A hybrid natural gas hydrate grid model generation method and related device

Abstract

The application discloses a mixed natural gas hydrate grid model generation method and related equipment, and the method comprises the following steps: obtaining preset parameters, and constructing target skeleton sphere data according to the preset parameters; constructing a pore-hydrate structure component; obtaining the shape ratio of a first hydrate and a second hydrate, and generating a first hydrate standard component and a second hydrate standard component; obtaining a preset ratio, and constructing a first hydrate component and a second hydrate component according to the preset ratio, the skeleton sphere data, the first hydrate standard component and the second hydrate standard component; and combining the pore-hydrate structure component, the first hydrate component and the second hydrate component to obtain a target hydrate model. The natural gas hydrate grid model conforming to a certain range of porosity and mixed hydrate ratio is automatically constructed, and method support is provided for commercial development and numerical simulation prediction of natural gas hydrate.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of natural gas hydrate, and particularly relates to a mixed natural gas hydrate grid model generation method and related equipment. BACKGROUND

[0002] Natural gas hydrate is a clean energy and is widely distributed in the southeast coastal areas of China. Therefore, the commercial development of natural gas hydrate has important practical significance for improving China's energy structure, ensuring China's energy security, achieving the "double carbon" goal, and reducing carbon dioxide emissions. The key to the development of natural gas hydrate is to break the in-situ stable conditions to promote the decomposition of hydrate, thereby discharging natural gas, so the research on the decomposition mechanism and gas-water migration law of natural gas hydrate is the premise of realizing the efficient exploitation of natural gas hydrate.

[0003] In the prior art, the research on natural gas hydrate usually adopts indoor experiments and numerical simulation methods to study the decomposition and gas-water migration law of natural gas hydrate. Among them, the indoor experiment can more truly simulate the physical and mechanical properties of natural gas hydrate, so as to reveal the decomposition and transport law under the action of multiple factors, provide theoretical reference for the exploitation of natural gas hydrate reservoir, and provide parameters and mathematical model for numerical simulation research. However, the indoor experiment is limited by the limitations of specimen preparation, instrument equipment and other aspects, and usually has a very high cost problem, so it is difficult to realize the decomposition and transport law research under the action of multiple factors in the full parameter range in batches. Therefore, numerical simulation research is an effective research method which can comprehensively consider the advantages of cost and reliability. The main difficulties in the numerical simulation research of natural gas hydrate include the differential characterization of natural gas hydrate decomposition and transport law and the micro characterization of complex natural gas hydrate structure. Among them, the differential characterization of natural gas hydrate decomposition and transport law is mainly realized by solving the corresponding mathematical model, and the microstructure of natural gas hydrate is also a difficulty in numerical simulation. According to the existing research results, under the macroscopic perspective, natural gas hydrate may present blocky, layered, dispersed and other situations, and under the microscopic perspective, the occurrence mode of natural gas hydrate can be divided into cemented type, pore filling type and particle bearing type. Therefore, when constructing the natural gas hydrate model for numerical simulation research, the accurate micro characterization of natural gas hydrate and its adjacent pore structure is the premise of accurately predicting the decomposition and transport mechanism of natural gas hydrate under the action of multiple factors. At present, the natural gas hydrate models constructed in domestic and foreign researches are mostly single type hydrate models, such as particle wrapped hydrate model or filling type hydrate model. However, the structure of natural gas hydrate in the real environment may contain multiple types of hydrate particles at the same time. Therefore, the existing research results cannot obtain a mixed natural gas hydrate grid model closer to the actual situation.

[0004] Therefore, the prior art remains to be improved and enhanced. SUMMARY

[0005] In view of the above defects of the prior art, the present application provides a hybrid natural gas hydrate grid model generation method and related equipment, aiming to solve the problem that there is no generation method of a hybrid natural gas hydrate grid model in the prior art, and it is difficult to predict the decomposition and transport mechanism of natural gas hydrate under the combined action of multiple factors in a theoretical interval by combining numerical simulation technology.

[0006] To solve the above technical problems, the technical solutions adopted by the present application are as follows:

[0007] In a first aspect of the present application, a hybrid natural gas hydrate grid model generation method is provided, which comprises:

[0008] Obtaining preset parameters, the preset parameters including model range and sphere parameters, and constructing target skeleton sphere data according to the preset parameters;

[0009] Constructing pore-hydrate structure components according to the model range and the target skeleton sphere data;

[0010] Obtaining the morphological proportion of first hydrate and second hydrate, and generating first hydrate standard components and second hydrate standard components according to the morphological proportion of the first hydrate and the second hydrate;

[0011] Obtaining a preset proportion, and constructing first hydrate components and second hydrate components according to the preset proportion, the skeleton sphere data, the first hydrate standard components and the second hydrate standard components;

[0012] Combining the pore-hydrate structure components, the first hydrate components and the second hydrate components to obtain a target hydrate model.

