Porous rock elasticity modulus prediction method and device, electronic equipment and medium

Abstract

The invention discloses a porous rock elastic modulus prediction method and device, electronic equipment and a medium. The method may include obtaining a bulk modulus and a shear modulus of a solid matrix of a rock sample; carrying out lossless scanning on the rock sample to obtain gray frequency distribution of a CT image, and obtaining quantitative parameters of the pore structure of the embedded body; measuring the porosity of the rock sample; according to the bulk modulus, the shear modulus, the quantitative parameters of the pore structure of the embedded body and the porosity, the effective elastic modulus is calculated through an equivalent embedded body stress average approximation method. On the basis of an equivalent insert stress average (EIAS) approximation method, interaction between inclusions of insert pores is represented in an incremental strain form, petrology and microstructure feature analysis is carried out at the same time, quantitative parameters are provided for visual background matrix minerals and insert pores, and the method has the advantages of being high in accuracy and high in accuracy. And the elastic characteristic of the porous rock under the complete communication of the pore fluid pressure is more accurately represented.

Description

Technical Field

[0001] The present invention relates to the field of rock physics research, and more specifically, to a method, device, electronic equipment and medium for predicting elastic modulus of porous rocks. Background Art

[0002] The elastic properties of porous rocks depend on their pore structure and the fluids they contain. Generally, the properties of each phase in the rock and the compositional relationship between the phases are expressed with the macroscopic physical properties of the underground rock by using rock physics theoretical models. Most of the existing rock physics theoretical models of porous rocks use the equivalent medium theory based on inclusions to characterize the influence of pore structure on elastic characteristics, approximating porous rocks as solid matrices composed of different mineral particles and embedded pores or cracks with a certain width-to-length ratio. Such models generally assume that the embedded bodies are isolated from each other and the fluids cannot flow into each other. However, changes in fluid pressure propagation can lead to huge changes in the effective elastic modulus of porous rocks.

[0003] There is still a need to develop a method to predict the elastic modulus of porous rocks that takes into account the pore structure and fluid.

[0004] The information disclosed in the background technology section of the present invention is only intended to deepen the understanding of the general background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0005] The present invention proposes a method, device, electronic equipment and medium for predicting the elastic modulus of porous rocks, which can simulate the elastic properties of porous rocks and provide basic support for complex reservoir prediction and fluid identification.

[0006] In a first aspect, an embodiment of the present disclosure provides a method for predicting elastic modulus of porous rocks, comprising:

[0007] Obtaining the bulk modulus and shear modulus of the solid matrix of the rock sample;

[0008] Performing nondestructive scanning on the rock sample to obtain grayscale frequency distribution of the CT image and quantitative parameters of the pore structure of the embedded body;

[0009] determining the porosity of the rock sample;

[0010] The effective elastic modulus is calculated according to the bulk modulus, the shear modulus, the quantitative parameter of the embedded body pore structure and the porosity by using an equivalent embedded body stress average approximation method.

[0011] As a specific implementation method of the embodiment of the present disclosure, the quantitative parameters of the embedded body pore structure include the pore morphology of the porous rock, the pore aspect ratio, the volume proportion of different types of pores, and the pore connectivity.

[0012] As a specific implementation of the embodiment of the present disclosure, calculating the effective elastic modulus by the equivalent embedded body stress average approximation method includes:

[0013] The interaction between the inclusions embedded in the background material having the bulk modulus and the shear modulus is characterized in the form of incremental strain by using the equivalent embedded body stress average approximation method, and the effective elastic modulus is calculated.

[0014] As a specific implementation of the embodiment of the present disclosure, the equivalent embedded body stress average approximation method includes the following steps:

[0015] Define representative volume elements and their volumes of porous rock and determine the applied incremental strain;

[0016] Under the condition that the fluid pressure between pores is completely communicated, the added incremental strain is substituted into the generalized expression of the effective elastic modulus to obtain the expression of the effective elastic modulus of porous rock.

[0017] As a specific implementation of the embodiment of the present disclosure, the applied incremental strain is:

[0018]

[0019]

[0020] Among them, <…> V represents the volume average of volume V, <f> V' =(1 / V')∫ V' f(x)dυ, is the pore volume in the representative volume unit RVE, that is and are the bulk dilatation and shear components expressed as incremental strains in a representative volume element, respectively.

[0021] As a specific implementation of the embodiment of the present disclosure, the applied incremental strain is substituted into the generalized expression of the effective elastic modulus to obtain:

[0022]

[0023]

[0024] in, P and Q are the inclusion geometry factors, is the probability density function describing the pore shape distribution, k f is the bulk modulus of the fluid.

