Quantitative characterization method for equivalent pore structure parameters combining digital rock physics and theoretical rock physics

Abstract

The invention provides an equivalent pore structure parameter quantitative characterization method combining digital rock physics and theoretical rock physics, and relates to the technical field of rock physics, and the method specifically comprises the following steps: carrying out finite element statics simulation on a digital rock physics model, calculating elastic parameters of the digital rock physics model, and calculating the elastic parameters of the digital rock physics model; constructing a quantitative relation between rock microscopic attribute parameters and elastic parameters of the digital rock physical model; constructing a relationship between the equivalent pore structure parameters and the elastic parameters based on theoretical rock physics; and constructing a quantitative relationship between the equivalent pore structure parameters and the rock microscopic attribute parameters according to the relationship between the microscopic attribute parameters and the elastic parameters and the relationship between the equivalent pore structure parameters and the elastic parameters. According to the technical scheme, the problem that quantitative characterization of macroscopic equivalent pore structure parameters is difficult to achieve under the condition that rock micro-pore characteristics are considered in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of rock physics, and in particular to a quantitative characterization method for equivalent pore structure parameters combining digital rock physics and theoretical rock physics. Background Art

[0002] Pore ​​structure is an important controlling factor of reservoir elasticity and is crucial for accurately describing the oil and gas reservoir characteristics of the reservoir. Affected by geological processes such as sedimentation, diagenesis and tectonic processes, the pore structure of the reservoir is complex and changeable, which directly affects the elasticity of the reservoir and the migration and distribution of fluids. Therefore, quantitative characterization of pore structure is crucial for the detailed interpretation of the reservoir.

[0003] Rock physics, as a bridge between reservoir physical parameters and seismic elastic parameters, is an effective means to study reservoir seismic response characteristics. Theoretical rock physics methods have wide applicability and do not rely on specific experimental conditions or equipment. However, most theoretical rock physics methods start from physical models and idealize underground pores. They lack in-depth consideration of the geological significance of complex reservoir pore structures and have certain limitations. Digital rock physics methods, as a bridge between macroscopic rock physical parameters and microscopic pore characteristics, can intuitively and visually describe pore structures by digitizing complex core images.

[0004] At present, in the field of theoretical rock physics, the existing technology mainly uses the equivalent pore aspect ratio of the rock physics model to carry out research, but the equivalent pore aspect ratio is indirectly obtained through theoretical rock physics models such as differential equivalent medium theory, KT model, self-consistent model, etc., which has certain limitations. The use of theoretical rock physics models to characterize the elastic characteristics of reservoirs with different pore structure types still remains at the qualitative level. Digital rock physics methods have obvious advantages in the intuitive characterization and quantitative description of reservoir microscopic pore structure, but the existing technology mainly focuses on microscopic scale analysis, and few combine microscopic parameters characterizing rock pore structure with macroscopic parameters for more in-depth analysis.

[0005] In summary, we use theoretical rock physics methods to find an equivalent pore structure parameter that can directly characterize the combination of various pore types in the reservoir, combine digital rock physics methods to conduct in-depth analysis of the parameter, build the relationship between the parameter and the microstructure, use the equivalent pore structure parameter to quantitatively characterize the microscopic pore structure of the rock, and clarify its geological significance, laying a theoretical foundation for applying this parameter in seismic reservoir prediction.

[0006] Therefore, there is a need for a quantitative characterization method for equivalent pore structure parameters that can achieve quantitative characterization of macroscopic equivalent pore structure parameters while taking into account the microscopic pore characteristics of rocks. Summary of the invention

[0007] The main purpose of the present invention is to provide a method for quantitatively characterizing equivalent pore structure parameters by combining digital rock physics and theoretical rock physics, so as to solve the problem in the prior art that it is difficult to achieve quantitative characterization of macroscopic equivalent pore structure parameters while considering the microscopic pore characteristics of rocks.

[0008] To achieve the above object, the present invention provides a quantitative characterization method for equivalent pore structure parameters combining digital rock physics and theoretical rock physics, which specifically comprises the following steps:

[0009] S1, finite element statics simulation is performed on the digital rock physics model, the elastic parameters of the digital rock physics model are calculated, and the quantitative relationship between the rock microscopic property parameters and the elastic parameters of the digital rock physics model is constructed.

[0010] S2, construct the relationship between the equivalent pore structure parameter γ and the elastic parameters based on theoretical rock physics.

