributes. The establishment of the rock physics model can provide a theoretical basis for the classification of lithology and the detection of oil and gas. Permeability is one of the key factors affecting oil and gas accumulation. Therefore, predicting the pore structure of the rock model is crucial for identifying the pore structure development area that is conducive to accumulation, and then finding high-quality reservoirs with high porosity and permeability and high oil and gas saturation.

[0003] Carbonate rocks have a complex sedimentary environment, and are affected by multiple factors such as weathering, leaching, and tectonic transformation, resulting in a variety of pore types, strong heterogeneity, and large differences between different pore structures. Conventional rock physics modeling techniques are mostly used to predict the total porosity of rocks, and it is difficult to further subdivide the effective porosity of various pores. Therefore, it is difficult to accurately establish the pore structure of carbonate rocks through 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. In actual production, due to high cost constraints, S-wave information is difficult to obtain, so S-wave estimation has always been a widely discussed issue.

[0004] In summary, in view of the characteristics of multiple pore development in carbonate rocks, there is an urgent need in production for 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 the rock physics model for shear wave estimation. Summary of the invention

[0005] In order to solve the above deficiencies in the prior art, one purpose of the present invention is to provide a carbonate rock physical modeling method based on the characteristics of multiple pores of carbonate rocks, and an application for obtaining longitudinal and transverse wave data; another purpose 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 purpose, the technical solution adopted by the present invention is 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 components and total porosity of the carbonate rock matrix, a pore quantitative interpretation template is established with the longitudinal wave velocity as the ordinate and the total porosity as the abscissa, and the logging curve is applied to the pore quantitative interpretation template to determine the pore type and pore parameters of various pores, wherein the pore quantitative interpretation template is divided into a limestone pore quantitative interpretation template and a dolomite pore quantitative interpretation template, and 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 pores;

[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. The pore types include matrix pores, dissolved pores and fractures, and the pore parameters include porosity and pore aspect ratio.

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

[0014] Among them, 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 limit 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 components. Limestone is mainly composed of calcite and 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 component is calcite, and the dolomite pore quantitative interpretation template is suitable for areas where the carbonate rock mineral component 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% cracks 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% crack, 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% cracks 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% crack, 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 ordinate 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. Apply the well logging curve to the pore quantitative interpretation template: When the total porosity and P-wave velocity of the rock are known, the well logging curve is superimposed on the pore quantitative interpretation template for comparative analysis. Through computer algorithms, the nearest pore quantitative interpretation template value is automatically searched 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 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 the smallest is found to obtain the pore type of the rock;

[0047] S2d. The volume percentage and pore aspect ratio corresponding to different pore types are obtained according to the pore type;

[0048] 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% 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 pore types that are all matrix pores correspond to Level V; the pore types that are all matrix pores correspond to Level VI; the pore types that are 20% cracks and 80% matrix pores correspond to Level VII; the pore types that are 40% cracks and 60% matrix pores correspond to Level VIII; the pore types that are 60% cracks and 40% matrix pores correspond to Level IX; the pore types that are 80% cracks and 20% matrix pores correspond to Level X; and the pore types that are all cracks correspond to Level XI.

[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, and 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 the 11 arrays are compared, and the i value corresponding to the smallest Ei is taken to obtain the pore structure corresponding to the i value, and the pore type of the rock can be obtained, and then the volume percentage and pore aspect ratio corresponding to different pore types can be 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 components and logging curves of carbonate rocks based on the external data system, wherein the 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 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 to obtain a carbonate rock rock physics model.

[0069] Furthermore, in step S4,

[0070] In view of the complex pore structure of carbonate rocks, in order to ensure the accuracy of fluid replacement results, it is necessary to pay attention to the impact of microcracks on Gassmann fluid replacement in carbonate rocks. Because microcracks are extremely small in size and have very low local permeability, they limit or slow down the relaxation of pore fluid pressure. Fluids are often trapped in these microcracks and cannot flow, resulting in the predicted speed of Gassmann fluid replacement being lower than the actual measurement. Therefore, the fluid mixture is added in the following way: Gassmann fluid replacement is used for matrix pores, solution pores and cracks other than microcracks, and Brie model fluid replacement is used for microcracks.

[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 the application are:

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

[0074] Sb. Based on the bulk modulus and shear modulus of the rock, the elastic response characteristics of the rock are obtained;

[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, characterized in that it comprises:

[0077] Rock information acquisition unit: used to obtain the mineral components of carbonate rock matrix and the volume content of each component, and calculate the equivalent mineral modulus and total porosity of 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 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 into 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 the processor implements any of the above-mentioned carbonate rock physical modeling methods when executing the computer program.

