Rock mass microscopic deformation simulation method and system, electronic equipment and storage medium

Abstract

The invention discloses a rock mass microscopic deformation simulation method and system, electronic equipment and a storage medium, and the method comprises the steps: carrying out the computed tomography of a to-be-simulated rock, and obtaining a first microstructure image; preprocessing the first microstructure image to obtain a second microstructure image; constructing an initial digital core model according to the second microstructure image; converting the initial digital core model into a first finite element model according to a preset mapping relation, and carrying out loading calculation through the first finite element model to obtain a second finite element model; wherein the second finite element model comprises the first finite element model at different loading moments; and constructing a target digital core model according to the second finite element model, and performing rock mass deformation prediction through the target digital core model to obtain rock mass microscopic deformation data. According to the embodiment of the invention, the rock mass microscopic deformation process can be simulated, and the accuracy of rock mass microscopic deformation simulation is effectively improved. The method can be widely applied to the technical field of rock mass mechanics.

Description

Technical Field

[0001] The present application relates to the technical field of rock mechanics, and in particular to a rock micro-deformation simulation method, system, electronic equipment and storage medium. Background Art

[0002] At present, the research on rock micro-deformation is mainly divided into two categories: one is to use microscopic observation technology to observe the specimens under loading; the other is to study the micro-deformation of rock through modeling by numerical simulation. The former is mainly divided into two categories. One is to observe the specimens at different loading stages by microscopic observation, but it requires multiple microscopic observation tests, which is costly and easy to cause interference during the operation, affecting the test results; the other is to observe the specimens by microscopic observation during the loading process until the specimens are destroyed. The observation results are easily affected by the loading device and also face the problem of high cost. Therefore, in the relevant technology, numerical simulation is mainly used to study the micro-deformation of rock, but it fails to reflect the real pore structure of the rock, and the characterization of the microstructure of the rock is not accurate enough. In addition, the finite element model has vertical strain, longitudinal strain, unit deformation and misalignment between units during the loading deformation process. It is difficult to accurately obtain these subtle deformations in the finite element model.

[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the invention

[0004] The main purpose of the embodiments of the present application is to propose a rock micro-deformation simulation method, system, electronic device and storage medium, which can simulate the rock micro-deformation process and effectively improve the accuracy of rock micro-deformation simulation.

[0005] To achieve the above purpose, one aspect of an embodiment of the present application provides a method for simulating rock microscopic deformation, the method comprising the following steps:

[0006] Performing computer tomography on the simulated rock to obtain a first microstructure image;

[0007] Preprocessing the first microstructure image to obtain a second microstructure image;

[0008] constructing an initial digital core model according to the second microstructure image;

[0009] The initial digital core model is converted into a first finite element model according to a preset mapping relationship, so as to perform loading calculation through the first finite element model to obtain a second finite element model; wherein the second finite element model includes the first finite element model at different loading moments;

[0010] A target digital core model is constructed according to the second finite element model, so as to predict rock mass deformation through the target digital core model and obtain rock mass microscopic deformation data.

[0011] In some embodiments, the step of performing computer tomography on the simulated rock to obtain a first microstructure image includes:

[0012] Cutting the rock to be simulated according to preset scanning requirements to obtain a preset rock sample;

[0013] The preset rock sample is scanned layer by layer to obtain the first microstructure image.

[0014] In some embodiments, the preprocessing of the first microstructure image to obtain the second microstructure image includes:

[0015] Performing gray value optimization processing on the first microstructure image to obtain a first preprocessed image;

[0016] Performing median filtering on the first preprocessed image to obtain a second preprocessed image;

[0017] The second preprocessed image is binarized by using an adaptive threshold segmentation algorithm to obtain the second microstructure image.

[0018] In some embodiments, constructing an initial digital core model according to the second microstructure image comprises:

[0019] Extracting spatial network characteristics of rock mass pores and rock matrix according to the second microstructure image;

[0020] Calculate and obtain preset spatial network data according to the spatial network characteristics;

[0021] The initial digital core model is constructed through a volume rendering model according to the preset spatial network data.

[0022] In some embodiments, converting the initial digital core model into a first finite element model according to a preset mapping relationship, and performing loading calculation through the first finite element model to obtain a second finite element model includes:

[0023] Converting the initial digital core model into the first finite element model according to a spatial mapping relationship; wherein the spatial mapping relationship includes a one-to-one correspondence between preset voxels of the initial digital core model and finite element units of the first finite element model;

[0024] Boundary conditions are determined according to preset test parameters, so as to perform loading calculation on the first finite element model according to the boundary conditions to obtain the second finite element model.

[0025] In some embodiments, constructing a target digital core model according to the second finite element model includes:

[0026] Determining model boundary data according to the node coordinate data of the second finite element model;

[0027] Constructing a three-dimensional voxel grid according to the model boundary data and preset image parameters; wherein the preset image parameters include image size parameters and voxel space parameters;

[0028] Extracting coordinates of each finite element unit in the second finite element model to obtain finite element node coordinate information;

[0029] Calculate the position information of the finite element unit in the three-dimensional voxel grid through the finite element node coordinate information to obtain preset index information;

[0030] An affine transformation matrix is ​​constructed according to the geometric characteristic parameters of the three-dimensional voxel grid, so as to map the preset index information to the actual space coordinates through the affine transformation matrix, and construct the target digital core model.