[0025] As a specific implementation of the embodiment of the present disclosure, the expression of the effective elastic modulus of porous rock is:

[0026]

[0027]

[0028] In a second aspect, the embodiments of the present disclosure further provide a porous rock elastic modulus prediction device, comprising:

[0029] A sampling module to obtain the bulk modulus and shear modulus of the solid matrix of the rock sample;

[0030] A scanning module performs non-destructive scanning on the rock sample to obtain the grayscale frequency distribution of the CT image and obtain quantitative parameters of the pore structure of the embedded body;

[0031] A measuring module, for measuring the porosity of the rock sample;

[0032] A calculation module calculates the effective elastic modulus through an equivalent embedded body stress average approximation method according to the bulk modulus, the shear modulus, the quantitative parameter of the embedded body pore structure and the porosity.

[0033] As a specific implementation method of the embodiment of the present disclosure, the quantitative parameters of the embedded body pore structure include the pore morphology of the porous rock, the pore aspect ratio, the volume proportion of different types of pores, and the pore connectivity.

[0034] As a specific implementation of the embodiment of the present disclosure, calculating the effective elastic modulus by the equivalent embedded body stress average approximation method includes:

[0035] The interaction between the inclusions embedded in the background material having the bulk modulus and the shear modulus is characterized in the form of incremental strain by using the equivalent embedded body stress average approximation method, and the effective elastic modulus is calculated.

[0036] As a specific implementation of the embodiment of the present disclosure, the equivalent embedded body stress average approximation method includes the following steps:

[0037] Define representative volume elements of porous rock and their volumes, and determine the applied incremental strains;

[0038] Under the condition that the fluid pressure between pores is completely communicated, the added incremental strain is substituted into the generalized expression of the effective elastic modulus to obtain the expression of the effective elastic modulus of the porous rock.

[0039] As a specific implementation of the embodiment of the present disclosure, the applied incremental strain is:

[0040]

[0041]

[0042] Among them, <…> V represents the volume average of volume V, <f> V' =(1 / V')∫ V' f(x)dυ, is the pore volume in the representative volume unit RVE, that is and are the bulk dilatation and shear components expressed as incremental strains in a representative volume element, respectively.

[0043] As a specific implementation of the embodiment of the present disclosure, the applied incremental strain is substituted into the generalized expression of the effective elastic modulus to obtain:

[0044]

[0045]

[0046] in, P and Q are the inclusion geometry factors, is the probability density function describing the pore shape distribution, k f is the bulk modulus of the fluid.

[0047] As a specific implementation of the embodiment of the present disclosure, the expression of the effective elastic modulus of porous rock is:

[0048]

[0049]

[0050] In a third aspect, an embodiment of the present disclosure further provides an electronic device, the electronic device comprising:

[0051] A memory storing executable instructions;

[0052] A processor runs the executable instructions in the memory to implement the porous rock elastic modulus prediction method.

[0053] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the method for predicting the elastic modulus of porous rocks is implemented.

[0054] Its beneficial effects are:

[0055] The present invention is based on the equivalent embedded volume stress average (EIAS) approximation method, which characterizes the interaction between embedded inclusions in the form of incremental strain, and simultaneously carries out petrological and microstructural characteristic analysis to provide quantitative parameters for the background matrix minerals and embedded volume pore structure, and more accurately characterizes the elastic properties of porous rocks under complete communication of pore fluid pressure.

[0056] The methods and apparatus of the present invention have other features and advantages that will be apparent from, or will be described in detail in, the accompanying drawings and subsequent detailed descriptions incorporated herein, which together serve to explain the specific principles of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The above and other objects, features and advantages of the present invention will become more apparent through a more detailed description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present invention.

[0058] Figure 1 A flow chart showing the steps of a method for predicting elastic modulus of porous rock according to an embodiment of the present invention.

[0059] Figure 2 A schematic diagram showing a representative volume unit structure according to one embodiment of the present invention is shown.

[0060] Figure 3a , Figure 3b Schematic diagrams respectively show the estimation results of the bulk modulus and the shear modulus based on the equivalent medium theory of the inclusion according to an embodiment of the present invention.

[0061] Figure 4a , Figure 4b Schematic diagrams respectively show the estimation results of bulk modulus and shear modulus based on the equivalent embedded body stress average approximation method according to an embodiment of the present invention.

