Multi-scale rock physical modeling method, electronic equipment, storage medium and device

Abstract

The invention discloses a multi-scale rock physical modeling method, electronic equipment, a storage medium and a multi-scale rock physical modeling device. The method comprises the following steps: acquiring a three-dimensional picture of a rock core sample; segmenting the three-dimensional picture to obtain a micro-scale rock core model; constructing a macro-scale digital karst cave and a macro-scale digital crack based on the karst fracture profile of the karst reservoir; based on the change of the karst caves and the cracks in the macro-scale digital karst caves and the macro-scale digital cracks, generating a macro-scale fracture section digital model; performing dynamic stress-strain simulation on the basis of the micro-scale rock core model and the macro-scale fault-solution section digital model to obtain a simulation result representing rock frequency dispersion and attenuation characteristics; and establishing a multi-scale rock physical model of the karst reservoir based on a simulation result. According to the method, the characteristics of the stratum are flexibly, efficiently and accurately expressed by establishing the multi-scale rock physical model of the karst reservoir, meanwhile, wide accessibility is achieved, time and resource cost are saved, and exploration and production strategies can be optimized.

Description

Technical Field

[0001] The present invention belongs to the technical field of digital core simulation, and more specifically, relates to a multi-scale rock physics modeling method, an electronic device, a storage medium, and a device. Background Art

[0002] Digital rock physics is developing rapidly at the current stage. With the help of advanced computing technologies and simulation methods, digital rock physics can more accurately simulate multi-scale rock properties and reservoir behavior, providing a powerful tool for oil and gas exploration, reservoir management, and geological research. By combining digital technology with rock physics, the multi-scale characteristics of deep karst reservoirs can be accurately simulated, and the complexity and heterogeneity of rock reservoirs can be better understood.

[0003] The deep karst reservoirs in the Tarim Basin are the main force for increasing oil and gas production and reserves in China. These karst reservoirs usually have some unique geological structures, such as caves, fractured caves, etc., and there are also heterogeneity characteristics at different scales, which have an important impact on the fluid flow and storage performance of the reservoir. At the microscale, deep karst reservoirs are usually composed of tiny structures such as rock particles, pores, and fractures; the distribution, shape, and connectivity of these microscale features affect the permeability, porosity, and fluid storage performance of the reservoir. At the macroscale, deep karst reservoirs are usually affected by geological processes such as large faults and dissolution, resulting in overall heterogeneity of the reservoir and affecting the large-scale fluid migration behavior of the reservoir. Therefore, accurately simulating and understanding this multi-scale heterogeneity is crucial for optimizing reservoir development and production plans.

[0004] Due to the limitations of experimental methods, digital rock physics methods have become an important alternative way to obtain multi-scale data. Through digital simulation and calculation, multi-scale rock physics models can be constructed to simulate rock properties and behaviors from microscale to macroscale, providing comprehensive information and generating a large amount of data in a shorter time, which helps to improve the efficiency of research. Although digital rock physics models also need to be based on accurate rock physical property data and geological information, they may still be limited by factors such as computing power and numerical methods when simulating some complex situations. Overall, digital rock physics methods do provide a more flexible, efficient, and accurate tool for constructing multi-scale rock physics models.

[0005] Current research mainly focuses on a single scale. Research at the seismic scale mainly focuses on the tectonic and fracture characteristics of rock formations, which helps predict seismic activities and tectonic evolution; while research at the core scale mainly infers rock properties and geological characteristics by collecting and analyzing core samples. Limiting the research focus to a single scale may limit our comprehensive understanding of the overall properties of deep karst reservoirs. In the actual development and utilization process, single-scale research may not be able to solve complex problems in the reservoir, which may lead to an increase in decision-making risks. Conducting multi-scale rock physics research based on experimental methods faces many challenges and difficulties. Due to the complex rock structure, deep carbonate karst reservoirs are usually accompanied by problems such as lack of logging data, difficulty in obtaining core samples, and difficulty in calibrating layer seismic characterization. Using conventional rock physics means, it is impossible to clarify the relationships between porosity, cave size, internal structure, filling type, fluid, fracture development, fracture connectivity, etc. and the elastic wave velocity and attenuation characteristics.

