A method for predicting microscale seismic wave dispersion based on scanning electron microscopy

Abstract

The present application belongs to the technical field of electron microscope scanning, and particularly relates to a method for predicting microscale seismic wave dispersion based on electron microscope scanning, which comprises the following steps: step one, geometric model construction: obtaining the distribution characteristics of rock sample particles at the particle scale, confirming the size of a representative unit, and constructing a numerical model of microscale pores and fractures; step two, grid subdivision: first, selecting the position of the fracture in the representative unit, and using triangular grid subdivision and refinement; second, using adaptive grid subdivision for other pore positions; and step three, converting the linear elasticity equation and the Navier-Stokes equation to the frequency domain to describe the elastic and fluid properties of the rock. The present application uses the electron microscope scanning results as the contact, searches for the optimal scale of the numerical model by using the REV scanning method, and describes the operation rules of each phase in the REV in a fully coupled manner of the fluid field and the solid field, so that the prediction result accuracy can be improved.

Description

Technical Field

[0001] This invention belongs to the field of electron microscopy scanning technology, specifically relating to a method for predicting the dispersion of microscale seismic waves based on electron microscopy scanning. Background Technology

[0002] Fractures are very important transport channels in reservoirs, and studying their impact on seismic, acoustic, and ultrasonic responses is essential for reservoir reserve prediction and assessment.

[0003] At the microscopic scale, reservoir rocks are filled with fractures, and the fluids within them flow when seismic waves pass through, inducing elastic wave dispersion and attenuation, which in turn affects the geophysical response of earthquakes, acoustic waves, and ultrasound. Understanding the relationship between microscopic fractures and the dispersion and attenuation of elastic waves is key to solving the challenges of reservoir exploration.

[0004] Currently, there are two main methods for obtaining information on the impact of microscale cracks on seismic wave dispersion and attenuation: experimental testing and numerical prediction. Experimental methods utilize the stress-strain method to measure the elastic modulus of rock, then calculate the P-wave and S-wave velocities and attenuation, assessing the macroscopic effects of microscale cracks. Numerical methods use solution methods such as the finite element method to simulate fluid flow within rock, thereby obtaining the dispersion and attenuation characteristics of P-wave and S-wave velocities. Numerical simulation methods are cost-effective and computationally fast, and have received widespread attention in recent years, primarily focusing on the influence of factors such as fluid saturation on seismic wave dispersion and attenuation. However, these numerical models do not consider microcracks in rocks. Studies have shown that microscale cracks are a significant cause of seismic wave dispersion and attenuation, and the impact of crack formation has been predicted using simplified models. However, real microcracks in rocks are extremely complex; therefore, simplified models cannot accurately predict the dispersion and attenuation induced by cracks in rocks. Therefore, providing a method that can accurately predict the impact of cracks on seismic wave dispersion and attenuation at the microscale is essential in the field of rock physics. Summary of the Invention

[0005] The purpose of this invention is to provide a method for predicting the dispersion of seismic waves at the microscale based on electron microscopy scanning, which can improve the accuracy of prediction results.

[0006] The specific technical solution adopted by this invention is as follows: A method for predicting the dispersion of microscale seismic waves based on electron microscopy scanning, the method comprising the following steps: Step 1: Geometric Model Construction: Obtain the distribution characteristics of rock samples at the grain scale, confirm the size of representative units, and construct a numerical model of microscale pores and fractures. Step 2, Mesh Generation: First, select the location of the crack in the representative element, and then use triangular mesh generation and refinement. Next, use adaptive mesh generation for other pore locations. Step 3: Transform the linear elastic equation and the Navier-Stokes equation into the frequency domain to describe the elastic and fluid properties of the rock; Step 4: P-wave boundary conditions: Calculate the P-wave modulus of the rock using P-wave boundary conditions to obtain the P-wave velocity.

[0007] The technical effects achieved by this invention are as follows: This invention uses electron microscopy scanning results as a contact point and employs REV scanning to search for the optimal scale of the numerical model. Furthermore, it describes the operational laws of each phase in REV using a fully coupled fluid and solid field approach, thereby improving the accuracy of prediction results. Attached Figure Description

[0008] Figure 1 This is a schematic diagram of the technical route of the present invention; Figure 2 This is the numerical modeling diagram in this invention; Figure 3 This is the mesh partitioning diagram of the numerical model in this invention; Figure 4 This is the boundary condition loading diagram in this invention; Figure 5 This is a fluid pressure distribution diagram at 1 kHz in this invention; Figure 6 This is a fluid pressure distribution diagram at 10 kHz in this invention; Figure 7 This is a fluid pressure distribution diagram at 100 kHz in this invention; Figure 8 This is a comparison chart of the predicted results and experimental results in this invention. Detailed Implementation

[0009] To make the objectives and advantages of this invention clearer, the invention will be specifically described below with reference to embodiments. It should be understood that the following text is merely used to describe one or more specific embodiments of the invention and does not strictly limit the scope of protection specifically claimed by the invention.