[0011] S3, based on the relationship between microscopic property parameters and elastic parameters, and the relationship between the equivalent pore structure parameter γ and elastic parameters, the quantitative relationship between the equivalent pore structure parameters and the rock microscopic property parameters is constructed.

[0012] Furthermore, step S1 specifically includes the following steps:

[0013] S1.1, perform morphological analysis on the digital rock physics model to extract pore geometric properties, including area, perimeter, pore aspect ratio, equivalent diameter, roundness, area envelope and eccentricity; perform statistical analysis on the extracted pore geometric properties to obtain the rock microscopic property parameters of the digital rock physics model, including equivalent pore aspect ratio, equivalent diameter, roundness, area envelope, eccentricity, pore specific surface area and fractal dimension.

[0014] S1.2, perform finite element static simulation on the digital rock physics model, calculate the elastic parameters of the digital rock physics model, and construct the quantitative relationship between the rock microscopic property parameters and the elastic parameters:

[0015]

[0016] V p =-0.001684×ED 2 +4.006×ED+3256;

[0017] V p =-1142×RD+7007;

[0018] V p =15270×SL-9482;

[0019] V p =-9.861×10 -8 ×e 22.98×EC +5736×e -0.03614×EC ;

[0020] V p = -73.25 × POA + 5858;

[0021] V p =-14830×FD+14730;

[0022] Among them, V p is the longitudinal wave velocity, EPAR is the equivalent pore aspect ratio, ED is the equivalent diameter, RD is the roundness, SL is the area envelope, EC is the eccentricity, POA is the pore specific surface area, and FD is the fractal dimension.

[0023] Furthermore, step S2 specifically includes the following steps:

[0024] S2.1, based on theoretical rock physics, introduces the equivalent pore structure parameter γ to characterize the pore structure in the rock, and obtains an improved dry rock approximate model:

[0025]

[0026] Among them, K d is the bulk modulus of dry rock, K m is the bulk modulus of the rock matrix, is the porosity of the rock.

[0027] S2.2, using the Gassmann equation, the calculation formula for the equivalent pore structure parameter γ is obtained:

[0028]

[0029] Among them, K sat is the bulk modulus of saturated rock, K m is the bulk modulus of the rock matrix, is the porosity of the rock, K f is the bulk modulus of the pore fluid, F K and f are intermediate variables, V p is the longitudinal wave velocity, V s is the shear wave velocity and ρ is the saturated rock density.

[0030] Furthermore, the quantitative relationship between the equivalent pore structure parameters constructed in step S3 and the rock microscopic property parameters is:

[0031] γ=5.646×e -3.783×EPAR +2.513×e 0.1549×EPAR ;

[0032] γ=5.34×10 -6 ×ED 2 -0.01284×ED+10.82;

[0033] γ=3.712×RD-1.327;

[0034] γ = -49.2 × SL + 51.84;

[0035] γ=2.878×e 0.1685×EC +2.008×10 -9 ×e 21.15×EC ;

[0036] γ = 0.2395 × POA + 2.399;

[0037] γ=48.48×FD-26.6.

[0038] The present invention has the following beneficial effects:

[0039] The present invention realizes the automatic extraction of rock microstructure parameters, the construction of digital rock physics models and the simulation of elastic characteristics. Through statistical analysis, finite element simulation and other steps, the quantitative relationship between the equivalent pore structure parameter γ and the rock microscopic property parameters can be constructed, and the quantitative characterization of the equivalent pore structure parameter γ can be realized, providing strong support for research in the fields of geology, petroleum engineering, mining engineering, etc. In addition, the present invention also has high accuracy and reliability, and can better reflect the real characteristics of the pores in the rock represented by the equivalent pore structure parameter γ. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the specific implementation of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the specific implementation or the prior art description. Obviously, the drawings described below are some implementations of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0041] Figure 1 A flow chart of a quantitative characterization method of equivalent pore structure parameters combining digital rock physics and theoretical rock physics of the present invention is shown.

[0042] Figure 2 The digital rock physics model constructed in the first embodiment of the present invention is shown.

[0043] Figure 3 shows the equivalent pore aspect ratio vs. V p relationship diagram.

[0044] Figure 4 shows the equivalent diameter and V p relationship diagram.

[0045] Figure 5 shows the circularity vs. V p relationship diagram.

[0046] Figure 6 shows the area envelope vs. V p relationship diagram.

[0047] Figure 7 shows the eccentricity and V p relationship diagram.

[0048] Figure 8 shows the pore surface area vs. V p relationship diagram.

[0049] Fig. 9 The fractal dimension and V p relationship diagram.