[0006] The information disclosed in the background art section of the present invention is only intended to deepen the understanding of the general background art of the present invention, and should not be regarded as an admission or any form of implication that this information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0007] The object of the present invention is to propose a multi-scale rock physics modeling method, an electronic device, a storage medium and a device, to establish a multi-scale rock physics model, through which the characteristics of the formation can be flexibly, efficiently and accurately expressed, and at the same time wide accessibility can be achieved.

[0008] To achieve the above object, the present invention proposes a multi-scale rock physics modeling method, an electronic device, a storage medium and a device.

[0009] According to the first aspect of the present invention, a multi-scale rock physics modeling method is proposed, including:

[0010] Obtain a three-dimensional picture of a core sample;

[0011] Segment the three-dimensional picture to obtain a micro-scale core model;

[0012] Construct a macro-scale digital cave and a macro-scale digital fracture based on the fault-karst profile of the karst reservoir;

[0013] Generate a macro-scale fault-karst profile digital model based on the changes of caves and fractures in the macro-scale digital cave and the macro-scale digital fracture;

[0014] Conduct dynamic stress-strain simulation based on the micro-scale core model and the macro-scale fault-karst profile digital model to obtain a simulation result representing the dispersion and attenuation characteristics of the rock;

[0015] Based on the simulation results, a multi-scale rock physics model of the karst reservoir is established.

[0016] Optionally, the obtaining the micro-scale core model by segmenting the three-dimensional picture includes:

[0017] Obtaining a three-dimensional micro digitalized core of a set size by performing threshold segmentation on the three-dimensional picture;

[0018] Uniformly segmenting the three-dimensional micro digitalized core to obtain a plurality of micro-scale core models.

[0019] Optionally, based on the outcrop observation and literature research of the specific morphological distribution of the fault-karst profile, the macro-scale digitalized cave and the macro-scale digitalized fracture based on the actual field outcrop are constructed.

[0020] Optionally, by giving the parameters of the cave, the parameters of the fractures in the sliding fault zone, and the parameters of the fractures in the induced fracture zone, and randomly varying the positions of the cave and the fractures, the morphology of the cave, and the angles of the fractures, a macro-scale digitalized fault-karst profile model is generated.

[0021] Optionally, the simulation results representing the dispersion and attenuation characteristics of the rock include:

[0022] P-wave velocity and inverse quality factor.

[0023] Optionally, the expression of the P-wave velocity is:

[0024]

[0025] Wherein, V p (ω) represents the P-wave velocity, ω is the circular frequency, V pc (ω) is the complex P-wave velocity, M(ω) is the complex P-wave modulus, ρ is the density, and Re is the real part of.

[0026] Optionally, the expression of the inverse quality factor is:

[0027]

[0028] Wherein, Q P (ω) is the inverse quality factor, Im is the imaginary part of M(ω), and Re is the real part of M(ω).

[0029] According to the second aspect of the present invention, a multi-scale rock physics modeling device is proposed, including:

[0030] An acquisition module, configured to acquire a three-dimensional picture of a core sample;

[0031] A segmentation module for segmenting the three-dimensional picture to obtain a microscopic-scale core model;

[0032] A construction module for constructing a macroscopic-scale digital cave and a macroscopic-scale digital fracture based on the fault dissolution profile of a karst reservoir;

[0033] A generation module for generating a macroscopic-scale fault dissolution profile digital model based on the changes of caves and fractures in the macroscopic-scale digital cave and the macroscopic-scale digital fracture;

[0034] A simulation module for performing dynamic stress-strain simulation based on the microscopic-scale core model and the macroscopic-scale fault dissolution profile digital model to obtain a simulation result representing the dispersion and attenuation characteristics of rocks;

[0035] An establishment module for establishing a multi-scale rock physics model of a karst reservoir based on the simulation result.