[0031] In some embodiments, the step of predicting rock mass deformation using the target digital core model to obtain rock mass microscopic deformation data includes:

[0032] Predicting deformation of the rock mass pores and the rock matrix according to the target digital core model to obtain preset deformation data;

[0033] Data visualization is performed according to the preset deformation data to obtain rock mass microscopic deformation simulation results.

[0034] To achieve the above purpose, another aspect of the embodiment of the present application provides a rock mass micro deformation simulation system, the system comprising:

[0035] The first module is used to perform computer tomography on the simulated rock to obtain a first microstructure image;

[0036] A second module is used to preprocess the first microstructure image to obtain a second microstructure image;

[0037] A third module is used to construct an initial digital core model according to the second microstructure image;

[0038] A fourth module is used to convert the initial digital core model into a first finite element model according to a preset mapping relationship, so as to perform loading calculation through the first finite element model to obtain a second finite element model; wherein the second finite element model includes the first finite element model at different loading moments;

[0039] The fifth module is used to construct a target digital core model according to the second finite element model, so as to predict rock deformation through the target digital core model and obtain rock micro deformation data.

[0040] To achieve the above objective, another aspect of an embodiment of the present application provides an electronic device, the electronic device comprising:

[0041] at least one processor;

[0042] at least one memory for storing at least one program;

[0043] When the at least one program is executed by the at least one processor, the at least one processor implements the above method.

[0044] To achieve the above objective, another aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program implements the above method when executed by a processor.

[0045] The embodiments of the present application include at least the following beneficial effects: The present application provides a method, system, electronic device and storage medium for simulating rock micro deformation. The scheme obtains a first microstructure image by performing a computer tomography scan on the rock to be simulated, and preprocesses the first microstructure image to obtain a second microstructure image. Then, the embodiment of the present invention constructs an initial digital core model according to the second microstructure image. Then, the embodiment of the present invention converts the initial digital core model into a first finite element model according to a preset mapping relationship, so as to perform loading calculation through the first finite element model to obtain a second finite element model, including the first finite element model at different loading moments, and then constructs a target digital core model according to the second finite element model, so as to predict rock deformation through the target digital core model, obtain rock micro deformation data, and realize the simulation of the rock micro deformation process. It is easy to understand that the embodiment of the present invention can truly characterize the microstructure adjustment of the rock mass by preprocessing the first microstructure image obtained by computer tomography, and constructing the initial digital core model according to the second microstructure image obtained by the preprocessing, and effectively improve the accuracy of the calculation results. At the same time, the embodiment of the present invention converts the second finite element model obtained by loading calculation into a target digital core model, so that the subtle deformation of the finite element model during the compression deformation process can be obtained more accurately, and the microscopic deformation results can be made clearer and more intuitive, thereby effectively improving the accuracy of rock microscopic deformation simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a flow chart of a rock mass microscopic deformation simulation method provided by an embodiment of the present invention;

[0047] Figure 2 is a schematic diagram of a reef limestone sample provided by an embodiment of the present invention;

[0048] Figure 3 is a schematic diagram of an original CT image obtained by scanning a rock to be simulated provided by an embodiment of the present invention;

[0049] Figure 4 is a schematic diagram of a first preprocessed image obtained by performing grayscale value optimization according to an embodiment of the present invention;

[0050] Figure 5 is a schematic diagram of a second pre-processed image obtained by performing median filtering according to an embodiment of the present invention;

[0051] Figure 6 is a schematic diagram of a second microstructure image obtained by performing adaptive threshold segmentation according to an embodiment of the present invention;

[0052] Figure 7 is a schematic diagram of an initial digital core model established based on a CT image provided by an embodiment of the present invention;

[0053] Figure 8 is a schematic diagram of a first finite element model constructed based on an initial digital core model provided by an embodiment of the present invention;

[0054] Fig. 9 is a schematic diagram of a first finite element model after pores are deleted provided by an embodiment of the present invention;

[0055] Fig.10 It is a schematic diagram of the overall steps of the rock mass micro-deformation simulation method provided by an embodiment of the present invention;

[0056] Fig.11 is a schematic diagram of a second finite element model at t=5.0s provided in an embodiment of the present invention;

[0057] Fig.12 is a schematic diagram of local details of a second finite element model at t=5.0s provided in an embodiment of the present invention;

[0058] Fig.13 is a schematic diagram of a target digital core model at t=5.0s provided in an embodiment of the present invention;

[0059] Fig.14 is a schematic diagram of local details of the target digital core model at t=5.0s provided by an embodiment of the present invention;

[0060] Fig.15 is a schematic diagram of the porosity (t=0s) of the initial model provided in an embodiment of the present invention in the XY plane;

[0061] Fig.16is a structural schematic diagram of a rock mass microscopic deformation simulation system provided in an embodiment of the present application;

[0062] Fig.17 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are only examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the attached claims.