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

[0083] The principle of the present invention is:

[0084] Classical rock physics models establish the relationship between rock-forming minerals, rock skeletons, porosity and pore fluids. In rock physics modeling of carbonate reservoirs, rocks can be simplified into two-phase media, one of which is the rock skeleton, which is composed of a single or combined mineral; the other phase is the pore fluid in the rock skeleton, which is composed of liquid or gas. In terms of the mineral components of the rock skeleton, the calculation method of mineral content is mainly the optimization logging interpretation; in terms of rock structure, the theoretical models involved are roughly divided into three categories: the porous medium volume average theory is used for the properties of minerals, such as the Wood equation and the Wyllie time average equation; the adaptive theory is used for the influence of spherical pores, ellipsoidal pores and cracks inside the rock on the rock properties, such as the Gassmann model; the elastic contact theory is used for the contact relationship of rock particles, such as the Hertz contact theory. The present invention is mainly based on the above theory, and establishes a carbonate rock physics model on the basis of clarifying the rock pore type and pore parameters and the 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 is based on the structural characteristics of multiple pores in carbonate rocks. It only needs to obtain conventional logging curve data and clearly define the proportion of the main rock matrix components to quickly build a carbonate rock physical model.

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

[0088] (3) The quantitative porosity interpretation template 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, three sections of different pore types interpreted by imaging logging were selected, and the program was applied for testing. When the total porosity was 5% and the longitudinal wave velocity was 4500 m / s, the predicted porosity contained 60% fractures and 40% matrix pores; when the total porosity was 10% and the longitudinal wave velocity was 5400 m / s, the predicted porosity contained 20% dissolved pores and 80% matrix pores; when the total porosity was 15% and the longitudinal wave velocity was 5380 m / s, the predicted porosity 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 the P- and S-wave estimation results. Since it integrates the calculation formulas corresponding to a variety of different lithology ratios, it has universal applicability for the S-wave estimation of carbonate rocks under multiple medium geological conditions. The correlation between the prediction results and the measured S-waves reaches more than 90%, which has high reliability 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 realize the construction of a carbonate rock physical model. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

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

[0095] Figure 3 is a shape division diagram of different pore types in Example 1, wherein: Figure 3 a is the solution pore, Figure 3 b is the matrix pore, Figure 3 c is 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 diagram for verifying the fluid replacement effect in Example 1, wherein: Figure 6 a is the cross-plot of all fractures replaced by Gassmann fluid. Figure 6 b is the cross-plot of the macropores using Gassmann fluid replacement and the microcracks using the equivalent medium model;

[0099] Figure 7 This is a graph 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 velocity curves and S-wave velocity curves predicted in Example 2 and the P-wave velocity curves of the measured wells;

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

[0102] Fig.10 This is a flow chart of the carbonate rock physical model device in Example 2, wherein: 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 is 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 used 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 usually carried out under conventional conditions or under conditions recommended by the manufacturer.

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

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

[0107] First, a well with carbonate rock matrix was selected and determined, and the logging data of the well was actually tested for subsequent use. Since the sound waves are affected by the physical properties of the rock and the pore fluid, in order to ensure that the model is closer to the real rock characteristics and reduce the errors caused by various factors, the original pore fluid was replaced with a single fluid environment saturated with salt water before this study. After obtaining the bulk modulus and shear modulus corresponding to the dry rock skeleton, the original pore fluid was replaced again to simulate the shear wave velocity under real 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.Since carbonate rocks are often mixed with quartz and clay minerals, they need to be studied as optional mineral components in the modeling process. Use in volume interpretation model: V 0 Represents the volume content of pores, V 1 V2 represents the volume content of calcite, V3 represents the volume content of dolomite, V4 represents the volume content of feldspar, and V5 represents the volume content of clay minerals.

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

[0111] S1b. Establish appropriate logging response equations by selecting the above four logging curves. The principle of multivariate fitting optimization calculation method is based on the fact that multiple basic logging curves can reflect the lithology, physical properties, electrical properties and oil and gas content of the reservoir. With reservoir parameters and mineral relative volume as independent variables, matrix joint solution of each logging response equation is performed. According to the principle of nonlinear weighted least squares method and error theory, the reservoir parameters and mineral relative content of the actual formation are calculated, that is, the optimized logging interpretation result.

[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 embodiment are shown in Table 1.