[0036] According to a third aspect of the present invention, an electronic device is provided, and the electronic device includes:

[0037] At least one processor; and,

[0038] A memory communicatively connected to the at least one processor; wherein,

[0039] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any one of the multi-scale rock physics modeling methods in the first aspect.

[0040] According to a fourth aspect of the present invention, a non-transitory computer-readable storage medium is provided, characterized in that the non-transitory computer-readable storage medium stores computer instructions for causing a computer to execute any one of the multi-scale rock physics modeling methods in the first aspect.

[0041] The beneficial effects of the present invention are as follows: In the process of conventional digital core and rock physics modeling, the research focus is limited to a single scale and cannot adapt to the complex conditions in reservoirs. Therefore, the present invention establishes a multi-scale rock physics model for karst reservoirs. The present invention constructs a digital core model with microscopic dimensions by segmenting three-dimensional pictures of core samples, expanding samples for digital analysis, and facilitating the analysis of the influence of microscopic structures and their connectivity on the dispersion and attenuation characteristics of rocks. Based on the fault-karst profile, digital caves with macroscopic dimensions and digital fractures with macroscopic dimensions are constructed. Based on the changes in digital caves with macroscopic dimensions and digital caves with macroscopic dimensions, a digital model of the fault-karst profile at the macroscopic scale is generated, and an idealized digital model of the macroscopic fault-karst profile is constructed. This model not only considers actual geological characteristics but also combines the characteristics of flexible parameter adjustment of digital models, facilitating the construction of a large number of models and saving time and costs. Based on the digital model of the macroscopic fault-karst profile and the digital core model with microscopic dimensions, dynamic stress-strain simulations are carried out to obtain simulation results representing the dispersion and attenuation characteristics of rocks. Based on the simulation results, a multi-scale rock physics model for karst reservoirs is established. The present invention reveals the differences in rock characteristics at different scales under the same geological background through the multi-scale rock physics model for karst reservoirs, provides more comprehensive information for fields such as reservoir evaluation, fluid simulation, and oil and gas development, saves time and resource costs, and can optimize exploration and production strategies. Through the multi-scale rock physics model for karst reservoirs, the characteristics of the formation can be expressed flexibly, efficiently, and accurately, and at the same time, wide accessibility can be achieved.

[0042] The system of the present invention has other characteristics and advantages, which will be obvious from the accompanying drawings incorporated herein and the subsequent detailed description, or will be described in detail in the accompanying drawings incorporated herein and the subsequent detailed description. These accompanying drawings and detailed description are used together to explain the specific principles of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] By describing the exemplary embodiments of the present invention in more detail in conjunction with the accompanying drawings, the above and other objects, features, and advantages of the present invention will become more obvious. In the exemplary embodiments of the present invention, the same reference numerals generally represent the same components.

[0044] Figure 1 FIG. shows a flowchart of the steps of a multi-scale rock physics modeling method according to the present invention.

[0045] Figure 2 FIG. shows a schematic diagram of a three-dimensional digital rock model based on the CT scan results of carbonate rocks according to Embodiment 2 of the present invention.

[0046] Figure 3 FIG. shows a flowchart of constructing a digital model of the macroscopic fault-karst profile according to Embodiment 2 of the present invention.

[0047] Figure 4a and Figure 4b shows a schematic diagram of the relationship between the longitudinal wave impedance in the vertical macroscale and the longitudinal wave impedance in the horizontal macroscale combined with porosity at the microscale according to Embodiment 2 of the present invention.

[0048] Figure 5 shows a schematic diagram of a multi-scale rock physics modeling device according to Embodiment 3 of the present invention. Detailed implementation manners

[0049] The present invention will be described in more detail below with reference to the accompanying drawings. Although the preferred embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to make the present invention more thorough and complete, and to fully convey the scope of the present invention to those skilled in the art.