[0064] It is understood that the terms "first", "second", etc. used in this application can be used to describe various concepts in this article, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the embodiment of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination".

[0065] The terms "at least one", "multiple", "each", "any", etc. used in this application, at least one includes one, two or more, multiple includes two or more, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0066] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0067] Before describing the embodiments of the present application in detail, some nouns and terms involved in the embodiments of the present application are first described. The nouns and terms involved in the embodiments of the present application are subject to the following explanations.

[0068] Computed Tomography (CT) is a technology that uses ionizing radiation (mainly X-rays) as energy and uses computers to display multiple cross-sectional images to detect the internal structure of an object.

[0069] Finite element model: It is a model established when using the finite element analysis method. It is a group of monomer combinations that are connected only at nodes, transmit forces only at nodes, and are constrained only at nodes. It approximates the real physical field distribution by discretizing the continuum and solving the discrete model.

[0070] At present, the research on rock micro-deformation is mainly divided into two categories: one is to use microscopic observation technology to observe the specimens under loading; the other is to study the micro-deformation of rock through modeling by numerical simulation. The former is mainly divided into two categories. One is to observe the specimens at different loading stages by microscopic observation, but it requires multiple microscopic observation tests, which is costly and easy to cause interference during the operation, affecting the test results; the other is to observe the specimens by microscopic observation during the loading process until the specimens are destroyed. The observation results are easily affected by the loading device and also face the problem of high cost. Therefore, in the relevant technology, numerical simulation is mainly used to study the micro-deformation of rock, but it fails to reflect the real pore structure of the rock, and the characterization of the microstructure of the rock is not accurate enough. In addition, the finite element model has vertical strain, longitudinal strain, unit deformation and misalignment between units during the loading deformation process. It is difficult to accurately obtain these subtle deformations in the finite element model.

[0071] In view of this, a method, system, electronic device and storage medium for simulating rock micro-deformation are provided in an embodiment of the present application. The scheme obtains a first microstructure image by performing a computer tomography scan on the rock to be simulated, and pre-processes the first microstructure image to obtain a second microstructure image. Next, an embodiment of the present invention constructs an initial digital core model based on the second microstructure image. Then, an embodiment of the present invention converts the initial digital core model into a first finite element model according to a preset mapping relationship, so as to perform loading calculation through the first finite element model to obtain a second finite element model, including the first finite element model at different loading moments, and then constructs a target digital core model according to the second finite element model, so as to predict rock deformation through the target digital core model, obtain rock micro-deformation data, realize the simulation of the rock micro-deformation process, and effectively improve the accuracy of the rock micro-deformation simulation.

[0072] The rock micro deformation simulation method, system, electronic device and storage medium method provided in the embodiment of the present application relate to the field of rock mechanics technology. The rock micro deformation simulation method provided in the embodiment of the present application can be applied to a terminal, can also be applied to a server, and can also be software running in a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and a car terminal, etc., but is not limited to this; the server side can be configured as an independent physical server, or it can be configured as a server cluster or distributed system composed of multiple physical servers, and can also be configured as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network; the software can be an application that implements the rock micro deformation simulation method, etc., but is not limited to the above forms.

[0073] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0074] Figure 1 is an optional flow chart of the rock mechanics method provided in the embodiment of the present application. Figure 1 The method may include but is not limited to steps S110 to S150.

[0075] Step S110: Performing computer tomography scanning on the rock to be simulated to obtain a first microstructure image.

[0076] Step S120: preprocessing the first microstructure image to obtain a second microstructure image.

[0077] Step S130: constructing an initial digital core model according to the second microstructure image.

[0078] Step S140: converting the initial digital core model into a first finite element model according to a preset mapping relationship, so as to perform loading calculation through the first finite element model to obtain a second finite element model, wherein the second finite element model includes the first finite element model at different loading moments.

[0079] Step S150: constructing a target digital core model according to the second finite element model, so as to predict rock mass deformation through the target digital core model and obtain rock mass microscopic deformation data.