[0013] The hybrid natural gas hydrate grid model generation method, wherein the sphere parameters include a sphere particle size list, a minimum sphere number and a minimum sphere skeleton proportion, and the sphere skeleton proportion is the proportion of the volume occupied by the sphere to the model range.

[0014] The hybrid natural gas hydrate grid model generation method, wherein the construction of the target skeleton sphere data according to the preset parameters comprises:

[0015] Randomly generating a plurality of non-intersecting first spheres according to the sphere particle size list, and obtaining first sphere parameters including sphere number, sphere center coordinates of each first sphere and sphere particle size;

[0016] determining whether the current number of spheres and the current proportion of sphere skeletons satisfy a first preset condition;

[0017] If the first preset condition is not satisfied, a second sphere is randomly generated, and it is determined whether the second sphere satisfies a second preset condition.

[0018] The step of determining whether the current number of spheres and the current proportion of sphere skeletons satisfy the first preset condition is re-executed until the current number of spheres and the current proportion of sphere skeletons satisfy the first preset condition.

[0019] The distance between the center coordinates of each sphere and the center coordinates of the remaining spheres is sequentially detected, and if the distance is greater than the particle diameter sum, the distance to a target sphere is obtained, the target sphere is the sphere closest to the current sphere, the particle diameter of the current sphere is increased to be adjacent to the target sphere, and the target skeleton sphere data is obtained, wherein, and the target skeleton sphere data includes the center coordinates of each sphere and the particle diameter data of the sphere.

[0020] The mixed natural gas hydrate grid model generation method, wherein the second sphere is randomly generated, including:

[0021] A random point in the model range is generated as the center of the second sphere, and the particle diameter of the current second sphere is randomly obtained according to the preset sphere particle diameter list;

[0022] The intersection relationship between the second sphere and the current skeleton sphere is detected, and if the intersection relationship exists, the second sphere is deleted, and the step of generating a random point in the model range as the center of the second sphere is repeatedly executed until the second sphere does not intersect with the current skeleton sphere.

[0023] The mixed natural gas hydrate grid model generation method, wherein the first preset condition is:

[0024] The current number of spheres is greater than the minimum number of spheres, and the current proportion of sphere skeletons is greater than the minimum proportion of sphere skeletons.

[0025] The second preset condition is that the second sphere does not intersect with the current existing sphere.

[0026] The mixed natural gas hydrate grid model generation method, wherein the pore-hydrate structure component is constructed according to the model range and the target skeleton sphere data, including:

[0027] A cubic component is obtained according to the model range, the cubic component is gridded to obtain a discrete grid model component;

[0028] The unit search function in the sphere is used to obtain a target characteristic skeleton set according to the target skeleton sphere data.

[0029] The units in the target characteristic skeleton set are deleted in the discrete grid model component to obtain the pore-hydrate structure component.

[0030] The mixed natural gas hydrate grid model generation method, wherein the first hydrate component and the second hydrate component are constructed according to the preset proportion, the skeleton sphere data, the first hydrate standard component and the second hydrate standard component, and the method comprises the following steps of:

[0031] The target skeleton sphere data is divided into first skeleton sphere data and second skeleton sphere data according to the preset proportion, the preset proportion is the quantity proportion of the first hydrate and the second hydrate, the first skeleton sphere data comprises the spherical center coordinate and the spherical particle size data of each first skeleton sphere, and the second skeleton sphere data comprises the spherical center coordinate and the spherical particle size data of each second skeleton sphere;

[0032] The first skeleton sphere data is traversed, the first hydrate standard component is scaled according to the first skeleton sphere data, a plurality of first hydrate models with the same spherical particle size as the first skeleton sphere data are obtained, the first hydrate models are randomly rotated and then translated to the positions of the corresponding first skeleton spheres respectively, and the first hydrate component is obtained;

[0033] The second skeleton sphere data is traversed, the second hydrate standard component is scaled according to the second skeleton sphere data, a plurality of second hydrate models with the same spherical particle size as the second skeleton sphere data are obtained, the second hydrate models are randomly rotated and then translated to the positions of the corresponding first skeleton spheres respectively, and the second hydrate component is obtained.

