A method for characterizing the pore structure of hydrate sediments, an electronic processing module, and a storage medium

Abstract

The present application relates to a method for characterizing the pore structure of hydrate sediments, an electronic processing module, and a storage medium. The method includes the following steps: obtaining a first discrete element particle assembly corresponding to a hydrate-free sediment; obtaining a second discrete element particle assembly corresponding to a hydrate based on the hydrate occurrence pattern; generating a first binary data set corresponding to the first discrete element particle assembly and a second binary data set corresponding to the second discrete element particle assembly; performing a superposition operation on the first binary data set and the second binary data set based on the hydrate occurrence pattern to generate a third binary data set; and calculating hydrate sediment pore structure characterization parameters using the third binary data set. The present application can generate hydrates under a specified occurrence pattern and content, overcoming the uncertainty of the hydrate occurrence pattern in traditional methods, thereby making it possible to quantitatively analyze the impact of the hydrate occurrence pattern on pore structure and permeability.

Description

Technical Field

[0001] The present application relates to the field of natural gas hydrate mining, and in particular to a method for characterizing the pore structure of hydrate sediments, an electronic processing module, and a storage medium. Background Art

[0002] The pore structure of hydrate deposits is essential data for predicting and calculating their intrinsic permeability and the relative permeabilities of water and gas phases. This data is directly related to hydrate recovery efficiency and process control. Traditional methods typically rely on manual laboratory generation of hydrate deposits, followed by characterization of their pore structure using computed tomography (X-ray CT scanning) to obtain information such as porosity and pore space distribution.

[0003] Various methods exist for artificially synthesizing hydrates in laboratories, including the dissolved gas method, partial water saturation method, ice-seeding method, and hydrate premixing method. These methods aim to generate hydrate samples with a specified content for subsequent quantitative analysis of the relationship between hydrate content and permeability. However, because the hydrate formation process is easily affected by sample state, material composition, and control conditions, the occurrence patterns of hydrates generated by different laboratories are uncontrollable.

[0004] like Figure 1 As shown, the same sample often contains one or more hydrate occurrence modes, including particle-encapsulated, pore-filled, and patchy distribution. Studies have found that, given the same hydrate content, the permeability of hydrate deposits obtained by different methods can differ by up to 2-3 orders of magnitude. Therefore, the hydrate occurrence mode has a significant impact on the permeability of hydrate sediments. However, traditional methods are unable to generate a specific hydrate occurrence mode and therefore cannot reveal the quantitative relationship between hydrate occurrence mode and permeability, hindering the accurate prediction and scientific control of hydrate extraction efficiency. Furthermore, indoor hydrate generation methods are slow, time-consuming, and costly, and require demanding conditions.

[0005] X-ray CT scanning technology applies X-rays to a sample. Due to the varying absorption of X-rays by the sample's constituent materials (particles, hydrates, water, and gas), the intensity of the X-rays received by the receiver varies. Statistical analysis of the intensity of the received X-rays is used to obtain grayscale pixels representing the distribution of the sample's material, thereby defining the sample's pore structure. It is important to note that X-ray CT scanning technology has limited resolution (the minimum resolution is micrometers). To achieve clearer scan detail, the sample must be sufficiently small. However, excessively small sample size compromises its representativeness. Even so, materials within the sample smaller than a few micrometers cannot be detected, thus affecting the accuracy of the test results. Furthermore, X-rays generate ionizing radiation, which can be harmful to the tester if the test is not performed properly. Summary of the Invention

[0006] In order to solve the above technical problems or at least partially solve the above technical problems, the present application provides a hydrate sediment pore structure characterization method, an electronic processing module and a storage medium.

[0007] In a first aspect, the present application provides a method for characterizing the pore structure of hydrate sediments, the method comprising the steps of:

[0008] Obtaining a first discrete element particle assembly corresponding to the sediment without hydrate;

[0009] Obtaining the second discrete element particle assembly corresponding to the hydrate according to the hydrate occurrence mode;

[0010] generating a first binarized data set corresponding to the first discrete element particle assembly and a second binarized data set corresponding to the second discrete element particle assembly;

[0011] performing a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode to generate a third binary data set;

[0012] The third binarized data set is used to calculate hydrate sediment pore structure characterization parameters.