[0080] In the working process of this specific embodiment, the embodiment of the present invention first performs a computer tomography scan on the rock to be simulated to obtain a first microstructure image. Specifically, the rock to be simulated in the embodiment of the present invention refers to a rock that needs to be simulated for microscopic deformation of the rock mass, such as an offshore rock. For example, Figure 2 As shown, the embodiment of the present invention Figure 2A reef limestone sample in the present invention is subjected to computed tomography (CT) scanning to obtain a first microstructure image. Then, an embodiment of the present invention preprocesses the first microstructure image. A second microstructure image is obtained. Specifically, in order to further distinguish the rock matrix and pores in the transition zone, an embodiment of the present invention performs batch data preprocessing on the first microstructure image obtained by CT scanning through a preset data processing software, such as AVIZO software, to obtain a second microstructure image. Then, an embodiment of the present invention constructs an initial digital core model based on the second microstructure image. Specifically, the CT image obtained after data preprocessing, i.e., the second microstructure image, retains the structural characteristics of the rock to be simulated to the greatest extent, such as the pore-skeleton structure characteristics of the rock mass. Therefore, an embodiment of the present invention establishes a three-dimensional digital core model of the rock microstructure based on the second microstructure image, i.e., the initial digital core model. Further, an embodiment of the present invention converts the initial digital core model into a first finite element model according to a preset mapping relationship, so as to obtain a second finite element model by performing loading calculation through the first finite element model. Specifically, the embodiment of the present invention first converts the constructed initial digital core model into a first finite element model according to the spatial mapping relationship between the digital core model and the finite element model. Accordingly, the embodiment of the present invention performs loading calculation based on the established first finite element model, for example, by setting the loading and pressing speed of the loading plate, such as 3mm / min, to perform uniaxial compression on the reef limestone micro-element to obtain a second finite element model. Among them, the second finite element model in the embodiment of the present invention includes several first finite element models at different loading moments, that is, the embodiment of the present invention loads the first finite element model to obtain the first finite element model corresponding to different loading moments, and constructs the second finite element model. Finally, the embodiment of the present invention constructs a target digital core model based on the second finite element model, so as to predict the rock deformation through the target digital core model and obtain the rock microscopic deformation data. Specifically, the embodiment of the present invention constructs the target digital core model based on the first finite element model at different loading moments, that is, the second finite element model. In order to analyze the deformation process of rock mass pore-pore, the embodiment of the present invention converts the first finite element model at different times during the loading process into a digital core model, and generates a voxel representation of the model, so that the entire microscopic deformation process of the rock mass-pore can be observed, and the changes in the pore-pore of the rock mass can be more intuitive and clear. Accordingly, the embodiment of the present invention simulates the microscopic deformation of the rock mass by constructing the target digital core model to predict the microscopic deformation data of the rock mass, and visualizes the results, so that the microscopic deformation results of the rock mass are clearer and more intuitive.

[0081] In some embodiments of the present invention, computer tomography is performed on the simulated rock to obtain a first microstructure image, including but not limited to the following steps:

[0082] The rock to be simulated is cut according to the preset scanning requirements to obtain the preset rock sample.

[0083] The preset rock sample is scanned layer by layer to obtain the first microstructure image.

[0084] In this specific embodiment, the embodiment of the present invention first cuts the rock to be simulated according to the preset scanning requirements to obtain a preset rock sample, and then scans the preset rock sample layer by layer to obtain a first microstructure image. Specifically, the embodiment of the present invention performs CT scanning on the rock to be simulated to obtain a two-dimensional microstructure image of the porous medium, that is, the first microstructure image. The embodiment of the present invention cuts the rock to be simulated (such as offshore rock) according to the CT scanning test sample requirements, that is, the preset scanning requirements, to obtain a preset rock sample. Medium, the embodiment of the present invention scans the cut preset rock sample layer by layer to obtain a continuous cross-section CT image of the sample, that is, the first microstructure image. Exemplarily, in this embodiment of the present invention, the embodiment of the present invention Figure 2 The reef limestone sample in the experiment was subjected to CT scanning test, where the CT resolution was 25.00 μm. Accordingly, 4000 CT image slices were obtained after the sample was scanned layer by layer, and the pixel size of each slice was 2000×2000. Figure 3 As shown, the grayscale value distribution range of the CT image in the embodiment of the present invention is 0 to 255, wherein the portion with a grayscale value close to 0 (in black) represents the pores of the rock, and the portion with a grayscale value close to 255 (in grayish white) represents the rock matrix.

[0085] In some embodiments of the present invention, preprocessing the first microstructure image to obtain the second microstructure image includes but is not limited to the following steps:

[0086] The first microstructure image is subjected to gray value optimization processing to obtain a first preprocessed image.

[0087] Perform median filtering on the first preprocessed image to obtain a second preprocessed image.

[0088] The second preprocessed image is binarized by an adaptive threshold segmentation algorithm to obtain a second microstructure image.

[0089] In this specific embodiment, the preprocessing performed on the first microstructure image by the embodiment of the present invention includes gray value optimization processing, median filtering processing and binarization processing. Specifically, the embodiment of the present invention first performs gray value optimization processing on the first microstructure image to obtain a first preprocessed image. Figure 4As shown, the embodiment of the present invention optimizes the grayscale value of the first microstructure image, i.e., the original CT image, to enhance the contrast between the pores and the matrix. Accordingly, the grayscale value optimization in the embodiment of the present invention refers to adjusting or processing the grayscale value in the image, such as optimizing the grayscale value through a grayscaling algorithm or an image enhancement algorithm. Next, the embodiment of the present invention performs median filtering on the first preprocessed image to obtain a second preprocessed image. Among them, the embodiment of the present invention removes the ring artifacts and impulse noise in the first preprocessed image through a median filtering algorithm. Accordingly, the median filtering algorithm of the embodiment of the present invention combines the pixel values ​​of the neighborhood Np around each pixel point, sorts the pixel values ​​in the neighborhood and selects the median as the new pixel value, such as Figure 5 As shown, the second preprocessed image is obtained. Finally, the embodiment of the present invention binarizes the second preprocessed image through an adaptive threshold segmentation algorithm to obtain a second microstructure image. Among them, in order to avoid subjective errors caused by artificial threshold segmentation, the embodiment of the present invention uses an adaptive threshold segmentation algorithm to binarize the second preprocessed image. Correspondingly, the principle of the algorithm is to use the mean or median of the grayscale value within the pixel neighborhood Np as the threshold of the central pixel. When the grayscale value of the pixel is greater than the threshold, the pixel is blue (rock matrix) in the output image, otherwise the output is black (rock matrix), as shown Figure 6 As shown, a second microstructure image is obtained.