[0050] As Figure 1 shown, a multi-scale rock physics modeling method according to the present invention includes:

[0051] Obtain a three-dimensional picture of a core sample;

[0052] Segment the three-dimensional picture to obtain a microscale core model;

[0053] Construct a macroscale digital cave and a macroscale digital fracture based on the fault-karst profile of a karst reservoir;

[0054] Generate a macroscale fault-karst profile digital model based on the changes in the cave and the fracture in the macroscale digital cave and the macroscale digital fracture;

[0055] Conduct dynamic stress-strain simulation based on the microscale core model and the macroscale fault-karst profile digital model to obtain a simulation result representing the dispersion and attenuation characteristics of the rock;

[0056] Establish a multi-scale rock physics model of a karst reservoir based on the simulation result.

[0057] Specifically, based on the research objective, the present invention obtains three-dimensional pictures of core samples through micro-CT scanning, and obtains three-dimensional microscopic digital cores of a set size by performing threshold segmentation on the three-dimensional pictures; evenly divides the three-dimensional microscopic digital cores to obtain a plurality of microscopic-scale core models. Through this segmentation scheme, a large number of digital core samples containing geological constraints can be generated, and numerical cutting can be performed without damaging the actual samples. With the help of digital rock physics technology, large-scale rock samples with high geological constraints are generated, overcoming many limitations of traditional rock sample collection, providing valuable data resources for scientific research and engineering applications, and enhancing the digital rock samples at the microscopic scale. For example, a representative microscopic digital core with a size of 200*200*200 is selected from the overall threshold segmentation, and on this basis, the cubic core is divided into two in each of the three dimensions to generate a total of 8 three-dimensional digital small cubic cores with a size of 100*100*100. This three-dimensional digital small cubic core is the microscopic-scale core model; based on the outcrop observation and literature research of the specific morphological distribution of the fracture-cavity profile, a macroscopic-scale digital cave and a macroscopic-scale digital fracture are constructed based on the actual field outcrop. On this basis, parameters including the number of caves, the number, length, width, distribution, etc. of fractures in the sliding fracture zone and the induced fracture zone are given, and the positions of the caves and fractures are randomly changed, and the cave morphology and fracture angle are slightly changed to generate a macroscopic-scale fracture-cavity profile digital model containing geological and physical backgrounds and reasonable perturbations. This model can not only simulate known rock profiles, but also generate ideal rock structures for purposes such as verifying geological models and expanding geological scenarios. For strong heterogeneous complex geological conditions such as fracture-cavity reservoirs that are difficult to actually measure, the digital ideal profile can be used to simulate various geological scenarios, conduct experimental research, and optimize exploration and development strategies; perform dynamic stress-strain simulation based on the microscopic-scale core model and the macroscopic-scale fracture-cavity profile digital model. During the simulation, the forced deformation movement of the digital core in the horizontal direction can be achieved by specifying the velocity components of the particles at the left and right boundaries. Fix the left boundary of the digital core, that is, the velocity component of its particles is: v x (0,z,t)=0,v z (0,z,t)=0,v x is the velocity component of the particle in the x direction, v z is the velocity component of the particle in the z direction, and t is the time; the velocity component of the particle at the right boundary of the digital core is: v x (L,z,t)=A·f(t),v z (L,z,t)=0,L represents the side length of the digital core in the horizontal direction, f(t) is a function of time t, and A is a constant for adjusting the strain magnitude; the initial condition of this algorithm is that the velocity and displacement components of all particles of the digital core are zero, that is, v x (x,z,t=0)=0,ux (x,z,t = 0) = 0, v z (x,z,t = 0) = 0, u z (x,z,t = 0) = 0, u x is the displacement component of the particle in the x - direction, u z is the displacement component of the particle in the z - direction. Assume that the skeleton of the digital core consists of an isotropic linear elastic medium, and its constitutive equation is:

[0058]

[0059] where, σ xx 、σ yy 、σ zz 、σ zx 、σ xy and σ yz are stresses, e xx 、σe yy 、e zz 、e zx 、e xy and e yz are strains. The constitutive relation of the fluid is:

[0060]

[0061] where, the motion equation is:

[0062]

[0063] where, u y is the displacement component of the particle in the y - direction; During the wave - field simulation by the finite - difference method, calculate the average normal strain and normal stress curves of the digital core:

[0064]