[0034] The second aspect of the present application provides a mixed natural gas hydrate grid model generation device, comprising:

[0035] A sphere data construction module is configured to obtain preset parameters, wherein the preset parameters comprise a model range and sphere parameters, and the target skeleton sphere data is constructed according to the preset parameters.

[0036] A pore-hydrate construction module is configured to construct a pore-hydrate structure component according to the model range and the target skeleton sphere data.

[0037] a hydrate construction module, configured to acquire a shape ratio of a first hydrate and a second hydrate, generate a first hydrate standard component and a second hydrate standard component according to the shape ratio of the first hydrate and the second hydrate;

[0038] acquire a preset ratio, and construct a first hydrate component and a second hydrate component according to the preset ratio, the skeleton sphere data, the first hydrate standard component and the second hydrate standard component;

[0039] a hydrate model acquisition module, configured to combine the pore-hydrate structure component, the first hydrate component and the second hydrate component to obtain a target hydrate model.

[0040] In a third aspect, the present application provides a terminal, comprising a processor, a computer readable storage medium connected with the processor, the computer readable storage medium is adapted to store a plurality of instructions, the processor is adapted to call the instructions in the computer readable storage medium, to execute the steps of the mixed natural gas hydrate grid model generation method.

[0041] In a fourth aspect, the present application provides a computer readable storage medium, the computer readable storage medium stores one or more programs, the one or more programs can be executed by one or more processors to implement the steps of the mixed natural gas hydrate grid model generation method.

[0042] Compared with the prior art, the application provides a hybrid natural gas hydrate grid model generation method and related equipment, in which, by acquiring preset parameters, the preset parameters include model range and sphere parameters, target skeleton sphere data is constructed according to the preset parameters; according to the model range and the target skeleton sphere data, a pore-hydrate structure component is constructed, then the shape proportion of a first hydrate and a second hydrate is acquired, after generating a first hydrate standard component and a second hydrate standard component according to the shape proportion of the first hydrate and the second hydrate, a preset proportion is acquired, according to the preset proportion, the skeleton sphere data, the first hydrate standard component and the second hydrate standard component, a first hydrate component and a second hydrate component are constructed, and finally the pore-hydrate structure component, the first hydrate component and the second hydrate component are combined to obtain a target hydrate model. The hybrid natural gas hydrate grid model generation method provided by the application can automatically construct a natural gas hydrate grid model meeting a certain range of porosity and a hybrid hydrate proportion, can facilitate the numerical simulation research of an ideal hybrid hydrate grid model, can facilitate the research of natural gas hydrate decomposition and transport mechanism under the influence of multiple factors, can provide method support for the commercial development and numerical simulation prediction of natural gas hydrate, and solves the problem that in the prior art, there is no generation method of a hybrid natural gas hydrate grid model, and it is difficult to predict the natural gas hydrate decomposition and transport mechanism under the comprehensive action of multiple factors in a theoretical interval by combining numerical simulation technology. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 The flowchart of the embodiment of the hybrid natural gas hydrate grid model generation method provided by the application;

[0044] Figure 2 The test flowchart of the embodiment of the hybrid natural gas hydrate grid model generation method provided by the application;

[0045] Figure 3 The skeleton sphere data acquisition flowchart of the embodiment of the hybrid natural gas hydrate grid model generation method provided by the application;

[0046] Figure 4 The standard sphere component diagram of the embodiment of the hybrid natural gas hydrate grid model generation method provided by the application;

[0047] Figure 5 The sphere skeleton component diagram of the embodiment of the hybrid natural gas hydrate grid model generation device provided by the application;

[0048] Figure 6A study area cubic part figure of the embodiment of the mixed natural gas hydrate grid model generation device provided by the present application;

[0049] Figure 7 A pore-hydrate structure part figure of the embodiment of the mixed natural gas hydrate grid model generation device provided by the present application;

[0050] Figure 8 A first type hydrate standard part figure of the embodiment of the mixed natural gas hydrate grid model generation device provided by the present application;

[0051] Figure 9 A second type hydrate standard part figure of the embodiment of the mixed natural gas hydrate grid model generation device provided by the present application;

[0052] Figure 10 A first type hydrate combined part figure of the embodiment of the mixed natural gas hydrate grid model generation device provided by the present application;

[0053] Figure 11 A second type hydrate combined part figure of the embodiment of the mixed natural gas hydrate grid model generation device provided by the present application;