[0090] In some embodiments of the present invention, constructing an initial digital core model according to the second microstructure image includes but is not limited to the following steps:

[0091] The spatial network characteristics of rock pores and rock matrix are extracted based on the second microstructure image.

[0092] The preset spatial network data is calculated based on the spatial network characteristics.

[0093] The initial digital core model is constructed through the volume rendering model according to the preset spatial network data.

[0094] In this specific embodiment, the embodiment of the present invention first extracts the spatial network characteristics of the rock mass pores and the rock matrix according to the second microstructure image, so as to calculate the preset spatial network data according to the spatial network characteristics, and then constructs the initial digital core model through the volume rendering model according to the preset spatial network data. Specifically, the CT image after a series of operations such as gray value optimization and threshold segmentation retains the rock mass pore-skeleton structure characteristics to the greatest extent, so the embodiment of the present invention extracts the spatial network characteristics of the rock mass pores and the rock matrix through the second microstructure image. Among them, the spatial network characteristics in the embodiment of the present invention include the size, shape, connectivity, distribution, etc. of the pores, as well as the particle size and arrangement of the rock matrix. The embodiment of the present invention analyzes the second microscopic image through corresponding image processing and analysis algorithms, such as morphological operations, connected component analysis algorithms, etc., to extract the spatial network characteristics. Then, based on the extracted spatial network characteristics, the embodiment of the present invention calculates the preset spatial network data, such as porosity, permeability, and connectivity of the pore network, and calculates the spatial relationship between the rock mass pores and the rock matrix through relevant mathematical statistical algorithms to obtain the preset spatial network data. Finally, the embodiment of the present invention uses a volume rendering model (Volume Rendering) to establish a three-dimensional digital core model of the rock microstructure, that is, an initial digital core model, according to the preset spatial network data of the pores and rock matrix obtained by calculation. Figure 7 The embodiment of the present invention converts the rock microstructure in the CT image into a three-dimensional digital model through a volume rendering model, so as to intuitively display the distribution, morphological characteristics and spatial relationship of the pores inside the rock and the rock matrix.

[0095] In some embodiments of the present invention, the initial digital core model is converted into a first finite element model according to a preset mapping relationship, so as to perform loading calculation through the first finite element model to obtain a second finite element model, including but not limited to the following steps:

[0096] The initial digital core model is converted into a first finite element model according to a spatial mapping relationship, wherein the spatial mapping relationship includes a one-to-one correspondence between preset voxels of the initial digital core model and finite element units of the first finite element model.

[0097] The boundary conditions are determined according to the preset test parameters, so as to perform loading calculation on the first finite element model through the boundary conditions to obtain the second finite element model.

[0098] In this specific embodiment, the embodiment of the present invention converts the initial digital core model into a first finite element model according to the spatial mapping relationship, and determines the boundary conditions according to the preset test parameters, so as to perform loading calculation on the first finite element model through the boundary conditions to obtain a second finite element model. Specifically, the spatial mapping relationship in the embodiment of the present invention includes a one-to-one correspondence between preset voxels of the initial digital core model and finite element units of the first finite element model, that is, one voxel corresponds to one finite element unit. The embodiment of the present invention converts the initial digital core model into the first finite element model based on the spatial mapping relationship between the initial digital core model and the first finite element model, where one voxel corresponds to one finite element unit. Figure 8 Accordingly, the embodiment of the present invention deletes the pore part of the first finite element model obtained by transformation, thereby obtaining a three-dimensional finite element model of offshore rock containing a real pore structure, as shown in FIG. Fig. 9 As shown. Then, the embodiment of the present invention determines the boundary conditions based on the established first finite element model according to preset experimental parameters, such as the research purpose and the test type. For example, the embodiment of the present invention determines the boundary conditions according to a triaxial compression test, a uniaxial compression test, a Hopkins pressure bar test, etc. Finally, the embodiment of the present invention performs a loading calculation on the first finite element model according to the determined boundary conditions to obtain a second finite element model. Exemplarily, according to the spatial mapping relationship between the initial digital core model and the first finite element model, that is, one voxel corresponds to one unit, the embodiment of the present invention converts the initial digital core model into the first finite element model, such as Figure 8 As shown. Among them, Figure 7 The initial digital core model in is a cube with a side length of 2.5 mm and an image size parameter of 100×100×100. Figure 8 is the corresponding finite element model, Figure 8 The blue represents pores, the gray represents matrix, and the size of each unit in the model is 25.0 μm, with a total of 1.0×10 6 Finally, the embodiment of the present invention deletes the pore part, and then a three-dimensional finite element model of reef limestone containing a real pore structure can be obtained, such as Fig. 9 The embodiment of the present invention adopts a speed loading method, and sets the loading plate pressing speed to 3 mm / min to perform uniaxial compression on the reef limestone micro-element, thereby constructing a second finite element model.