[0050] Fig.10 The equivalent pore structure parameter γ and V are shown p relationship diagram.

[0051] Fig.11 A plot of the relationship between the equivalent pore structure parameter γ and the equivalent pore aspect ratio is shown.

[0052] Fig.12 A plot of the relationship between the equivalent pore structure parameter γ and the equivalent diameter is shown.

[0053] Fig.13 A plot of the equivalent pore structure parameter γ versus circularity is shown.

[0054] Fig.14 The relationship between the equivalent pore structure parameter γ and the area envelope is shown.

[0055] Fig.15 The relationship between the equivalent pore structure parameter γ and the eccentricity is shown

[0056] Fig.16 The relationship between the equivalent pore structure parameter γ and the pore specific surface area is shown.

[0057] Fig.17 The relationship between the equivalent pore structure parameter γ and the fractal dimension is shown DETAILED DESCRIPTION

[0058] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] Embodiment 1

[0060] like Figure 1 A quantitative characterization method of equivalent pore structure parameters combining digital rock physics and theoretical rock physics is shown, which specifically includes the following steps:

[0061] S1, finite element statics simulation is performed on the digital rock physics model, the elastic parameters of the digital rock physics model are calculated, and the quantitative relationship between the rock microscopic property parameters and the elastic parameters of the digital rock physics model is constructed.

[0062] S2, construct the relationship between the equivalent pore structure parameter γ and the elastic parameters based on theoretical rock physics.

[0063] S3, based on the relationship between microscopic property parameters and elastic parameters, and the relationship between the equivalent pore structure parameter γ and elastic parameters, the quantitative relationship between the equivalent pore structure parameters and the rock microscopic property parameters is constructed.

[0064] Digital rock physics models with different pore structures of a certain porosity are constructed using digital core technology. In the digital rock physics model, different pore structures are characterized by pore aspect ratio; the pore aspect ratio increases from 0.1 to 1, with an interval of 0.025, and a total of 37 digital rock physics models. The black part represents the pores and the white part represents the rock skeleton. The constructed digital rock physics models are shown in Figure 2. Figure 2 Shown

[0065] Specifically, step S1 includes the following steps:

[0066] S1.1, perform morphological analysis on the digital rock physics model to extract pore geometric properties, including area, perimeter, pore aspect ratio, equivalent diameter, roundness, area envelope and eccentricity; perform statistical analysis on the extracted pore geometric properties to obtain the rock microscopic property parameters of the digital rock physics model, including equivalent pore aspect ratio, equivalent diameter, roundness, area envelope, eccentricity, pore specific surface area and fractal dimension.

[0067] The equivalent pore aspect ratio EPAR is defined as: the ratio of the short axis to the long axis of the pore, with a value range of 0 to 1. Its calculation expression is as follows:

[0068]

[0069] Among them, l a represents the pore minor axis length, l b Represents the length of the major axis of the pore.

[0070] The equivalent diameter ED is defined as the diameter of a circle with the same area as a given pore, and is calculated as follows:

[0071]

[0072] Where A is the pore area.

[0073] The roundness RD is a shape factor related to the pore perimeter P and the pore area A, and its calculation formula is as follows:

[0074]

[0075] Where P is the pore perimeter and A is the pore area.

[0076] The area envelope SL is defined as the ratio between the actual area of ​​the pore and the minimum convex hull that can completely surround the pore, that is, the ratio between the actual area and the area of ​​the convex polygon. The calculation formula is as follows:

[0077]

[0078] Where A0 is the pore area, A CH is the area of ​​the convex hull surrounding the hole.

[0079] The eccentricity EC is defined as the eccentricity of the ellipse with the same standard second-order central moment as the pore, which ranges from 0 to 1 and is calculated as follows:

[0080]

[0081] Among them, c represents the distance from the focus to the center of the ellipse, and a represents half of the major axis of the ellipse.

[0082] The pore surface area (POA) is defined as the ratio of the total pore area in the core image to the total perimeter surrounding the pores, and its calculation formula is as follows:

[0083]

[0084] Where P is the perimeter surrounding the pore, and A is the pore area in μm -1 .

[0085] The fractal dimension (FD) is the ratio of the logarithm of the pore perimeter to the logarithm of the pore area, and its calculation formula is:

[0086]

[0087] Where P is the perimeter surrounding the pore and A is the area of ​​the pore.