[0013] Preferably, the step of obtaining the second discrete element particle assembly corresponding to the hydrate according to the hydrate occurrence mode comprises the following steps:

[0014] Determining whether the hydrate occurrence mode is a preset mode;

[0015] If so, generating the second discrete element particle assembly based on the first discrete element particle assembly;

[0016] If not, an unconsolidated particle assembly is generated using a discrete element method as the second discrete element particle assembly.

[0017] Preferably, generating the second discrete element particle assembly according to the first discrete element particle assembly comprises the steps of:

[0018] The radius of all particles in the first discrete element particle assembly is multiplied by a coefficient K greater than 1 to obtain the second discrete element particle assembly.

[0019] Preferably, the generating of a first binary data set corresponding to the first discrete element particle assembly and a second binary data set corresponding to the second discrete element particle assembly respectively comprises the steps of:

[0020] Extracting position information of all first particles in the first discrete element particle assembly and position information of all second particles in the second discrete element particle assembly;

[0021] Performing a slicing and screenshot process on the first discrete element particle assembly according to the position information of the first particle to obtain a first slicing and screenshot;

[0022] Performing a slicing and screenshot process on the second discrete element particle assembly according to the position information of the second particle to obtain a second slicing and screenshot;

[0023] The first slice screenshot and the second slice screenshot are binarized respectively to obtain the first binarized data set and the second binarized data set.

[0024] Preferably, the step of performing a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode to generate a third binary data set comprises the following steps:

[0025] Acquire first binarized data in the first binarized data set, second binarized data in the second binarized data set, and third binarized data in the third binarized data set;

[0026] Determining whether the hydrate occurrence mode is a particle encapsulation mode;

[0027] If so, determining whether the second binarized data is 1;

[0028] If so, set the data at the same position of the third binary data to 1;

[0029] If not, the data at the same position of the third binarized data is set to 0.

[0030] Preferably, the step of performing a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode to generate a third binary data set comprises the following steps:

[0031] Acquire first binarized data in the first binarized data set, second binarized data in the second binarized data set, and third binarized data in the third binarized data set;

[0032] Determining whether the hydrate occurrence mode is a pore-filling mode;

[0033] If yes, determine whether the first binary data and the second binary data at the same position are both 0 or 1;

[0034] If so, set the data at the same position of the third binary data to 1;

[0035] If not, the data at the same position of the third binarized data is set to 0.

[0036] Preferably, the step of performing a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode to generate a third binary data set comprises the following steps:

[0037] Acquire first binarized data in the first binarized data set, second binarized data in the second binarized data set, and third binarized data in the third binarized data set;

[0038] determining whether the hydrate occurrence pattern is a patchy distribution pattern;

[0039] If so, determining whether the first binarized data and the second binarized data at the same position are both 0;

[0040] If so, set the data at the same position of the third binary data to 0;

[0041] If not, the data at the same position of the third binary data is set to 1.

[0042] In a second aspect, the present application provides an integrated module for characterizing the pore structure of hydrate sediments, comprising:

[0043] A first discrete element particle assembly acquisition module is used to obtain a first discrete element particle assembly corresponding to the sediment without hydrate;

[0044] A second discrete element particle assembly acquisition module is used to obtain a second discrete element particle assembly corresponding to the hydrate according to the hydrate occurrence mode;

[0045] A binary data set generation module, configured to generate a first binary data set corresponding to the first discrete element particle assembly and a second binary data set corresponding to the second discrete element particle assembly;

[0046] A binary data set superposition operation module, configured to perform a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode and generate a third binary data set;

[0047] The hydrate sediment pore structure characterization parameter calculation module is used to calculate the hydrate sediment pore structure characterization parameters using the third binarized data set.

[0048] According to a third aspect, an electronic processing module is provided, the electronic processing module comprising:

[0049] at least one processor; and,

[0050] a memory communicatively connected to the at least one processor; wherein,

[0051] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform any of the aforementioned methods for characterizing the pore structure of hydrate sediments.

[0052] In a fourth aspect, a non-transitory computer-readable storage medium is provided, which stores computer instructions for causing the computer to execute any of the aforementioned methods for characterizing the pore structure of hydrate sediments.