[0099] In some embodiments of the present invention, constructing a target digital core model according to the second finite element model includes but is not limited to the following steps:

[0100] Model boundary data is determined based on the node coordinate data of the second finite element model.

[0101] A three-dimensional voxel grid is constructed according to the model boundary data and preset image parameters, wherein the preset image parameters include image size parameters and voxel space parameters.

[0102] Coordinates of each finite element unit in the second finite element model are extracted to obtain finite element node coordinate information.

[0103] The position information of the finite element unit in the three-dimensional voxel grid is calculated through the finite element node coordinate information to obtain the preset index information.

[0104] An affine transformation matrix is ​​constructed according to the geometric characteristic parameters of the three-dimensional voxel grid, so as to map the preset index information to the actual space coordinates through the affine transformation matrix, and construct the target digital core model.

[0105] In this specific embodiment, the embodiment of the present invention first determines the model boundary data according to the node coordinate data of the second finite element model. Specifically, the node coordinate data in the embodiment of the present invention includes the maximum value and the minimum value of the node coordinates. The embodiment of the present invention determines the minimum value and the maximum value of the node coordinates from the node coordinates of the second finite element model, thereby determining the boundary data of the model. Next, the embodiment of the present invention constructs a three-dimensional voxel grid according to the model boundary data and preset image parameters. Specifically, the preset image parameters in the embodiment of the present invention include image size parameters and voxel space parameters. Among them, in the embodiment of the present invention, voxels refer to basic volume elements in three-dimensional space, and voxel space parameters include voxel size parameters. Accordingly, the image size parameters in the embodiment of the present invention include the resolution or size parameters of the grid. For example, the embodiment of the present invention constructs a three-dimensional voxel grid according to the image size parameters. Among them, the image size is determined according to the size of the microscopic deformation area. Accordingly, the embodiment of the present invention calculates the voxel size and the origin coordinates by the image size and the number of voxels on the image. Among them, the origin coordinates are the coordinates of the lower left corner of the voxel grid, which are obtained by subtracting half the voxel size from the minimum coordinates. Then, the embodiment of the present invention extracts the coordinates of each finite element unit in the second finite element model to obtain the finite element node coordinate information, so as to calculate the position information of the finite element unit in the three-dimensional voxel grid through the finite element node coordinate information, and obtain the preset index information. Specifically, for each finite element unit, the embodiment of the present invention obtains the finite element node coordinate information by extracting its node coordinates in the corresponding finite element software. Accordingly, the embodiment of the present invention calculates the index of these node coordinates in the three-dimensional voxel grid. For example, the embodiment of the present invention determines the mapping relationship between the two coordinate systems according to the scaling relationship between the voxel space and the finite element model, and calculates the index of the maximum node coordinate and the minimum node coordinate of the finite element unit in the voxel grid. Among them, in the embodiment of the present invention, the node coordinate is divided by the voxel size, and rounded up or down to obtain the corresponding index. Accordingly, in the embodiment of the present invention, the minimum index is obtained by rounding down, and the maximum index is obtained by rounding up. At the same time, the embodiment of the present invention sets the values ​​of all voxels within the unit range to 1 to represent the entity area. Finally, the embodiment of the present invention constructs an affine transformation matrix based on the geometric characteristic parameters of the three-dimensional voxel grid, so as to map the preset index information to the actual space coordinates through the affine transformation matrix, and construct a target digital core model. Specifically, the embodiment of the present invention first creates an affine transformation matrix. Among them, the geometric characteristic parameters in the embodiment of the present invention include voxel size and voxel coordinates. Accordingly, the diagonal elements of the affine transformation matrix in the embodiment of the present invention are the voxel size, and the last column of the matrix is ​​the origin coordinate, and the voxel coordinates of the study area are mapped to the voxel coordinates of the entire model through the origin coordinates. Among them, the relative position relationship between voxels in the model voxel coordinates in the embodiment of the present invention is consistent with the relative position relationship between the pores and the matrix in the actual space coordinates.Therefore, the embodiment of the present invention maps the voxel index, i.e., the preset index information, to the actual space coordinates through the affine transformation matrix, and saves the corresponding three-dimensional voxel grid and the affine transformation matrix as the target digital core model. Among them, the finite element model in the embodiment of the present invention has vertical strain, longitudinal strain, unit deformation and misalignment between units during the compression deformation process. In order to obtain these subtle deformations more accurately, the embodiment of the present invention fixes the voxel size to 5μm and specifies the three-dimensional voxel grid image size parameter to be 560×560×500.

[0106] In some embodiments of the present invention, the rock mass deformation prediction is performed by using the target digital core model to obtain the rock mass microscopic deformation data, including but not limited to the following steps:

[0107] The deformation of rock mass pores and rock matrix is ​​predicted according to the target digital core model to obtain preset deformation data.

[0108] Data visualization is performed based on the preset deformation data to obtain the rock mass micro-deformation simulation results.