[0010] like Figure 1-8 As shown, a method for predicting the dispersion of seismic waves at the microscale based on electron microscopy scanning is described, and the specific steps of the method are as follows: Step 1: Geometric Model Construction Electron microscopy was used to obtain the size and shape distribution characteristics of rock samples at the particle scale (several hundred micrometers). Porosity was calculated using rectangular frames of different scales. When the size of the rectangular frame reached a certain value, the porosity no longer changed; this current size is the representative element (REV) size. Relevant regions were selected from the electron microscopy results at this size to construct a numerical model of microscale pores and fractures.

[0011] By combining the above steps, through scanning electron microscopy and the determination of representative units (REV), we can gain a more comprehensive understanding of the microstructure and properties of rock samples and provide more accurate numerical simulations for practical problems.

[0012] like Figure 2 As shown, a is the Representative Element (REV) picking image, and b is the numerical model corresponding to the REV. Following step one above, the electron microscopy scanning results of carbonate rocks are first selected. Representative elements (REVs) are scanned using electron microscopy, and based on the REVs, a numerical model of the carbonate rocks at the microscale is constructed. Step 2: Mesh Generation a. Select the location of the crack in the representative unit, and refine it using triangular mesh; b. Adaptive meshing is used for other pore locations.

[0013] Based on step two, the adaptive mesh generation method is used to obtain the mesh generation result of REV, such as... Figure 3 As shown.

[0014] Step 3: Governing Equations: The linear elastic equations and Navier-Stokes equations are transformed into the frequency domain to describe the elastic and fluid properties of the rock. Two key equations are obtained, namely Equation 1: ; Equation 2: ; in It is the stress tensor, used to describe the stress distribution characteristics in solid particles. When describing the stress distribution characteristics in a fluid, ; F is the external applied stress of the solid particle portion; P is the fluid background pressure; It is the fluid shear viscosity. It refers to the viscosity of the fluid. It is the fluid velocity; It is the gradient operator. It is the divergence operator, and I is the identity matrix.

[0015] Based on step three, load the governing equations and boundary conditions, such as... Figure 4 As shown, Equation 1 is applied to the space occupied by the fluid to analyze the fluid flow characteristics, and Equation 2 is applied to the space occupied by the solid particles to analyze the stress distribution characteristics of the solid particles. The implementation effect of the case is as follows. Figure 4 As shown.

[0016] Step 4, P-wave boundary conditions: Since the electron microscopy results are 2D, the P-wave modulus of the rock can be calculated using P-wave boundary conditions, thereby obtaining the P-wave velocity.

[0017] a. Apply stress to the top of the numerical model. ; b. Apply fixed boundary conditions at the bottom of the numerical model, and adjust the displacement. ; c. Apply longitudinal wave boundary conditions to the side of the numerical model, and adjust the displacement. ; d. Solve the governing equations under the aforementioned P-wave boundary conditions using the finite element method. Combined with the PARDISO solver, simulate the physical behavior of the rock based on specific boundary conditions and calculate the required physical properties. This process helps to reveal the internal structure and characteristics of the rock.

[0018] e. Divide the stress by the strain in the entire numerical model to obtain the longitudinal wave modulus. : .

[0019] Based on step four, the fluid pressure and rock skeleton particle displacement characteristics were calculated. Results: The fluid pressure at 1 kHz, such as... Figure 5 As shown, the fluid pressure throughout the fracture and pore system is basically uniform, approximately 0.7 (fluid pressure / 0.1 MPa); the fluid pressure at 10 kHz, as... Figure 6 As shown, the fluid pressure in the entire fracture and pore system is locally non-uniform, approximately 0.75 (fluid pressure / 0.1MPa), while the fluid pressure at other locations is approximately 0.65. Fluid pressure at 100kHz, such as Figure 7 As shown, the fluid pressure in the entire fracture and pore system is non-uniform, with the local pressure in the narrow fracture being approximately 1, and the fluid pressure in the circular pores being approximately 0.3 and 0.4, which is relatively low (fluid pressure / 0.1MPa).