[0065] In the formula, (i, j) represents the index of the grid, <·> represents the volume average of the variable, and respectively represent the normal stress and normal strain of the grid (i, j) in the x - direction at time t, and respectively represent the average normal stress and normal strain of the digital core in the x - direction at time t; After the simulation, calculate the strain - rate and stress - rate curves:

[0066]

[0067] The complex longitudinal - wave modulus of the digital core is the ratio of the Fourier transform of the stress - rate and strain - rate curves:

[0068] In the formula, FT[·] represents the Fourier transform, and ω is the circular frequency;

[0069] The P-wave velocity and inverse quality factor of the digital core are calculated from the complex P-wave modulus and density:

[0070]

[0071] where V p (ω) represents the P-wave velocity, ω is the circular frequency, and V pc (ω) is the complex P-wave velocity, M(ω) is the complex P-wave modulus, ρ is the density, Re is the real part of, Q P (ω) is the inverse quality factor, Im is the imaginary part of M(ω), and Re is the real part of M(ω); the simulation results representing the dispersion and attenuation characteristics of the rock are obtained through the above formulas; based on the simulation results, a multi-scale rock physics model of the karst reservoir is established. The velocity data of each frequency band are selected from the digital rock physics simulation results obtained from the micro-scale digital core model and the macro-scale fault-karst profile digital model. Combining the simulation and porosity, the relationship between the P-wave impedance and porosity including multi-scale data is constructed to form a multi-scale rock physics model of the deep karst reservoir driven by digital rock physics. The uniqueness of this model lies in that the data generated by the simulation can describe the physical properties of the rock at different scales, observe their similarities and differences, which helps to consider different scales and geological scenarios more comprehensively, save time and resource costs, and can optimize exploration and production strategies. Combining the micro results with the macro results reveals the differences in rock characteristics at different scales under the same geological background, provides more comprehensive information for fields such as reservoir evaluation, fluid simulation, and oil and gas development, and helps to optimize decision-making.

[0072] In one example, the micro-scale core model obtained by segmenting the three-dimensional picture includes:

[0073] The three-dimensional micro digital core with a set size is obtained by threshold segmentation of the three-dimensional picture;

[0074] The three-dimensional micro digital core is evenly segmented to obtain multiple micro-scale core models.

[0075] In one example, the macro-scale digital karst cave and macro-scale digital fracture based on the actual field outcrop are constructed based on the outcrop observation and literature research of the specific morphological distribution of the fault-karst profile.

[0076] In one example, by specifying the parameters of the karst cave, the parameters of the fractures in the sliding fault zone, and the parameters of the fractures in the induced fracture zone, and randomly varying the positions of the karst cave and fractures, the morphology of the karst cave, and the angles of the fractures, a macro-scale fault-karst profile digital model is generated.

[0077] In one example, the simulation results representing the dispersion and attenuation characteristics of rocks include:

[0078] P-wave velocity and inverse quality factor.

[0079] In one example, the expression for the P-wave velocity is:

[0080]

[0081] where V p (ω) represents the P-wave velocity, ω is the circular frequency, and V pc (ω) is the complex P-wave velocity, M(ω) is the complex P-wave modulus, ρ is the density, and Re is the real part of.

[0082] In one example, the expression for the inverse quality factor is:

[0083]

[0084] where Q P (ω) is the inverse quality factor, Im is the imaginary part of M(ω), and Re is the real part of M(ω).

[0085] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, but it is not a limitation of the present invention. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0086] Embodiment 1

[0087] This embodiment provides a multi-scale rock physics modeling method, including:

[0088] Obtaining three-dimensional pictures of a core sample through micro-CT scanning; obtaining a three-dimensional microscopic digitalized core of a set size by performing threshold segmentation on the three-dimensional pictures; uniformly dividing the three-dimensional microscopic digitalized core to obtain a plurality of microscopic-scale core models; constructing a macroscopic-scale digitalized cave and a macroscopic-scale digitalized fracture based on the outcrop observation and literature research of the specific morphological distribution of the fracture dissolution profile; generating a macroscopic-scale fracture dissolution profile digitalized model by specifying the parameters of the cave, the parameters of the fractures in the sliding fracture zone, and the parameters of the fractures in the induced fracture zone, and randomly varying the positions of the cave and the fractures, the morphology of the cave, and the angles of the fractures; performing dynamic stress-strain simulation based on the microscopic-scale core models and the macroscopic-scale fracture dissolution profile digitalized model to obtain simulation results representing the dispersion and attenuation characteristics of rocks; the simulation results representing the dispersion and attenuation characteristics of rocks include P-wave velocity and inverse quality factor; the expression for the P-wave velocity is:

[0089] Among them, V p (ω) represents the longitudinal wave velocity, ω is the circular frequency, and V pc (ω) is the complex longitudinal wave velocity, M(ω) is the complex longitudinal wave modulus, ρ is the density, and Re is the real part; the expression of the inverse quality factor is:

[0090] Among them, Q P (ω) is the inverse quality factor, Im is the imaginary part of M(ω), and Re is the real part of M(ω); select the velocity data of each frequency band from the simulation results, and combine the simulation and porosity to construct the relationship between the longitudinal wave impedance and porosity containing multi-scale data, and establish a multi-scale rock physics model of deep karst reservoirs driven by digital rock physics.

[0091] Example 2

[0092] This example provides a multi-scale rock physics modeling method, including:

[0093] Step 1: Based on the research objective, perform sample segmentation from the threshold segmentation results of the microscopic CT scan images to obtain three-dimensional images of the core samples; select a representative microscopic digital core with a size of 200*200*200 from the overall threshold segmentation, and on this basis, divide the cubic core into two in each of the three dimensions to generate a total of 8 three-dimensional digital small cubic cores with a size of 100*100*100, as Figure 2 shown, and save it as a file that can be read again; this step can generate a large number of digital rock samples containing geological constraints, realizing sample enhancement; based on the microscopic CT samples, digital rock models with representative sizes of 200 and 100 pixel points are generated, expanding the samples for digital analysis, and facilitating the analysis of the influence of the microscopic structure and its connectivity on the dispersion and attenuation characteristics of the rock

[0094] Step 2: As Figure 3 shown, based on the outcrop observation and literature research on the specific morphological distribution of the fault-karst profile, construct macroscopic digital karst caves and digital fractures based on the actual field outcrops. On this basis, given parameters including the number of karst caves, the number, length, width, and distribution of fractures in the sliding fault zone and the induced fracture zone, and randomly change the positions of the karst caves and fractures, and slightly change the karst cave morphology and fracture angles within a small range to generate a macroscopic fault-karst profile digital model containing geological and physical backgrounds and reasonable perturbations; this step constructs an idealized macroscopic fault-karst profile digital model, which not only considers the actual geological characteristics but also combines the characteristics of the digital model to flexibly adjust parameters, facilitating the construction of a large number of models and saving time and cost;

[0095] Step 3: Generate digital rock models at the microscale and macroscale for Steps 1 and 2.

[0096] The forced deformation motion of the digital core in the horizontal direction can be achieved by specifying the velocity components of the particles at the left and right boundaries. A simple implementation is to fix the left boundary of the digital core, i.e., the velocity components of its particles are:

[0097] v x (0, z, t) = 0

[0098] v z (0, z, t) = 0 (1)

[0099] In the formula, v x and v z are the velocity components of the particle in the x and z directions. The velocity components of the particles at the right boundary of the digital core are:

[0100] v x (L, z, t) = A·f(t)

[0101] v z (L, z, t) = 0 (2)

[0102] In the formula, L represents the side length of the digital core in the horizontal direction; f(t) is a function of time t; A is a constant for adjusting the strain magnitude.

[0103] The initial condition of this algorithm is that the velocity and displacement components of all particles of the digital core are zero, i.e.,

[0104] v x (x, z, t = 0) = 0 u x (x, z, t = 0) = 0

[0105] v z (x, z, t = 0) = 0, u z (x, z, t = 0) = 0 (3)

[0106] In the formula, u x and u z are the displacement components of the particle in the x and z directions.