[0109] In this specific embodiment, the embodiment of the present invention first predicts the deformation of the rock mass pores and rock matrix according to the target digital core model to obtain preset deformation data, and then visualizes the data according to the preset deformation data to obtain the rock mass micro deformation simulation result. Specifically, the embodiment of the present invention extracts the spatial network characteristics of the rock mass pores and rock matrix to construct an initial digital core model and convert it into a first finite element model, and then loads the first finite element model to obtain finite element models at different loading moments, that is, a second finite element model. Therefore, the embodiment of the present invention analyzes the changes in the rock mass pore-rock matrix through the constructed target digital core model to obtain the corresponding preset deformation data. Then, the embodiment of the present invention visualizes the prediction results, that is, the preset deformation data, to achieve rock mass micro deformation simulation, so as to facilitate the subsequent analysis of the micro deformation of the rock mass pore-rock matrix, and can more accurately obtain the subtle deformation of the rock mass.

[0110] Next, the scheme of the embodiment of the present invention is described in detail and explained in conjunction with a specific rock mass microscopic deformation simulation scenario:

[0111] For example, Fig.10As shown, the embodiment of the present invention first performs a CT scanning test on the rock to be simulated, such as offshore rock, to obtain a CT image, i.e., a first microstructure image. Then, the embodiment of the present invention performs data preprocessing on the CT image by using preset data preprocessing software, such as AVIZO software, to obtain a second microstructure image. At the same time, the embodiment of the present invention obtains a digital core model, i.e., an initial digital core model, based on the second microstructure image and combined with a volume rendering model. Further, the embodiment of the present invention converts the constructed initial digital core model into a finite element model, i.e., a first finite element model, according to a preset interference relationship, i.e., one voxel corresponds to one finite element unit. Then, the embodiment of the present invention adds boundary conditions according to the first finite element model, and performs loading calculations to obtain finite element models at different loading times, i.e., a second finite element model. Finally, the embodiment of the present invention uses programming software such as Python or C language to process unit and node data, converts the finite element model into a digital core model, and generates a voxelized representation of the model, i.e., converts the second finite element model into a target digital core model, and converts the first finite element model at different times into a digital core model corresponding to the loading time, to obtain a target digital core model. Accordingly, the embodiment of the present invention analyzes the pore-pore changes of the rock mass by constructing a target digital core model and visualizes the results, thereby realizing the simulation of the microscopic deformation of the rock mass.

[0112] Accordingly, in order to verify the reliability and accuracy of the above method, Figure 8 Based on the finite element model in the paper, the corresponding digital core model is established and compared with the digital core model obtained by CT scanning ( Figure 7 ) for comparison, such as Fig.11 As shown. Fig.11 The porosity of the two digital core models in the CT test was compared. The average porosity of the digital core model based on the finite element model was 40.90%, while the average porosity of the digital core model obtained by the CT test was 40.98%. At the same time, the porosity of the two models in the XY plane was compared layer by layer, and it was found that the maximum porosity difference was only 1.78%. Fig.12 and Fig.13 The finite element model after simulation loading of the embodiment of the present invention is shown in FIG. Fig.14 and Fig.15 The corresponding digital core model. Fig.12 and Fig.13 and Fig.14 and Fig.15 The two types of models are highly similar in overall morphology and local slice details. Therefore, the digital core model established based on the above method can better reflect the pore-skeleton compression deformation behavior of the model during the compression simulation process.

[0113] It is easy to understand that the embodiment of the present invention can more intuitively and clearly display the changes in the pores of the rock mass and visualize the results by converting the finite element model at different loading moments into a digital core model. At the same time, the embodiment of the present invention processes the units in the finite element model through Python (but not limited to Python, and can also be replaced by programming languages ​​such as C language), and converts it into a voxel matrix, including voxel size and voxel spatial position coordinate information, and voxelizes the finite element model, and the unit micro-deformation is reflected in the voxel change, and the micro-deformation result is clearer and more intuitive. Correspondingly, compared with the existing numerical simulation method, the embodiment of the present invention establishes a model based on the CT scanning observation results, truly characterizes the microstructural characteristics of the rock mass, and the calculation results are more accurate. At the same time, since the finite element model has vertical strain, longitudinal strain, unit deformation and misalignment between units during the compression deformation process, these subtle deformations can be obtained more accurately after being converted into a digital core model. In addition, the embodiment of the present invention only requires one CT test, so that the rock mass micro-deformation is studied by modeling according to the CT test results, which significantly reduces the research cost and is more popular.

[0114] See also Fig.16 The present application also provides a rock mass micro deformation simulation system, which can implement the above rock mass micro deformation simulation method. The system includes:

[0115] The first module 210 is used to perform computer tomography on the rock to be simulated to obtain a first microstructure image.

[0116] The second module 220 is used to preprocess the first microstructure image to obtain a second microstructure image.

[0117] The third module 230 is used to construct an initial digital core model according to the second microstructure image.

[0118] The fourth module 240 is used to convert the initial digital core model into a first finite element model according to a preset mapping relationship, so as to perform loading calculation through the first finite element model to obtain a second finite element model, wherein the second finite element model includes the first finite element model at different loading moments.