[0062] Figure 5 A block diagram of a porous rock elastic modulus prediction device according to an embodiment of the present invention is shown.

[0063] Description of reference numerals:

[0064] 201, sampling module; 202, scanning module; 203, measuring module; 204, calculating module. DETAILED DESCRIPTION

[0065] The preferred embodiments of the present invention will be described in more detail below. Although the preferred embodiments of the present invention are described below, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0066] To facilitate understanding of the solutions and effects of the embodiments of the present invention, four specific application examples are given below. Those skilled in the art should understand that the examples are only for facilitating understanding of the present invention, and any specific details thereof are not intended to limit the present invention in any way.

[0067] Example 1

[0068] Figure 1 A flow chart showing the steps of a method for predicting elastic modulus of porous rock according to an embodiment of the present invention.

[0069] like Figure 1 As shown, the method for predicting the elastic modulus of porous rocks includes: step 101, obtaining the bulk modulus and shear modulus of the solid matrix of the rock sample; step 102, performing non-destructive scanning on the rock sample, obtaining the grayscale frequency distribution of the CT image, and obtaining the quantitative parameters of the pore structure of the embedded body; step 103, determining the porosity of the rock sample; step 104, calculating the effective elastic modulus through the equivalent embedded body stress average approximation method according to the bulk modulus, shear modulus, the quantitative parameters of the pore structure of the embedded body and the porosity.

[0070] In one example, the quantitative parameters of the embedded pore structure include the pore morphology of the porous rock, the pore aspect ratio, the volume proportion of different types of pores, and the pore connectivity.

[0071] In one example, calculating the effective elastic modulus by the equivalent embedded body stress averaging approximation includes:

[0072] The interaction between inclusions embedded in a background material with bulk modulus and shear modulus is characterized in the form of incremental strain by using the equivalent embedded body stress average approximation method, and the effective elastic modulus is calculated.

[0073] In one example, the equivalent embedded body stress average approximation method includes the following steps:

[0074] Define representative volume elements and their volumes of porous rock and determine the applied incremental strain;

[0075] Under the condition that the fluid pressure between pores is completely communicated, the expression of the effective elastic modulus of porous rock is obtained by substituting the external incremental strain into the generalized expression of the effective elastic modulus.

[0076] In one example, the applied incremental strain is:

[0077]

[0078]

[0079] Among them, <…> V represents the volume average of volume V, <f> V' =(1 / V')∫ V' f(x)dυ, is the pore volume in the representative volume unit RVE, that is and are the bulk dilatation and shear components expressed as incremental strains in a representative volume element, respectively.

[0080] In one example, substituting the applied incremental strain into the generalized expression for the effective elastic modulus yields:

[0081]

[0082]

[0083] in, P and Q are the inclusion geometry factors, is the probability density function describing the pore shape distribution, k f is the bulk modulus of the fluid.

[0084] In one example, the expression for the effective elastic modulus of porous rock is:

[0085]

[0086]

[0087] Specifically, the drilled porous rock samples were processed into cylinders with a diameter of 25 mm and a length of 50 mm, and rock samples were selected near the drilling position of the cylindrical samples. The rock samples were crushed and sliced ​​according to the X-ray diffraction analysis method of clay minerals and common non-clay minerals in sedimentary rocks (SY / T 5163-2018), and the mineral composition and content were quantitatively analyzed. The bulk modulus k of the solid matrix was obtained by using the volume average method. m and shear modulus μ m .

[0088] The cylindrical samples were nondestructively scanned using an X-ray CT scanner. The different blocking effects of different minerals on X-rays were used to obtain the grayscale frequency distribution of the CT image, and the pore morphology, pore aspect ratio α, and volume proportion of different types of pores in porous rocks were quantitatively analyzed. Pore ​​connectivity, etc.

[0089] The prepared cylindrical sample is dried according to the core analysis method, and then the physical properties of the cylindrical sample are measured using a porosity and permeability meter to obtain the porosity φ of the cylindrical sample.

[0090] Based on the obtained quantitative parameters of the background matrix mineral composition and embedded pore structure of porous rocks, the equivalent embedded body stress average (EIAS) approximation method is used to characterize the stress distribution of embedded particles with elastic modulus k in the form of incremental strain. m and μ m Interactions between inclusions in the visual background material.

[0091] Figure 2 A schematic diagram showing a representative volume unit structure according to one embodiment of the present invention is shown.