[0088] S1.2, perform finite element static simulation on the digital rock physics model, calculate the elastic parameters of the digital rock physics model, and construct the quantitative relationship between the rock microscopic property parameters and the elastic parameters:

[0089]

[0090] V p =-0.001684×ED 2 +4.006×ED+3256;

[0091] V p =-1142×RD+7007;

[0092] V p =15270×SL-9482;

[0093] V p =-9.861×10 -8 ×e 22.98×EC +5736×e -0.03614×EC ;

[0094] V p = -73.25 × POA + 5858;

[0095] V p =-14830×FD+14730;

[0096] Among them, V p is the longitudinal wave velocity, EPAR is the equivalent pore aspect ratio, ED is the equivalent diameter, RD is the roundness, SL is the area envelope, EC is the eccentricity, POA is the pore specific surface area, and FD is the fractal dimension.

[0097] Figure 3-Figure 9 A graph showing the relationship between rock microscopic property parameters and elastic parameters, the elastic parameters including the longitudinal wave velocity.

[0098] Specifically, step S2 includes the following steps:

[0099] S2.1, based on theoretical rock physics, introduces the equivalent pore structure parameter γ to characterize the pore structure in the rock, and obtains an improved dry rock approximate model:

[0100]

[0101] Among them, K d is the bulk modulus of dry rock, K m is the bulk modulus of the rock matrix, is the porosity of the rock.

[0102] S2.2, using the Gassmann equation, the calculation formula for the equivalent pore structure parameter γ is obtained:

[0103]

[0104] Among them, K sat is the bulk modulus of saturated rock, K m is the bulk modulus of the rock matrix, is the porosity of the rock, K f is the bulk modulus of the pore fluid, F K and f are intermediate variables, V p is the longitudinal wave velocity, V s is the shear wave velocity and ρ is the saturated rock density.

[0105] Based on theoretical rock physics, the relationship between the equivalent pore structure parameter γ and the elastic parameters is constructed, such as Fig.10 shown.

[0106] Specifically, the quantitative relationship between the equivalent pore structure parameters and the rock microscopic property parameters constructed in step S3 is:

[0107] γ=5.646×e -3.783×EPAR +2.513×e 0.1549×EPAR ;

[0108] γ=5.34×10 -6 ×ED 2 -0.01284×ED+10.82;

[0109] γ=3.712×RD-1.327;

[0110] γ = -49.2 × SL + 51.84;

[0111] γ=2.878×e 0.1685×EC +2.008×10 -9 ×e 21.15×EC ;

[0112] β = 0.2395 × POA + 2.399;

[0113] β = 48.48 × FD - 26.6.

[0114] Figure 11-Figure 17 The relationship between the equivalent pore structure parameter γ and the rock microscopic property parameters is shown.

[0115] Embodiment 2

[0116] The present invention provides a quantitative characterization system for equivalent pore structure parameters of combined digital rock physics and theoretical rock physics. The quantitative characterization method for equivalent pore structure parameters of combined digital rock physics and theoretical rock physics provided in Embodiment 1 of the present invention is applied to the quantitative characterization system for equivalent pore structure parameters of combined digital rock physics and theoretical rock physics.

[0117] The system provided by the present invention is based on computer image processing technology and numerical simulation technology, and adopts modular design, including a pore identification module, a rock microscopic property parameter calculation module, a finite element numerical simulation calculation module and a result output module. The modules communicate with each other through a data interface and collaboratively complete the quantitative characterization of the equivalent pore structure parameter β.

[0118] Pore ​​Identification Module: This module accurately extracts the geometric properties of pores based on the constructed digital rock physics model.

[0119] Rock microscopic property parameter calculation module: This module calculates the rock microscopic property parameters in the digital rock physical model based on the pore geometric properties extracted from the digital rock physical model, including equivalent pore aspect ratio, equivalent diameter, roundness, area envelope, eccentricity, pore specific surface area and fractal dimension. This module uses statistical analysis methods to deeply explore the pore properties and obtain detailed parameters of the pore structure of the digital rock physical model.

[0120] Finite element numerical simulation calculation module: This module calculates the elastic parameters (P-wave velocity, S-wave velocity, etc.) of the digital rock physics model based on the finite element method, the size of the digital rock physics model, the bulk modulus of the rock matrix and fluid, the shear modulus and other parameter information.

[0121] Result output module: Output the calculated parameters in a visual form and provide data export function. This module supports multiple data formats for output, which is convenient for users to conduct further data analysis and processing.