[0119] The fifth module 250 is used to construct a target digital core model according to the second finite element model, so as to predict rock mass deformation through the target digital core model and obtain rock mass microscopic deformation data.

[0120] It can be understood that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0121] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above rock mass micro deformation simulation method when executing the computer program. The electronic device can be any smart terminal including a tablet computer, a car computer, etc.

[0122] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0123] See also Fig.17 , Fig.17 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0124] The processor 310 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0125] The memory 320 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 320 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 320, and the processor 310 calls and executes the rock micro deformation simulation method of the embodiment of this application;

[0126] Input / output interface 330, used to implement information input and output;

[0127] Communication interface 340, used to realize communication interaction between the device and other devices, which can be realized through wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.);

[0128] bus 350 , which transmits information between the various components of the device (e.g., processor 310 , memory 320 , input / output interface 330 , and communication interface 340 );

[0129] The processor 310 , the memory 320 , the input / output interface 330 and the communication interface 340 are connected to each other in communication within the device via the bus 350 .

[0130] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned rock micro-deformation simulation method is implemented.

[0131] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiments, the functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0132] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0133] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0134] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0135] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0136] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0137] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0138] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0139] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0140] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0141] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0142] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0143] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A method for simulating rock mass microscopic deformation, characterized in that: The method comprises the following steps: Performing computer tomography on the simulated rock to obtain a first microstructure image; Preprocessing the first microstructure image to obtain a second microstructure image; constructing an initial digital core model according to the second microstructure image; The initial digital core model is converted into a first finite element model according to a preset mapping relationship, so as to perform loading calculation through the first finite element model to obtain a second finite element model; wherein the second finite element model includes the first finite element model at different loading moments; A target digital core model is constructed according to the second finite element model, so as to predict rock mass deformation through the target digital core model and obtain rock mass microscopic deformation data.

2. The method according to claim 1, characterized in that: The method of performing computer tomography on the rock to be simulated to obtain a first microstructure image includes: Cutting the rock to be simulated according to preset scanning requirements to obtain a preset rock sample; The preset rock sample is scanned layer by layer to obtain the first microstructure image.

3. The method according to claim 1, characterized in that The preprocessing of the first microstructure image to obtain a second microstructure image includes: Performing gray value optimization processing on the first microstructure image to obtain a first preprocessed image; Performing median filtering on the first preprocessed image to obtain a second preprocessed image; The second preprocessed image is binarized by using an adaptive threshold segmentation algorithm to obtain the second microstructure image.

4. The method according to claim 1, characterized in that The step of constructing an initial digital core model according to the second microstructure image comprises: Extracting spatial network characteristics of rock mass pores and rock matrix according to the second microstructure image; Calculate and obtain preset spatial network data according to the spatial network characteristics; The initial digital core model is constructed through a volume rendering model according to the preset spatial network data.

5. The method according to claim 1, characterized in that The converting the initial digital core model into a first finite element model according to a preset mapping relationship, so as to perform loading calculation through the first finite element model to obtain a second finite element model, comprises: Converting the initial digital core model into the first finite element model according to a spatial mapping relationship; wherein the spatial mapping relationship includes a one-to-one correspondence between preset voxels of the initial digital core model and finite element units of the first finite element model; Boundary conditions are determined according to preset test parameters, so as to perform loading calculation on the first finite element model according to the boundary conditions to obtain the second finite element model.

6. The method according to claim 1, characterized in that The step of constructing a target digital core model according to the second finite element model comprises: Determining model boundary data according to the node coordinate data of the second finite element model; Constructing a three-dimensional voxel grid according to the model boundary data and preset image parameters; wherein the preset image parameters include image size parameters and voxel space parameters; Extracting coordinates of each finite element unit in the second finite element model to obtain finite element node coordinate information; Calculate the position information of the finite element unit in the three-dimensional voxel grid through the finite element node coordinate information to obtain preset index information; An affine transformation matrix is ​​constructed according to the geometric characteristic parameters of the three-dimensional voxel grid, so as to map the preset index information to the actual space coordinates through the affine transformation matrix, and construct the target digital core model.

7. The method according to claim 4, characterized in that The rock mass deformation prediction is performed by using the target digital core model to obtain rock mass microscopic deformation data, including: Predicting deformation of the rock mass pores and the rock matrix according to the target digital core model to obtain preset deformation data; Data visualization is performed according to the preset deformation data to obtain rock mass microscopic deformation simulation results.

8. A rock mass micro deformation simulation system, characterized in that: The system comprises: The first module is used to perform computer tomography on the simulated rock to obtain a first microstructure image; A second module is used to preprocess the first microstructure image to obtain a second microstructure image; A third module is used to construct an initial digital core model according to the second microstructure image; A fourth module is used to convert the initial digital core model into a first finite element model according to a preset mapping relationship, so as to perform loading calculation through the first finite element model to obtain a second finite element model; wherein the second finite element model includes the first finite element model at different loading moments; The fifth module is used to construct a target digital core model according to the second finite element model, so as to predict rock deformation through the target digital core model and obtain rock micro deformation data.

9. An electronic device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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