[0053] The above technical solution provided by the embodiment of the present application has the following advantages compared with the prior art:

[0054] The method provided in the embodiments of the present application can generate hydrates under specified occurrence patterns and contents, overcoming the uncertainty of hydrate occurrence patterns in traditional methods, thereby making it possible to quantitatively analyze the impact of hydrate occurrence patterns on pore structure and permeability. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0057] Figure 1 Schematic diagrams of several typical hydrate occurrence modes in the prior art;

[0058] Figure 2 A schematic flow chart of a method for characterizing the pore structure of hydrate sediments provided in an embodiment of the present application;

[0059] Figure 3 A schematic diagram of the structure of an integrated module for characterizing the pore structure of hydrate sediments provided in an embodiment of the present application;

[0060] Figure 4 A schematic diagram of a slice screenshot of a method for characterizing the pore structure of a hydrate sediment provided in an embodiment of the present application;

[0061] Figure 5 A schematic diagram of binarization processing in a method for characterizing the pore structure of hydrate sediments provided in an embodiment of the present application;

[0062] Figure 6 A schematic diagram of superposition calculation in a method for characterizing the pore structure of hydrate sediments provided in an embodiment of the present application;

[0063] Figure 7 A schematic diagram of the working effect of a method for characterizing the pore structure of hydrate sediments provided in an embodiment of the present application;

[0064] Figure 8 This is a structural diagram of an electronic processing module provided by the present invention;

[0065] Figure 9 It is a structural schematic diagram of a non-transitory computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION

[0066] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0067] Figure 2 A schematic flow chart of a method for characterizing the pore structure of hydrate sediments provided in an embodiment of the present application.

[0068] The present application provides a method for characterizing the pore structure of hydrate sediments, the method comprising the steps of:

[0069] S1: obtaining the first discrete element particle assembly corresponding to the sediment without hydrate;

[0070] In an embodiment of the present application, a discrete element method is used to generate a consolidated three-dimensional particle assembly (a first discrete element particle assembly), which is used to represent a sediment without hydrates (an idealized model in which the particles are spherical).

[0071] S2: Obtain the second discrete element particle assembly corresponding to the hydrate according to the hydrate occurrence mode;

[0072] In the embodiment of the present application, obtaining the second discrete element particle assembly corresponding to the hydrate according to the hydrate occurrence mode includes the steps of:

[0073] Determining whether the hydrate occurrence mode is a preset mode;

[0074] If so, generating the second discrete element particle assembly based on the first discrete element particle assembly;

[0075] If not, an unconsolidated particle assembly is generated using a discrete element method as the second discrete element particle assembly.

[0076] Specifically, to generate hydrates in sediments, it is necessary to establish a second discrete element particle assembly (DEA) related to the hydrate occurrence mode. According to the aforementioned prior art, hydrates primarily occur in three types of occurrence modes: particle-encapsulated, pore-filling, and patchy. For each occurrence mode, a corresponding DEA is required.

[0077] In an embodiment of the present application, generating the second discrete element particle assembly according to the first discrete element particle assembly includes the following steps:

[0078] The radius of all particles in the first discrete element particle assembly is multiplied by a coefficient K greater than 1 to obtain the second discrete element particle assembly.

[0079] Specifically, for hydrates with particle-encapsulated and pore-filling occurrence modes, a second discrete element particle assembly can be generated based on the first discrete element particle assembly. That is, the radius of all particles in the first discrete element particle assembly is multiplied by a coefficient K greater than 1 to obtain the second discrete element particle assembly. For hydrates with patchy distribution occurrence mode, an unconsolidated particle assembly needs to be regenerated as the second discrete element particle assembly. In this second discrete element particle assembly, there is no contact between particles. These particles can represent hydrates randomly generated in space, and the radius of these particles is generally larger than the radius of the particles in the first discrete element particle assembly.

[0080] S3: generating a first binarized data set corresponding to the first discrete element particle assembly and a second binarized data set corresponding to the second discrete element particle assembly;

[0081] In an embodiment of the present application, respectively generating a first binary data set corresponding to the first discrete element particle assembly and a second binary data set corresponding to the second discrete element particle assembly comprises the steps of:

[0082] Extracting position information of all first particles in the first discrete element particle assembly and position information of all second particles in the second discrete element particle assembly;

[0083] Performing a slicing and screenshot process on the first discrete element particle assembly according to the position information of the first particle to obtain a first slicing and screenshot;

[0084] Performing a slicing and screenshot process on the second discrete element particle assembly according to the position information of the second particle to obtain a second slicing and screenshot;

[0085] The first slice screenshot and the second slice screenshot are binarized respectively to obtain the first binarized data set and the second binarized data set.