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

[0115]

[0116] The present invention uses the rock volume component and reservoir parameter optimization interpretation algorithm, and solves according to 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, and 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=AC 0 *V 0 +AC 1 *V 1 +AC 2 *V 2 +AC 3 *V 3 +AC 4 *V 4 +AC 5 *V 5 +Err1

[0118] DEN=DEN 0 *V 0 +DEN 1 *V 1 +DEN 2 *V 2 +DEN 3 *V 3 +DEN 4 *V 4 +DEN 5 *V 5 +Err2

[0119] NPHI=NPHI 0 *V 0 +NPHI 1 *V 1 +NPHI 2 *V 2 +NPHI 3 *V 3 +NPHI 4 *V 4 +NPHI 5 *V 5 +Err3

[0120] GR=GR 0 *V 0 +GR 1 *V 1 +GR 2 *V2 +GR 3 *V 3 +GR 4 *V 4 +GR 5 *V 5 +Err4

[0121] V 0 +V 1 +V 2 +V 3 +V 4 +V 5 =1

[0122] Where: AC 0 , AC 1 , AC 2 , AC 3 , AC 4 , AC 5 The sound wave time difference of the above six components, DEN 0 、DEN 1 、DEN 2 、DEN 3 、DEN 4 、DEN 5 They are the densities of the above six components, NPHI 0 NPHI 1 NPHI 2 NPHI 3 NPHI 4 NPHI 5 are the compensated neutron porosities of the above six components, GR 0 , GR 1 , GR 2 , GR 3 , GR 4 , GR 5 are the gamma values ​​of the above six components, V 0 、V 1 、V 2 、V 3 、V 4 、V 5 are the volume contents of each component respectively. 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 template for quantitative interpretation of pores and determine the pore types and pore parameters of various pores:

[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, where the pore types include: matrix pores, dissolved pores and fractures. 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 "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, and the aspect ratio of the interparticle pores "α inter ”Mostly between 0.08 and 0.15.

[0128] In order to construct the interpretation volume version, 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 under the condition of clear rock matrix components, and then obtain the volume component and aspect ratio corresponding to different pore combinations. Under the condition of specific carbonate matrix components, the corresponding relationship between different P-wave velocities, total porosity, pore structure and pore aspect ratio is shown in S2a in the invention content;

[0129] S2b. Apply the well logging curve to the pore quantitative interpretation template: When the total porosity and P-wave velocity of the rock are known, the well logging curve is superimposed on the pore quantitative interpretation template for comparative analysis. Through computer algorithms, the nearest pore quantitative interpretation template value is automatically searched 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 ranked and sorted, and the vertical coordinate distance between the input curve sample point and the preset nonlinear equation representing each pore structure is used to represent 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 calculate the difference between the P-wave velocity of the rock and the P-wave velocity of each pore type step by step, find the pore structure corresponding to the case where the square value of the difference is the smallest, and obtain the pore type of the rock;

[0131] In the device, the main type of carbonate rock (limestone / dolomite) is first determined, and then the data of the sonic curve and the total porosity curve are loaded into the corresponding worksheet. The principle and method of applying the program to determine the volume component and aspect ratio of the pores 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 % of intergranular pores correspond to level V; all pore types are intergranular pores, corresponding to level VI; pore types are 20% cracks and 80% intergranular pores, corresponding to level VII; pore types are 40% cracks and 60% intergranular pores, corresponding to level VIII; pore types are 60% cracks and 40% intergranular pores, corresponding to level IX; pore types are 80% cracks and 20% intergranular pores, corresponding to level X; pore types are all cracks, corresponding to level XI. According to the classification, the square of the difference between the longitudinal wave velocity of the rock and the longitudinal 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 obtain the pore structure corresponding to the i value, and the pore type of the rock can be obtained, and then the volume percentage and pore aspect ratio corresponding to different pore types can be determined.

[0135] S2d. The volume percentage and pore aspect ratio corresponding to different pore types are obtained 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 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 fraction.

[0142] S3. Building a dry rock skeleton model

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

[0144] S4. Establishment of carbonate rock physics model

[0145] Based on the equivalent mineral modulus of carbonate rock, the bulk modulus and shear modulus of dry rock skeleton, the fluid mixture of carbonate rock is added to the dry rock skeleton obtained in step S3, and Gassmann fluid is used for matrix pores, dissolved pores and cracks other than microcracks, and Brie model fluid is used for microcracks to obtain a carbonate rock physical model. The quantitative interpretation chart of the pore structure of the carbonate reservoir is shown in 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 and 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 6 As shown in b;

[0150] Depend on Figure 6 a and Figure 6 b It can be seen that 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 using Brie model fluid replacement for microfractures is more in line 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, three sections of imaging logging interpretation of the well were selected to interpret different pore types, 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, when the total porosity is 5% and the P-wave velocity is 4500 m / s, the predicted porosity includes 60% fractures and 40% matrix pores; when the total porosity is 10% and the P-wave velocity is 5400 m / s, the predicted porosity includes 20% dissolved pores and 80% matrix pores; when the total porosity is 15% and the P-wave velocity is 5380 m / s, the predicted porosity includes 60% dissolved pores and 40% matrix pores. The test results are basically consistent with the imaging logging interpretation results.