[0122] Embodiment 3

[0123] The present invention provides a quantitative characterization device for equivalent pore structure parameters combining digital rock physics and theoretical rock physics, supporting the system provided by the present invention, and the device includes:

[0124] Computer: runs the system provided by the present invention to complete image processing and parameter calculation tasks;

[0125] Display: used to display the operation interface of this system and visualize the results;

[0126] Data storage device: used to store microscopic images and calculated parameter data.

[0127] Embodiment 4

[0128] The present invention provides a storage medium for quantitative characterization of equivalent pore structure parameters combining digital rock physics and theoretical rock physics, which is a computer-readable memory, such as a solid state drive (SSD), a read-only memory (ROM) or a random access memory (RAM). These storage media can be used to store the program code, microscopic image data and calculated parameter data of the system. By deploying the system on a computer and using appropriate storage media to store and read data, the various functions of the present invention can be realized.

[0129] Of course, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by technicians in this technical field within the essential scope of the present invention should also fall within the protection scope of the present invention.

Claims

1. A quantitative characterization method for equivalent pore structure parameters combining digital rock physics and theoretical rock physics, characterized in that: The specific steps include: S1, perform finite element static simulation on the digital rock physics model, calculate the elastic parameters of the digital rock physics model, and construct the quantitative relationship between the rock microscopic property parameters and the elastic parameters of the digital rock physics model; S2, construct the relationship between the equivalent pore structure parameter γ and the elastic parameters based on theoretical rock physics; S3, based on the relationship between microscopic property parameters and elastic parameters, and the relationship between the equivalent pore structure parameter γ and elastic parameters, the quantitative relationship between the equivalent pore structure parameters and the rock microscopic property parameters is constructed.

2. The quantitative characterization method of equivalent pore structure parameters combining digital rock physics and theoretical rock physics according to claim 1 is characterized in that: Step S1 specifically includes the following steps: S1.1, perform morphological analysis on the digital rock physics model to extract pore geometric properties, including area, perimeter, pore aspect ratio, equivalent diameter, roundness, area envelope and eccentricity; perform statistical analysis on the extracted pore geometric properties to obtain rock microscopic property parameters of the digital rock physics model, including equivalent pore aspect ratio, equivalent diameter, roundness, area envelope, eccentricity, pore specific surface area and fractal dimension; S1.2, perform finite element static simulation on the digital rock physics model, calculate the elastic parameters of the digital rock physics model, and construct the quantitative relationship between the rock microscopic property parameters and the elastic parameters: In p =5682×e (4.048×10-5)×EPAR -1667×e -4.428×EPAR ; In p =-0.001684×ED 2 +4.006×ED+3256; In p =-1142×RD+7007; In p =15270×SL-9482; In p =-9.861×10 -8 ×e 22.98×EC +5736×e -0.03614×EC ; In p =-73.25×POA+5858; In p =-14830×FD+14730; Among them, V p is the longitudinal wave velocity, EPAR is the equivalent pore aspect ratio, ED is the equivalent diameter, RD is the roundness, SL is the area envelope, EC is the eccentricity, POA is the pore specific surface area, and FD is the fractal dimension.

3. The quantitative characterization method of equivalent pore structure parameters combining digital rock physics and theoretical rock physics according to claim 1 is characterized in that: Step S2 specifically includes the following steps: S2.1, based on theoretical rock physics, introduces the equivalent pore structure parameter γ to characterize the pore structure in the rock, and obtains an improved dry rock approximate model: Among them, K d is the bulk modulus of dry rock, K m is the bulk modulus of the rock matrix, is the porosity of the rock; S2.2, using the Gassmann equation, the calculation formula for the equivalent pore structure parameter γ is obtained: Among them, K sat is the bulk modulus of saturated rock, K m is the bulk modulus of the rock matrix, is the porosity of the rock, K f is the bulk modulus of the pore fluid, F K and f are intermediate variables, V p is the longitudinal wave velocity, V s is the shear wave velocity and ρ is the saturated rock density.

4. The quantitative characterization method of equivalent pore structure parameters combining digital rock physics and theoretical rock physics according to claim 1 is characterized in that: The quantitative relationship between the equivalent pore structure parameters and rock microscopic property parameters constructed in step S3 is: γ=5.646×e -3.783×EPAR +2.513×e 0.2549×EPAR ; γ=5.34×10 -6 ×ED 2 -0.01284×ED+10.82; γ=3.712×RD-1.327; γ = -49.2 × SL + 51.84; γ=2.878×e 0.1685×EC +2.008×10 -9 ×e 21.15×EC ; γ = 0.2395 × POA + 2.399; γ=48.48×FD-26.6.

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