[0086] Specifically, if Figure 4 and 5 , the generation process of the first binary data set and the second binary data set is the same, so for the sake of simplicity, the generation process of the first binary data set is described. First, the position information (spatial coordinates and radius) of all the first particles in the first discrete element particle assembly is extracted, and then the first discrete element particle assembly is sliced ​​and screenshoted using MATLAB programming based on the position information of the first particles. The larger the number of slices N, the higher the accuracy of the subsequent pore structure. In each first slice screenshot, the particles are represented by black and the pores are represented by white. Subsequently, each first slice screenshot is binarized using MATLAB programming. The total amount of data in each slice is N*N. During the processing, the areas where the particles and pores are located are assigned values ​​of 1 and 0, respectively. In this way, the three-dimensional pore structure information corresponding to the sediment without hydrates can be obtained, that is, the first binary data set of N*N*N binary data.

[0087] S4: performing a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode to generate a third binary data set;

[0088] Specifically, after obtaining the first and second binarized data sets corresponding to the first discrete element particle assembly and the second discrete element particle assembly, it is necessary to use MATLAB programming to perform a superposition operation on the first and second binarized data sets to obtain a third binarized data set of hydrate sediments. The third binarized data set can then be used to obtain the pore structure information of hydrate sediments under different hydrate occurrence modes.

[0089] In an embodiment of the present application, performing a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode to generate a third binary data set includes the steps of:

[0090] Acquire first binarized data in the first binarized data set, second binarized data in the second binarized data set, and third binarized data in the third binarized data set;

[0091] Determining whether the hydrate occurrence mode is a particle encapsulation mode;

[0092] If so, determining whether the second binarized data is 1;

[0093] If so, determining whether the second binarized data is 1;

[0094] If so, set the data at the same position of the third binary data to 1;

[0095] If not, the data at the same position of the third binarized data is set to 0.

[0096] Specifically, if Figure 6 In the particle wrapping mode, the superposition operation principle of the first binary data and the second binary data is: 0+0=0, 0+1=1, 1+1=1.

[0097] In an embodiment of the present application, performing a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode to generate a third binary data set includes the steps of:

[0098] Acquire first binarized data in the first binarized data set, second binarized data in the second binarized data set, and third binarized data in the third binarized data set;

[0099] Determining whether the hydrate occurrence mode is a pore-filling mode;

[0100] If yes, determine whether the first binary data and the second binary data at the same position are both 0 or 1;

[0101] If so, set the data at the same position of the third binary data to 1;

[0102] If not, the data at the same position of the third binarized data is set to 0.

[0103] Specifically, if Figure 6 In the pore filling mode, the superposition operation principle of the first binary data and the second binary data is: 0+0=1, 0+1=0, 1+1=1.

[0104] In an embodiment of the present application, performing a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode to generate a third binary data set includes the steps of:

[0105] Acquire first binarized data in the first binarized data set, second binarized data in the second binarized data set, and third binarized data in the third binarized data set;

[0106] determining whether the hydrate occurrence pattern is a patchy distribution pattern;

[0107] If so, determining whether the second binarized data is 1;

[0108] If so, determining whether the first binarized data and the second binarized data at the same position are both 0;

[0109] If so, set the data at the same position of the third binary data to 0;

[0110] If not, the data at the same position of the third binary data is set to 1.

[0111] Specifically, if Figure 6 In the patch distribution mode, the superposition operation principle of the first binary data and the second binary data is: 0+0=0, 0+1=1, 1+1=1.

[0112] S5: Calculating hydrate sediment pore structure characterization parameters using the third binarized data set.