[0107] Assume that the skeleton of the digital core consists of an isotropic linearly elastic medium, and its constitutive equation is:

[0108]

[0109] In the formula, σ xx , σ yy , σ zz , σ zx , σ xy and σ yzdenotes stress; e xx , e yy , e zz , e zx , e xy and e yz denote strain. The constitutive relation of the fluid is:

[0110]

[0111] The equation of motion is:

[0112]

[0113] wherein, u x , u y and u z denote displacement components.

[0114] During the finite-difference wavefield simulation, the average normal strain and normal stress curves of the digital core are calculated,

[0115]

[0116] wherein, i, j denote the indices of the grid, <·> denotes the volume average of the variable, and respectively denote the normal stress and normal strain in the x direction of the grid (i, j) at time t, τ xx (t) and ε xx (t) respectively denote the average normal stress and normal strain of the digital core in the x direction at time t.

[0117] After the simulation, the strain rate and stress rate curves are calculated

[0118]

[0119] The complex longitudinal wave modulus of the digital core is the ratio of the Fourier transform of the stress rate and strain rate curves,

[0120]

[0121] wherein, FT[·] denotes the Fourier transform, and ω is the circular frequency. The longitudinal wave velocity and inverse quality factor of the digital core are calculated from the complex longitudinal wave modulus and density,

[0122]

[0123] wherein, V P (ω) denotes the longitudinal wave velocity, denotes the inverse quality factor of the longitudinal wave.

[0124] Step 4: Select the velocity data in their respective frequency bands from the digital rock physics simulation results obtained from the microscopic digital model and the macroscopic digital model. Combine the simulation results and porosity to construct the relationship between the longitudinal wave impedance and porosity containing multi-scale data, as shown in Figures 4(a) and 4(b). Establish a multi-scale rock physics model for deep karst reservoirs driven by digital rock physics. This step combines the microscopic results with the macroscopic results, revealing the differences in rock characteristics at different scales under the same geological background, providing more comprehensive information for fields such as reservoir evaluation, fluid simulation, and oil and gas development, and helping to optimize decision-making.

[0125] Example 3

[0126] As Figure 5 shown, this example provides a multi-scale rock physics modeling device, including:

[0127] An acquisition module for obtaining three-dimensional pictures of core samples;

[0128] A segmentation module for segmenting the three-dimensional pictures to obtain a microscopic-scale core model;

[0129] A construction module for constructing a macroscopic-scale digital cave and macroscopic-scale digital fractures based on the fault-karst profile of the karst reservoir;

[0130] A generation module for generating a macroscopic-scale fault-karst profile digital model based on the changes in caves and fractures in the macroscopic-scale digital cave and macroscopic-scale digital fractures;

[0131] A simulation module for performing dynamic stress-strain simulations based on the microscopic-scale core model and the macroscopic-scale fault-karst profile digital model to obtain simulation results representing the dispersion and attenuation characteristics of rocks;

[0132] An establishment module for establishing a multi-scale rock physics model for the karst reservoir based on the simulation results.

[0133] Example 4

[0134] This example provides an electronic device, which includes:

[0135] At least one processor; and,

[0136] A memory communicatively connected to the at least one processor; wherein,

[0137] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the multi-scale rock physics modeling method in Example 1.

[0138] An electronic device according to an embodiment of the present disclosure includes a memory and a processor. The memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0139] 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 an embodiment of the present disclosure, the processor is used to run the computer-readable instructions stored in the memory.

[0140] Those skilled in the art should understand that, in order to solve the technical problem of how to obtain good user experience effects, known structures such as communication buses and interfaces may also be included in this embodiment, and these known structures should also be included in the protection scope of the present disclosure.

[0141] For a detailed description of this embodiment, reference may be made to the corresponding descriptions in the foregoing embodiments, and details will not be repeated here.

[0142] Embodiment 5

[0143] This embodiment provides a non-transitory computer-readable storage medium that stores computer instructions for causing a computer to execute the multi-scale rock physics modeling method in Embodiment 1.