[0020] The above results indicate that at high frequencies, the fluid pressure in the crack cannot be released, resulting in a crack medium with high stiffness and thus a large longitudinal wave modulus; at low frequencies, the fluid pressure in the crack is successfully released, resulting in a crack medium with low stiffness and thus a smaller longitudinal wave modulus.

[0021] Based on step four, calculate Young's modulus. Young's modulus is an elastic property of a material, commonly used to describe the stiffness of a material under tension or compression, i.e., the relationship coefficient between stress and strain.

[0022] Next, this calculation result is compared with the experimental measurement result, such as... Figure 8As shown in the figure, this comparison verifies the reliability of the present invention and proves its effectiveness.

[0023] In summary, in terms of principle, traditional methods use simplified models of cracks and pores, assuming that each pore in the sample consists of a circular pore and a rectangular frame. The prerequisite for using this method is that the entire sample satisfies these assumptions at the microscopic scale; therefore, as the original technique described, it is a simple model. However, for real rocks, the REV scale is unknown, and the model selected at the REV scale is much more complex than the so-called simple model. Furthermore, the equations describing the physical laws of the above model are not simplified equations in the traditional method; the interaction and relationship between solids and fluids should be fully considered.

[0024] This invention addresses two shortcomings of traditional methods by proposing the following: 1. Using electron microscopy scanning results as a reference, the optimal scale for the numerical model is searched using REV scanning. 2. Describe the operating laws of each phase in REV using a fully coupled fluid field and solid field approach.

[0025] Furthermore, in terms of prediction results, this invention takes into account the actual situation, and therefore the prediction results are more accurate than those of traditional methods.

[0026] The above description is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained in this invention are implemented according to conventional methods in the art unless otherwise specified or limited.

Claims

1. A method for predicting the dispersion of microscale seismic waves based on electron microscopy, characterized in that: The method includes the following steps: S1. Geometric model construction: Obtain the distribution characteristics of rock samples at the particle scale, confirm the size of representative units, and construct a numerical model of microscale pores and fractures. S2. Mesh generation: First, select the location of the crack in the representative element, and then use triangular mesh generation and refinement. Next, use adaptive mesh generation for other pore locations. S3. Transform the linear elastic equation and the Navier-Stokes equation into the frequency domain to describe the elastic and fluid properties of rocks; S4. P-wave boundary conditions: Use P-wave boundary conditions to calculate the P-wave modulus of the rock and obtain the P-wave velocity; In S1, the size of the representative unit is determined by electron microscopy scanning technology; The two equations in S3 that transform the linear elastic equation and the Navier-Stokes equation to the frequency domain are as follows: Equation 1: ; Equation 2: ; in It is the stress tensor, used to describe the stress distribution characteristics in solid particles. When describing the stress distribution characteristics in a fluid, ; F is the external applied stress of the solid particle portion; P is the fluid background pressure; It is the fluid shear viscosity. It refers to the viscosity of the fluid. It is the fluid velocity; It is the gradient operator. It is the divergence operator, and I is the identity matrix.

2. The method for predicting microscale seismic wave dispersion based on electron microscopy scanning according to claim 1, characterized in that: The selection of the representative unit size in S1 is based on the variation in porosity.

3. The method for predicting microscale seismic wave dispersion based on electron microscopy scanning according to claim 1, characterized in that: The specific steps for obtaining the longitudinal wave velocity in S4 are as follows: A. Apply stress to the top of the numerical model. ; B. Apply fixed boundary conditions at the bottom of the numerical model, and adjust the displacement. ; C. Apply longitudinal wave boundary conditions to the side of the numerical model, and adjust the displacement. ; D. Solve the governing equations under the above longitudinal wave boundary conditions using the finite element method; E. Divide the stress by the strain in the entire numerical model to obtain the longitudinal wave modulus. .

4. The method for predicting microscale seismic wave dispersion based on electron microscopy scanning according to claim 3, characterized in that: The specific solution method for solving the governing equations under the aforementioned longitudinal wave boundary conditions using the finite element method is PARDISO.

5. The method for predicting microscale seismic wave dispersion based on electron microscopy scanning according to claim 3, characterized in that: The longitudinal wave modulus The solution formula is: 。

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