[0113] Specifically, the porosity n of the hydrate sediment can be calculated based on the third binarized data set (porosity is equal to the ratio of the number of 0s to the total number of 0s and 1s in the data set, that is, n = No. 0 / (No. 0 + No. 1), and the spatial distribution characteristics of the pores can be obtained. These characterization parameters can be used as input data for modeling the pore network model, and then the intrinsic permeability, water retention curve, and relative permeability of water and gas phases can be calculated. In order to consider the influence of different hydrate contents, the K value can be changed for the particle encapsulation type and pore distribution type; for the patch distribution type, the size and number of particles in the unconsolidated particle aggregate can be changed.

[0114] like Figure 7 A schematic diagram of a patchy distribution hydrate occurrence pattern in a method for characterizing the pore structure of hydrate sediments provided in an embodiment of the present application.

[0115] like Figure 3 , the present application provides an integrated module for characterizing the pore structure of hydrate sediments, including:

[0116] A first discrete element particle assembly acquisition module 10 is used to obtain a first discrete element particle assembly corresponding to the sediment without hydrate;

[0117] A second discrete element particle assembly acquisition module 20 is used to acquire a second discrete element particle assembly corresponding to the hydrate according to the hydrate occurrence mode;

[0118] A binary data set generating module 30 is configured to generate a first binary data set corresponding to the first discrete element particle assembly and a second binary data set corresponding to the second discrete element particle assembly;

[0119] A binary data set superposition operation module 40 is configured to perform a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode and generate a third binary data set;

[0120] The hydrate sediment pore structure characterization parameter calculation module 50 is used to calculate the hydrate sediment pore structure characterization parameters using the third binarized data set.

[0121] The present application provides an integrated module for characterizing the pore structure of hydrate sediments, which can execute the aforementioned method for characterizing the pore structure of hydrate sediments.

[0122] Reference below Figure 8, which shows a schematic diagram of the structure of an electronic processing module 100 suitable for implementing the embodiments of the present disclosure. The electronic processing module in the embodiments of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 8 The electronic processing module shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0123] like Figure 8 As shown, the electronic processing module 100 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 101, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 102 or a program loaded from a storage device 108 into a random access memory (RAM) 103. Various programs and data required for the operation of the electronic processing module 100 are also stored in the RAM 103. The processing device 101, the ROM 102, and the RAM 103 are connected to each other via a bus 104. An input / output (I / O) interface 105 is also connected to the bus 104.

[0124] Typically, the following devices may be connected to I / O interface 105: input device 106 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output device 107 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage device 108 including, for example, a magnetic tape, hard disk, etc.; and communication device 109. Communication device 109 may allow electronic processing module 100 to communicate with other devices wirelessly or by wire to exchange data. Although the figures illustrate electronic processing module 100 with various devices, it should be understood that not all of the illustrated devices are required to be implemented or present. More or fewer devices may alternatively be implemented or present.

[0125] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network via the communication device 109, or installed from the storage device 108, or installed from the ROM 102. When the computer program is executed by the processing device 101, the above-mentioned functions defined in the method of the embodiment of the present disclosure are performed.

[0126] Reference below Figure 9, which shows a structural schematic diagram of a computer-readable storage medium suitable for implementing an embodiment of the present disclosure, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it can implement the hydrate sediment pore structure characterization method as described in any of the above.

[0127] Compared with the traditional indoor artificial hydrate generation method, the method for characterizing the pore structure of hydrate sediments provided by the present application is more controllable and can generate hydrates under specified occurrence patterns and contents, overcoming the uncertainty of the hydrate occurrence pattern in the traditional method, thereby making it possible to quantitatively analyze the impact of the hydrate occurrence pattern on the pore structure and permeability. In addition, the method proposed in the present invention is simpler and more efficient, avoiding the harsh conditions required by the indoor method and the defects of the slow hydrate generation rate, greatly saving experimental and time costs. Compared with the method of characterizing the pore structure of hydrate sediments by traditional X-ray CT scanning technology, the method proposed in the present invention is not limited by resolution, so it can capture details ignored by X-ray CT scanning technology, thereby making the pore structure information of the obtained hydrate sediments more complete and accurate. In addition, the method proposed in the present invention is safer and more reliable, will not cause any harm to the human body, and saves experimental and time costs.

