Finite element model construction method of large-scale digital core

Abstract

The invention relates to the field of digital core finite element model construction, and particularly discloses a large-scale digital core finite element model construction method. The method comprises the following steps: collecting a sandstone core sample, and trimming the sample into a regular cylinder; scanning the sample by using a CT scanning instrument to obtain a sample core image; carrying out noise reduction and enhancement processing on the CT image by using three-dimensional visualization software; a PyCharm writing program is used for removing the micro gaps; performing threshold segmentation on the image, and constructing a surface mesh model; carrying out repairing processing on the surface grid; a volume mesh finite element model is constructed through a surface mesh. According to the construction method of the digital rock core finite element model, the physical size of the digital rock core finite element model is greatly increased under the condition that accurate description of rock pore characteristics is guaranteed, and the constructed finite element model can be used for mechanical characteristic research simulation and cutting analog simulation of rocks.

Description

Technical Field

[0001] The present invention relates to the field of digital core finite element model construction, and more precisely to a method for constructing a large-scale digital core finite element model. Background Art

[0002] As the "blood of industry", oil has a particularly high strategic significance. After years of exploration and development, the proportion of conventional oil and gas fields has begun to decrease, and the proportion of unconventional oil and gas fields has gradually increased. However, the reservoirs of unconventional oil and gas fields have extremely complex characteristics, especially some sandstone and shale reservoirs have very complex pore structures. For deep reservoir rocks, sampling is very difficult, and traditional rock physics tests or cutting tests are very difficult to achieve when studying their properties. At this time, simulation in this regard becomes extremely important, but how to accurately construct a rock model in the simulation has become a new problem. Thanks to the advancement of CT scanning technology, digital core technology can already characterize the pore structure of rocks. However, existing technologies are all constructed for small-scale digital cores, which are difficult to use to study the macroscopic mechanical characteristics of rocks and cutting simulations.

[0003] Therefore, how to accurately construct a large-scale digital core finite element model that can be used for the study of macroscopic mechanical characteristics of rocks and cutting simulation is a technical problem that needs to be solved urgently. Summary of the invention

[0004] The present invention proposes a finite element model construction method for large-scale digital cores, which is used to solve the problem that the current simulation scale of digital cores is very small. At the same time, it describes the macroscopic pore characteristics inside the rock in great detail, thereby improving the accuracy of the rock model in the field of rock macroscopic mechanical characteristics and rock cutting research.

[0005] The present invention provides a method for constructing a finite element model of a large-scale digital core, and the technical solution includes:

[0006] S1. Obtaining core CT images

[0007] A larger sandstone core sample was collected and trimmed into a cylinder. The diameter of the cylindrical plunger of the trimmed sample was more than 15 mm. A micron-level CT scanning instrument was used to scan and obtain a grayscale image of the core.

[0008] Step S2: Perform noise reduction and enhancement processing on the original CT image

[0009] The CT image obtained in step S1 is subjected to noise reduction, smoothing and enhancement processing using three-dimensional visualization software.

[0010] After scanning, CT images need to be post-processed to improve image quality. The post-processing method mainly uses median filtering and non-local mean filtering algorithms to remove interference such as salt and pepper noise in the original image.

[0011] The quality of CT images has been greatly improved after post-processing, but in order to more easily distinguish pores from matrix (a small amount of high-density minerals in the matrix are also regarded as matrix here), the CT images need to be enhanced during processing to increase the grayscale difference between the components, which is convenient for subsequent threshold segmentation.

[0012] Step S3: Removing local micropores in the CT image after noise reduction and enhancement

[0013] After denoising and enhancing the CT image, it is also necessary to remove the tiny pores and tiny high-density minerals in the image that affect the establishment of the finite element model, and assimilate the high-density minerals into the rock matrix. A program written in PyCharm is used to cover the pores or high-density minerals smaller than a certain threshold in the CT image after denoising and enhancement with the surrounding grayscale, regardless of whether the pores are connected or isolated.

[0014] Step S4: constructing a three-dimensional shell model of the core

[0015] After the CT image is processed, the threshold segmentation method is used to divide the pores and matrix (containing high-density minerals). After repeated comparison with the original image, the threshold setting is adjusted to make the division more accurate. Finally, a three-dimensional reconstruction is performed to obtain the shell model of the core.