[0153] Example 2 Application of a carbonate rock physics modeling method

[0154] Elastic curves are the bridge between rock and seismic data. The purpose of rock physics modeling is to obtain rock elastic parameters, such as P-wave velocity and S-wave velocity. At the same time, by changing the rock components or fluid properties, simulating the P-wave and S-wave velocities of rocks under different conditions, analyzing the P-wave and S-wave velocity variation characteristics brought about by these changes, and providing a reliable quantitative parameter selection basis for subsequent reservoir characteristic research.

[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. Calculating the bulk modulus and shear modulus of the rock based on the carbonate rock physical model;

[0157] Sb. Based on the bulk modulus and shear modulus of the rock, the elastic response characteristics of the rock are obtained;

[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] The P-wave and S-wave velocities predicted by the modeling method of the present invention are compared with the P-wave and S-wave velocities of the measured wells. Figure 8 As shown, it can be seen that the trends of the measured and predicted P- and S-wave velocity curves are completely consistent; Fig. 9 is the error analysis of the predicted curve relative to the measured curve, where: Fig. 9 a is the error of the longitudinal wave curve, Fig. 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] Fig.10 A flow chart of a carbonate rock physical modeling device according to an embodiment of the present invention is shown, the carbonate rock physical modeling device comprising:

[0165] Rock information acquisition unit 1: used to obtain the mineral components of carbonate rock matrix and the volume content of each component, and calculate the equivalent mineral modulus and total porosity of 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 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] Embodiment 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-temporary 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, for example, include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

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

[0173] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present 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 protection scope of the present disclosure.

[0174] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0175] Embodiment 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. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the above-mentioned methods of various embodiments are executed.

[0178] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0179] It should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention is described in detail with reference to the above embodiments, those skilled in the art can still modify the technical solutions described in the above embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope 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; S2. Using the mineral composition and total porosity of carbonate rock matrix, a pore quantitative interpretation template with P-wave velocity as the ordinate and total porosity as the abscissa is established. The logging curve is applied to the pore quantitative interpretation template to determine the pore type and pore parameters of various pores. The pore parameters include: porosity and pore aspect ratio; S3. Establish a dry rock skeleton model using the pore parameters of the carbonate rock matrix and various pores; S4. Add the fluid mixture to the dry rock skeleton model to establish a carbonate rock physics model.

2. The carbonate rock physical modeling method according to claim 1, characterized in that: The step S2 is: S2a. Construction of pore quantitative interpretation template: Based on the preset porosity and initial pore aspect ratio of the rock matrix mineral components, the differential equivalent medium model is used to calculate the P-wave velocity of each pore type, and a pore quantitative 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. Apply the well logging curve to the pore quantitative interpretation template: When the total porosity and P-wave velocity of the rock are known, the well logging curve is superimposed on the pore quantitative interpretation template for comparative analysis. Through computer algorithms, the nearest pore quantitative interpretation template value is automatically searched 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 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 the smallest is found to obtain the pore type of the rock; S2d. The volume percentage and pore aspect ratio corresponding to different pore types are obtained according to the pore type; S2e. Determine the porosity of the pores based on the volume percentage of each pore type.

3. The carbonate rock physical modeling method according to claim 1, characterized in that: The step S1 is: S1a. Obtaining mineral components and logging curves of carbonate rock matrix, wherein the logging curves include at least one of compensated neutron logging curves, acoustic time difference curves, density curves and gamma curves; 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; The step S3 is: By adopting the differential equivalent medium model in multiple iterations, each pore obtained in step S2 is added to the rock matrix in step S1 to establish a dry rock skeleton model; The step S4 is: The fluid mixture of carbonate rock is added to the dry rock skeleton obtained in step S3 to obtain a carbonate rock physical model.

4. The carbonate rock physical modeling method according to claim 1 or 3, 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.

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

6. An application of the carbonate rock physical modeling method according to any one of claims 1 to 5, 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.

7. A carbonate rock physical modeling device according to any one of claims 1 to 5, characterized in that: include: Rock information acquisition unit: used to obtain the mineral components of carbonate rock matrix and the volume content of each component, and calculate the equivalent mineral modulus and total porosity of 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 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 into the dry rock skeleton model to obtain the carbonate rock physical model.

8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the rock physics modeling method of carbonate rock described in any one of claims 1 to 5 is implemented.

9. 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 5.

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