[0128] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0129] The foregoing description is intended only to provide specific embodiments of the present invention, which will enable those skilled in the art to understand and implement the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown herein, but is intended to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for characterizing the pore structure of hydrate sediments, characterized in that: The method comprises the steps of: Obtaining a first discrete element particle assembly corresponding to the sediment without hydrate; Obtaining the second discrete element particle assembly corresponding to the hydrate according to the hydrate occurrence mode; generating a first binarized data set corresponding to the first discrete element particle assembly and a second binarized data set corresponding to the second discrete element particle assembly; performing a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode to generate a third binary data set; Calculating hydrate sediment pore structure characterization parameters using the third binarized data set; The method of obtaining the second discrete element particle assembly corresponding to the hydrate according to the hydrate occurrence mode comprises the following steps: Determining whether the hydrate occurrence mode is a preset mode; If so, generating the second discrete element particle assembly based on the first discrete element particle assembly; If not, generating an unconsolidated particle assembly as the second discrete element particle assembly using a discrete element method; The step of generating the second discrete element particle assembly according to the first discrete element particle assembly comprises the following steps: Multiplying the radius of all particles in the first discrete element particle assembly by a coefficient K greater than 1 to obtain the second discrete element particle assembly; The step of respectively generating a first binary data set corresponding to the first discrete element particle assembly and a second binary data set corresponding to the second discrete element particle assembly comprises the following steps: Extracting position information of all first particles in the first discrete element particle assembly and position information of all second particles in the second discrete element particle assembly; Performing a slicing and screenshot process on the first discrete element particle assembly according to the position information of the first particle to obtain a first slicing and screenshot; Performing a slicing and screenshot process on the second discrete element particle assembly according to the position information of the second particle to obtain a second slicing and screenshot; The first slice screenshot and the second slice screenshot are binarized respectively to obtain the first binarized data set and the second binarized data set.

2. The method for characterizing the pore structure of hydrate sediments according to claim 1, characterized in that: The performing a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode to generate a third binary data set comprises the following steps: Acquire first binarized data in the first binarized data set, second binarized data in the second binarized data set, and third binarized data in the third binarized data set; Determining whether the hydrate occurrence mode is a particle encapsulation mode; If so, determining whether the second binarized data is 1; If so, set the data at the same position of the third binary data to 1; If not, the data at the same position of the third binarized data is set to 0.

3. The method for characterizing the pore structure of hydrate sediments according to claim 1, characterized in that: The performing a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode to generate a third binary data set comprises the following steps: Acquire first binarized data in the first binarized data set, second binarized data in the second binarized data set, and third binarized data in the third binarized data set; Determining whether the hydrate occurrence mode is a pore-filling mode; If yes, determine whether the first binary data and the second binary data at the same position are both 0 or 1; If so, set the data at the same position of the third binary data to 1; If not, the data at the same position of the third binarized data is set to 0.

4. The method for characterizing the pore structure of hydrate sediments according to claim 1, characterized in that: The performing a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode to generate a third binary data set comprises the following steps: Acquire first binarized data in the first binarized data set, second binarized data in the second binarized data set, and third binarized data in the third binarized data set; determining whether the hydrate occurrence pattern is a patchy distribution pattern; If so, determining whether the first binarized data and the second binarized data at the same position are both 0; If so, set the data at the same position of the third binary data to 0; If not, the data at the same position of the third binary data is set to 1.

5. A hydrate sediment pore structure characterization device for use in the method according to any one of claims 1 to 4, characterized in that: include: A first discrete element particle assembly acquisition module is used to obtain a first discrete element particle assembly corresponding to the sediment without hydrate; A second discrete element particle assembly acquisition module is used to obtain a second discrete element particle assembly corresponding to the hydrate according to the hydrate occurrence mode; A binary data set generation module, configured to generate a first binary data set corresponding to the first discrete element particle assembly and a second binary data set corresponding to the second discrete element particle assembly; A binary data set superposition operation module, configured to perform a superposition operation on the first binary data set and the second binary data set according to the hydrate occurrence mode and generate a third binary data set; The hydrate sediment pore structure characterization parameter calculation module is used to calculate the hydrate sediment pore structure characterization parameters using the third binarized data set.

6. An electronic processing module, characterized in that: The electronic processing module includes: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the hydrate sediment pore structure characterization method according to any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable the computer to execute the method for characterizing the pore structure of hydrate sediments according to any one of claims 1 to 4.

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