[0092] The EIAS approximation defines a representative volume element (RVE) for porous rock, such as Figure 2 As shown, its volume is V, assuming an additional incremental strain is equal to the volume average of the incremental strain of the solid matrix:

[0093]

[0094]

[0095] Among them, <…> V The volume average value of volume V can be expressed as:

[0096] f> V' =(1 / V')∫ V' f(x)dυ

[0097] In the formula is the pore volume in the representative volume unit RVE, that is and are represented as the volume expansion and shear components of the incremental strain in RVE, respectively.

[0098] In the case of complete communication of fluid pressure between pores, the volume average is substituted into the generalized expression of effective elastic modulus:

[0099]

[0100]

[0101] in, P and Q are the inclusion geometry factors, is the probability density function describing the pore shape distribution, k f is the bulk modulus of the fluid.

[0102] The expression of the effective elastic modulus of porous rock is obtained as follows:

[0103]

[0104]

[0105] After obtaining the elastic modulus, elastic parameters such as elastic wave velocity and Lame coefficient of porous rock can be further calculated.

[0106] Example 2

[0107] The present invention also provides a porous rock elastic modulus prediction device, comprising:

[0108] A sampling module to obtain the bulk modulus and shear modulus of the solid matrix of the rock sample;

[0109] Scanning module, which performs non-destructive scanning on rock samples, obtains the grayscale frequency distribution of CT images, and obtains quantitative parameters of the pore structure of the embedded body;

[0110] Determination module, to determine the porosity of rock samples;

[0111] The calculation module calculates the effective elastic modulus based on the bulk modulus, shear modulus, quantitative parameters of the embedded pore structure and porosity through the equivalent embedded body stress average approximation method.

[0112] In one example, the quantitative parameters of the embedded pore structure include the pore morphology of the porous rock, the pore aspect ratio, the volume proportion of different types of pores, and the pore connectivity.

[0113] In one example, calculating the effective elastic modulus by the equivalent embedded body stress averaging approximation includes:

[0114] The interaction between inclusions embedded in a background material with bulk modulus and shear modulus is characterized in the form of incremental strain by using the equivalent embedded body stress average approximation method, and the effective elastic modulus is calculated.

[0115] In one example, the equivalent embedded body stress average approximation method includes the following steps:

[0116] Define representative volume elements of porous rock and their volumes, and determine the applied incremental strains;

[0117] Under the condition that the fluid pressure between pores is completely communicated, the expression of the effective elastic modulus of porous rock is obtained by substituting the external incremental strain into the generalized expression of the effective elastic modulus.

[0118] In one example, the applied incremental strain is:

[0119]

[0120]

[0121] Among them, <…> V represents the volume average of volume V, <f> V' =(1 / V')∫ V' f(x)dυ, is the pore volume in the representative volume unit RVE, that is and are the bulk dilatation and shear components expressed as incremental strains in a representative volume element, respectively.

[0122] In one example, substituting the applied incremental strain into the generalized expression for the effective elastic modulus yields:

[0123]

[0124]

[0125] in, P and Q are the inclusion geometry factors, is the probability density function describing the pore shape distribution, k f is the bulk modulus of the fluid.

[0126] In one example, the expression for the effective elastic modulus of porous rock is:

[0127]

[0128]

[0129] Specifically, the drilled porous rock samples were processed into cylinders with a diameter of 25 mm and a length of 50 mm, and rock samples were selected near the drilling position of the cylindrical samples. The rock samples were crushed and sliced ​​according to the X-ray diffraction analysis method of clay minerals and common non-clay minerals in sedimentary rocks (SY / T 5163-2018), and the mineral composition and content were quantitatively analyzed. The bulk modulus k of the solid matrix was obtained by using the volume average method. m and shear modulus μ m .

[0130] The cylindrical samples were nondestructively scanned using an X-ray CT scanner. The different blocking effects of different minerals on X-rays were used to obtain the grayscale frequency distribution of the CT image, and the pore morphology, pore aspect ratio α, and volume proportion of different types of pores in porous rocks were quantitatively analyzed. Pore ​​connectivity, etc.

[0131] The prepared cylindrical sample is dried according to the core analysis method, and then the physical properties of the cylindrical sample are measured using a porosity and permeability meter to obtain the porosity φ of the cylindrical sample.

[0132] Based on the obtained quantitative parameters of the background matrix mineral composition and embedded pore structure of porous rocks, the equivalent embedded body stress average (EIAS) approximation method is used to characterize the stress of embedded in the porous rock with elastic modulus k in the form of incremental strain. m and μ m Interactions between inclusions in the visual background material.