[0144] A computer-readable storage medium according to an embodiment of the present disclosure stores non-transitory computer-readable instructions thereon. When the non-transitory computer-readable instructions are run by a processor, all or part of the steps of the methods of the foregoing embodiments of the present disclosure are executed.

[0145] The above-mentioned computer-readable storage media include but are not limited to: optical storage media (such as CD-ROM and DVD), magneto-optical storage media (such as MO), magnetic storage media (such as magnetic tape or removable hard disk), media with built-in rewritable non-volatile memory (such as memory card), and media with built-in ROM (such as ROM cartridge).

[0146] The embodiments of the present invention have been described above. The above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations are obvious to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.

[0147] The embodiments of the present invention have been described above. The above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations are obvious to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A multi-scale rock physics modeling method, characterized in that, it includes: Obtain a three-dimensional picture of the core sample; Segment the three-dimensional picture to obtain a micro-scale core model; Construct a macro-scale digital cave and a macro-scale digital fracture based on the fault dissolution profile of the karst reservoir; Generate a macro-scale fault dissolution profile digital model based on the changes of caves and fractures in the macro-scale digital cave and the macro-scale digital fracture; Conduct dynamic stress-strain simulation based on the micro-scale core model and the macro-scale fault dissolution profile digital model to obtain a simulation result representing the dispersion and attenuation characteristics of the rock; Establish a multi-scale rock physics model of the karst reservoir based on the simulation result.

2. The multi-scale rock physics modeling method according to claim 1, characterized in that, The segmenting the three-dimensional picture to obtain a micro-scale core model includes: Obtain a three-dimensional micro digital core of a set size by threshold segmenting the three-dimensional picture; Uniformly segment the three-dimensional micro digital core to obtain a plurality of micro-scale core models.

3. The multi-scale rock physics modeling method according to claim 1, characterized in that, Construct the macro-scale digital cave and the macro-scale digital fracture based on the outcrop observation and literature research of the specific morphological distribution of the fault dissolution profile.

4. The multi-scale rock physics modeling method according to claim 1, characterized in that, Generate a macro-scale fault dissolution profile digital model by specifying cave parameters, parameters of fractures in the sliding fracture zone, and parameters of fractures in the induced fracture zone, and randomly varying the positions of the cave and the fractures, the shape of the cave, and the angles of the fractures.

5. The multi-scale rock physics modeling method according to claim 1, characterized in that, The simulation result representing the dispersion and attenuation characteristics of the rock includes: P-wave velocity and inverse quality factor.

6. The multi-scale rock physics modeling method according to claim 5, characterized in that, The expression of the P-wave velocity is: Among them, V p (ω) represents the longitudinal wave velocity, ω is the circular frequency, V pc (ω) is the complex longitudinal wave velocity, M(ω) is the complex longitudinal wave modulus, ρ is the density, and Re is the real part of.

7. The multi-scale rock physics modeling method according to claim 6, characterized in that, The expression of the inverse quality factor is: Among them, Q P (ω) is the inverse quality factor, Im is the imaginary part of M(ω), and Re is the real part of M(ω).

8. An electronic device, characterized in that, the electronic device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the multi-scale rock physics modeling method according to any one of claims 1-7.

9. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions for causing a computer to execute the multi-scale rock physics modeling method according to any one of claims 1-7.

10. A multi-scale rock physics modeling device, characterized in that, it includes: An acquisition module for the three-dimensional picture of the core sample; A segmentation module for segmenting the three-dimensional picture to obtain a micro-scale core model; A building module for constructing macroscopic digital caves and macroscopic digital fractures based on the fault-karst profile of a karst reservoir; A generating module for generating a macroscopic fault-karst profile digital model based on the changes in caves and fractures in the macroscopic digital caves and the macroscopic digital fractures; A simulation module for performing dynamic stress-strain simulations based on the microscopic core model and the macroscopic fault-karst profile digital model to obtain simulation results representing the dispersion and attenuation characteristics of rocks; A building module for establishing a multi-scale rock physics model of a karst reservoir based on the simulation results.

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