[0016] Step S5: Repair and optimize the shell model mesh and generate a three-dimensional finite element mesh model

[0017] For the three-dimensional shell model constructed by S4, HyperMesh is used to repair the surface mesh of the shell model, and then the shell model with the repaired surface mesh is used to generate a volume mesh model. During the generation process, the size of the mesh is controlled to obtain a finite element model with a relatively reasonable number of meshes.

[0018] Beneficial effects of the present invention:

[0019] The finite element model is constructed based on core scanning CT. The constructed model takes into account the influence of the shape and distribution of rock pores on the finite element model. Compared with the mean and inhomogeneous rock finite element models used in advanced simulations of the macroscopic physical properties of rocks, the rock model in the present invention can better reflect the actual rock situation, and can greatly improve the accuracy of rock finite element simulations such as cutting, providing important technical support for the study of rock physical properties and simulations in oil drilling, and has very broad application prospects and economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present invention will be further described below in conjunction with the accompanying drawings.

[0021] Figure 1 The accompanying drawing is a flow chart of the construction method of the present invention;

[0022] Figure 2 The attached figure is a grayscale image of the core sample after CT scanning and cutting;

[0023] Figure 3 The attached figure is a grayscale image of the core after noise reduction, smoothing and enhancement;

[0024] Figure 4 The attached figure is a grayscale image of the core after removing tiny pores;

[0025] Figure 5 The attached figure shows a three-dimensional shell model of the core constructed after assimilating high-density minerals into the matrix;

[0026] Figure 6 The attached figure is a three-dimensional mesh digital core model constructed from the shell model. DETAILED DESCRIPTION

[0027] The following is a clear and complete description of the technical solution of the present invention by taking the core of the second section of the Shahejie Formation in a certain oil field as an example. The described examples are only part of the examples of the present invention, not all of them. The examples described with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, but cannot be understood as limiting the present invention. Based on the examples in the present invention, all other examples obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] For specific implementation steps, please refer to the attached Figure 1 as follows:

[0029] Step S1: Obtaining core CT images

[0030] ① Collect sandstone core samples. There is no special requirement for the collection method of core samples, which is a conventional method.

[0031] ② After the sandstone core samples are collected, they are trimmed into cylinders and scanned using a CT scanner to obtain grayscale images of the cores. Here, the core samples are larger in size, and the diameter of the cylindrical plunger used to trim the samples is more than 15 mm. The plunger surface is cleaned, and the CT instrument resolution is selected to be 11.6 μm according to the size of the sample. Finally, a clearer grayscale image of the core is obtained after scanning, as shown in the figure. Figure 2 shown.

[0032] Step S2: Perform noise reduction and enhancement processing on the original CT image

[0033] ① After scanning, CT images need to be post-processed to improve image quality. The post-processing method mainly uses median filtering and non-local mean filtering algorithms to remove interference such as salt and pepper noise in the original image. The algorithm cycle number is not less than 5 times, but it is not limited to these two image processing methods. The specific method needs to be determined according to the specific situation of the CT image.

[0034] ② After post-processing, the quality of CT images has been greatly improved. However, in order to more easily distinguish pores from matrix (here, a small amount of high-density minerals in the matrix are also regarded as matrix), the CT images need to be enhanced during processing to increase the grayscale difference between the components, which is convenient for subsequent threshold segmentation. The black part is the pores, the gray part is the rock matrix, and the bright white part is the high-density mineral.

[0035] Figure 3 This is a grayscale image of the core after noise reduction, smoothing, and enhancement. Taking the black pores as an example, Figure 3 The pores in the Figure 2 There have been obvious changes.

[0036] Step S3: Removing local micropores in the CT image after noise reduction and enhancement

[0037] Since the proportion and area of ​​high-density minerals in the image are relatively small and their distribution is relatively scattered, retaining high-density minerals will affect the mesh quality of the subsequent construction of the finite element model. Therefore, after the CT image is denoised and enhanced, it is also necessary to remove the tiny pores and tiny high-density minerals in the image that affect the establishment of the finite element model, and assimilate the high-density minerals into the rock matrix.