[0133] The EIAS approximation defines a representative volume element (RVE) for porous rock, such as Figure 2 As shown, its volume is V, assuming an additional incremental strain is equal to the volume average of the incremental strain of the solid matrix:

[0134]

[0135]

[0136] Among them, <…> V The volume average value of volume V can be expressed as:

[0137] <f> V' =(1 / V')∫ V' f(x)dυ

[0138] In the formula is the pore volume in the representative volume unit RVE, that is and are represented as the volume expansion and shear components of the incremental strain in RVE, respectively.

[0139] In the case of complete communication of fluid pressure between pores, the volume average is substituted into the generalized expression of effective elastic modulus:

[0140]

[0141]

[0142] in, P and Q are the inclusion geometry factors, is the probability density function describing the pore shape distribution, k f is the bulk modulus of the fluid.

[0143] The expression of the effective elastic modulus of porous rock is obtained as follows:

[0144]

[0145]

[0146] After obtaining the elastic modulus, elastic parameters such as elastic wave velocity and Lame coefficient of porous rock can be further calculated.

[0147] Example 3

[0148] Figure 3a , Figure 3b Schematic diagrams showing estimation results of bulk modulus and shear modulus based on the equivalent medium theory of inclusions according to an embodiment of the present invention are shown respectively, and the color scale represents the relative error between the actual elastic modulus and the predicted elastic modulus.

[0149] like Figure 3a , Figure 3b As shown in the figure, the relative errors of the bulk modulus and shear modulus predicted by this method are 11-20% and 9.2-21% respectively, and the errors between the predicted results and the actual data are large. This shows that the equivalent medium theory based on inclusions cannot accurately characterize the elastic characteristics of porous rocks because it does not consider the influence of pore fluid pressure interaction on the elastic properties of porous media.

[0150] Figure 4a , Figure 4b Schematic diagrams showing the estimation results of the bulk modulus and shear modulus based on the equivalent inclusion stress averaging approximation method according to an embodiment of the present invention, where the color scale represents the relative error between the actual elastic modulus and the predicted elastic modulus.

[0151] As Figure 4a , Figure 4b shown, the mineral composition, its content, physical properties, and pore structure parameters obtained from tests are introduced into the EIAS approximation, and the elastic modulus is predicted under the constraint of the quantitative parameters of the rock microstructure. The prediction results of the method proposed by the present invention are in good agreement with the measured data, and the relative errors of the bulk modulus and shear modulus are basically controlled within 8%. Thus, it can be seen that the influence of the pore fluid pressure interaction on the elastic properties of porous media cannot be ignored.

[0152] Example 4

[0153] Figure 5 Shows a block diagram of a porous rock elastic modulus prediction device according to an embodiment of the present invention.

[0154] As Figure 5 shown, the porous rock elastic modulus prediction device includes:

[0155] A sampling module 201 that obtains the bulk modulus and shear modulus of the solid matrix of the rock sample;

[0156] A scanning module 202 that performs non-destructive scanning on the rock sample to obtain the gray-scale frequency distribution of the CT image and obtain the quantitative parameters of the inclusion pore structure;

[0157] A determination module 203 that determines the porosity of the rock sample;

[0158] A calculation module 204 that calculates the effective elastic modulus according to the bulk modulus, shear modulus, quantitative parameters of the inclusion pore structure, and porosity through the equivalent inclusion stress averaging approximation method.

[0159] As an optional solution, the quantitative parameters of the inclusion pore structure include the pore morphology, pore aspect ratio, volume fraction of different types of pores, and pore connectivity of the porous rock.

[0160] As an optional solution, calculating the effective elastic modulus through the equivalent inclusion stress averaging approximation method includes:

[0161] Through the equivalent inclusion stress averaging approximation method, the interaction between inclusions embedded in the apparent background material with the bulk modulus and shear modulus is characterized in the form of incremental strain, and the effective elastic modulus is calculated.

[0162] As an optional solution, the equivalent inclusion stress averaging approximation method includes the following steps:

[0163] Define representative volume elements of porous rock and their volumes, and determine the applied incremental strains;

[0164] Under the condition that the fluid pressure between pores is completely communicated, the expression of the effective elastic modulus of porous rock is obtained by substituting the external incremental strain into the generalized expression of the effective elastic modulus.

[0165] As an option, the applied incremental strain is:

[0166]

[0167]

[0168] Among them, <…> V represents the volume average of volume V, <f> V' =(1 / V')∫ V' f(x)dυ, is the pore volume in the representative volume unit RVE, that is and are the bulk dilatation and shear components expressed as incremental strains in a representative volume element, respectively.

[0169] Alternatively, substituting the applied incremental strain into the generalized expression for the effective elastic modulus yields:

[0170]

[0171]

[0172] in, P and Q are the inclusion geometry factors, is the probability density function describing the pore shape distribution, k f is the bulk modulus of the fluid.

[0173] As an alternative, the expression for the effective elastic modulus of porous rock is:

[0174]

[0175]

[0176] Example 5

[0177] This embodiment provides an electronic device, which includes: a memory storing executable instructions; and a processor, which runs the executable instructions in the memory to implement the above-mentioned porous rock elastic modulus prediction method.

[0178] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0179] 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.

[0180] The processor may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present disclosure, the processor is used to run the computer-readable instructions stored in the memory.

[0181] 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.

[0182] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0183] Example 6

[0184] This embodiment provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the method for predicting the elastic modulus of porous rock is implemented.

[0185] According to the computer-readable storage medium of the embodiment of the present disclosure, non-transitory computer-readable instructions are stored thereon. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the above-mentioned methods of each embodiment of the present disclosure are executed.

[0186] 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).

[0187] Those skilled in the art should understand that the purpose of the above description of the embodiments of the present invention is only to exemplarily illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any given examples.

[0188] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.< / f> < / f> < / f> < / f> < / f> < / f>

Claims

1. A method for predicting elastic modulus of porous rocks, It is characterized in that include: Obtaining the bulk modulus and shear modulus of the solid matrix of the rock sample; Performing nondestructive scanning on the rock sample to obtain grayscale frequency distribution of the CT image and quantitative parameters of the pore structure of the embedded body; determining the porosity of the rock sample; The effective elastic modulus is calculated according to the bulk modulus, the shear modulus, the quantitative parameter of the embedded body pore structure and the porosity by using an equivalent embedded body stress average approximation method.

2. The method for predicting elastic modulus of porous rock according to claim 1, in, The quantitative parameters of the embedded pore structure include the pore morphology of the porous rock, the pore aspect ratio, the volume proportion of different types of pores, and the pore connectivity.

3. The method for predicting elastic modulus of porous rock according to claim 1, in, The effective elastic modulus is calculated by the equivalent embedded body stress average approximation method including: The interaction between the inclusions embedded in the background material having the bulk modulus and the shear modulus is characterized in the form of incremental strain by using the equivalent embedded body stress average approximation method, and the effective elastic modulus is calculated.

4. The method for predicting elastic modulus of porous rock according to claim 1, in, The equivalent embedded body stress average approximation method comprises the following steps: Define representative volume elements and their volumes of porous rock and determine the applied incremental strain; Under the condition that the fluid pressure between pores is completely communicated, the added incremental strain is substituted into the generalized expression of the effective elastic modulus to obtain the expression of the effective elastic modulus of porous rock.

5. The method for predicting elastic modulus of porous rock according to claim 4, in, The applied incremental strain is: Among them, <…> V represents the volume average of volume V, <f> V' =(1 / V')∫ V' f(x)dυ, is the pore volume in the representative volume unit RVE, that is and are the bulk dilatation and shear components expressed as incremental strains in a representative volume element, respectively.< / f> 6. The method for predicting elastic modulus of porous rock according to claim 4, in, Substituting the applied incremental strain into the generalized expression for the effective elastic modulus yields: in, P and Q are the inclusion geometry factors, is the probability density function describing the pore shape distribution, k f is the bulk modulus of the fluid.

7. The method for predicting elastic modulus of porous rock according to claim 4, in, The expression of the effective elastic modulus of porous rock is:

8. A porous rock elastic modulus prediction device, It is characterized in that include: A sampling module to obtain the bulk modulus and shear modulus of the solid matrix of the rock sample; A scanning module performs non-destructive scanning on the rock sample to obtain the grayscale frequency distribution of the CT image and obtain quantitative parameters of the pore structure of the embedded body; A measuring module, for measuring the porosity of the rock sample; A calculation module calculates the effective elastic modulus through an equivalent embedded body stress average approximation method according to the bulk modulus, the shear modulus, the quantitative parameter of the embedded body pore structure and the porosity.

9. An electronic device, It is characterized in that The electronic device comprises: A memory storing executable instructions; A processor, wherein the processor runs the executable instructions in the memory to implement the porous rock elastic modulus prediction method according to any one of claims 1 to 7.

10. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for predicting the elastic modulus of porous rocks described in any one of claims 1 to 7 is implemented.

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