[0038] PyCharm was used to write a program to remove small pores and tiny high-density minerals in CT images. The threshold for removing pores was set to an area less than 50 pixels. The image processing results are shown in Figure 2. Figure 4 shown.

[0039] Step S4: constructing a three-dimensional shell model of the core

[0040] After the CT image is processed, the pores and matrix (containing high-density minerals) are divided using the threshold segmentation method. After repeated comparison with the original image, the threshold setting is adjusted to make the division more accurate. Finally, a three-dimensional reconstruction is performed to obtain the shell model of the core and export it to STL format. The shell model is as follows: Figure 5 shown.

[0041] Step S5: Repair and optimize the shell model mesh and generate a three-dimensional finite element mesh model

[0042] ① Due to the presence of a large number of pore structures in the shell model of the constructed core, the surface mesh quality in the shell model will be relatively poor, and there will be many deformed meshes and local encryption at the pores. The surface mesh needs to be repaired before the volume mesh model can be constructed. Therefore, the aspect ratio, distortion and other factors of the surface mesh are repaired. Finally, the aspect ratio of the mesh is required to be less than 5, the distortion is less than 60°, and the Jacobian is greater than 0.6.

[0043] ②Use HyperMesh to repair the surface mesh of the shell model, and then use the shell model after surface mesh repair to generate a volume mesh model. In the process of generating, the size of the mesh is controlled. Under the condition of balancing the model accuracy and computer computing power, a finite element model with a relatively reasonable number of meshes is obtained. The finite element model is as follows: Figure 6 shown.

[0044] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

Claims

1. A method for constructing a finite element model of a large-scale digital core, characterized in that: The method comprises: S1. Obtaining core CT images Collect larger sandstone core samples, trim them into cylinders, and use micron-level CT scanning equipment to obtain grayscale images of the cores; S2. Denoise and enhance the original CT image Using three-dimensional visualization software to perform noise reduction, smoothing and enhancement processing on the CT image obtained in step S1; S3. Removal of local micropores in CT images after noise reduction and enhancement The tiny pores and tiny high-density minerals in the CT image processed in step S2 that affect the establishment of the finite element model are removed, and the high-density minerals are assimilated into the rock matrix; S4. Constructing a three-dimensional shell model of the core The CT image processed in step S3 is segmented into pores and matrix using a threshold segmentation method, and the threshold setting is adjusted after repeated comparison with the original image to make the segmentation more accurate, and finally a shell model of the core is obtained by three-dimensional reconstruction; S5. Shell model mesh repair and optimization and generation of 3D finite element mesh model For the three-dimensional shell model constructed in step S4, the surface mesh of the shell model is repaired using HyperMesh, and then the shell model after the surface mesh repair is used to generate a volume mesh model. During the generation process, the size of the mesh is controlled to obtain a finite element model with a more reasonable number of meshes.

2. The method for constructing a large-scale digital core finite element model according to claim 1, characterized in that: In the step S1, the diameter of the cylindrical plunger of the sample trimming is greater than 15 mm, and the surface of the plunger is cleaned.

3. The method for constructing a finite element model of a large-scale digital core according to claim 1, characterized in that: In step S2, the noise reduction and smoothing processing can use median filtering and non-local mean filtering algorithms to remove the salt and pepper noise interference in the original CT image, but it is not limited to these two image processing methods and needs to be determined according to the specific situation of the CT image.

4. The method for constructing a finite element model of a large-scale digital core according to claim 1, characterized in that: The specific method of step S3 is to use a program written in PyCharm to cover the tiny pores and high-density minerals in the CT image after the noise reduction and enhancement processing with the surrounding grayscale, without considering whether the pores are connected pores or isolated pores.

5. The method for constructing a finite element model of a large-scale digital core according to claim 4, characterized in that: The threshold for removing tiny pores and high-density minerals was set to an area less than 50 pixels.

6. The method for constructing a finite element model of a large-scale digital core according to claim 1, characterized in that: In step S5, the surface mesh repair includes but is not limited to the aspect ratio and distortion of the surface mesh, and the aspect ratio of the mesh is required to be less than 5, the distortion is less than 60°, and the Jacobian is greater than 0.6.

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