[0054] Figure 12 A hydrate part figure of the embodiment of the mixed natural gas hydrate grid model generation device provided by the present application;

[0055] Figure 13 A hydrate grid model figure of the embodiment of the mixed natural gas hydrate grid model generation device provided by the present application;

[0056] Figure 14 A structure principle figure of the embodiment of the mixed natural gas hydrate grid model generation device provided by the present application;

[0057] Figure 15 A principle schematic figure of the embodiment of the terminal provided by the present application. DETAILED DESCRIPTION

[0058] In order to make the objectives, technical solutions and effects of the present application clearer and more explicit, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0059] The mixed natural gas hydrate grid model generation method provided by the application can be applied to a terminal with computing capability, and the terminal can execute the mixed natural gas hydrate grid model generation method provided by the application to obtain a target densification point and transmit the target densification point to a target motion control card. The terminal can be various computers, mobile terminals, smart home appliances, wearable devices, and the like.

[0060] Embodiment one

[0061] As shown in the mixed natural gas hydrate grid model generation method, one embodiment includes the following steps: Figure 1

[0062] S100, obtain preset parameters, the preset parameters include model range and sphere parameters, and target skeleton sphere data is constructed according to the preset parameters.

[0063] Referring to Figure 2 In this embodiment, the model range and sphere parameters need to be set first, the sphere parameters include a sphere particle size list, a minimum sphere number and a minimum sphere skeleton ratio, wherein the sphere skeleton ratio is the ratio of the sphere volume to the model range.

[0064] The terminal obtains the preset parameters, and then constructs the target skeleton sphere data according to the preset parameters. The skeleton sphere data includes a model unit for constructing a pore-hydrate structure component and the sphere center position, sphere particle size and the like of each sphere in the pore-hydrate structure component.

[0065] The target skeleton sphere data is constructed according to the preset parameters, including:

[0066] S110, a plurality of non-intersecting first spheres are randomly generated according to the sphere particle size list, and first sphere parameters are obtained, the first sphere parameters include sphere number, sphere center coordinates and sphere particle size of each first sphere.

[0067] Referring to Figure 3 After the model range and sphere parameters are set, the terminal randomly generates initial spheres according to the model range and sphere parameters. Specifically, a point in the model range is randomly generated as the sphere center of the initial sphere, and a particle size in the sphere particle size list is randomly called as the sphere particle size of the initial sphere. In this embodiment, the initial sphere is a first sphere, and each first sphere is non-intersecting. After a plurality of first spheres are generated, the parameters of the first spheres are obtained, wherein the first sphere parameters include sphere number, sphere center coordinates and sphere particle size of each first sphere.

[0068] ​S120, determine whether the current number of spheres and the current sphere skeleton ratio meet a first preset condition.

[0069] The first preset condition is:

[0070] The current number of spheres is greater than the minimum number of spheres and the current sphere skeleton ratio is greater than the minimum sphere skeleton ratio.

[0071] Specifically, after generating the first sphere, since the first sphere is randomly generated, it is necessary to detect whether the particle size, number, and skeleton ratio meet the expected value. That is, to detect whether the current number of spheres and its volume ratio are lower than the minimum number of spheres or the minimum sphere skeleton ratio.

[0072] S130, if the first preset condition is not met, a second sphere is randomly generated, it is determined whether the second sphere meets a second preset condition, and if the second preset condition is met, the current second sphere data is added to the current skeleton sphere data.

[0073] The second preset condition is that the second sphere does not intersect with the current existing sphere.

[0074] The second sphere is randomly generated, including:

[0075] S131, a random point in the model range is generated as the center of the second sphere, and a sphere size of the current second sphere is randomly obtained according to a preset sphere size list;

[0076] S132, the intersection relationship between the second sphere and the current skeleton sphere is detected, if there is intersection, the second sphere is deleted, and the step of generating a random point in the model range as the center of the second sphere is repeated until the second sphere does not intersect with the current skeleton sphere.

[0077] Specifically, when the first preset condition is not met, that is, the current number of spheres is less than the minimum number of spheres or the current sphere skeleton ratio is less than the minimum sphere skeleton ratio, a new sphere needs to be generated in the model range to meet the first preset condition. Specifically, if the first preset condition is not met, a random point is generated in space as a new sphere center, and a new sphere size is retrieved from the sphere size list as a new sphere size, and the new sphere is set as a second sphere. Then, the intersection relationship between the second sphere and the existing sphere is detected, if there is intersection, the current sphere data is deleted and a random point is generated as a new sphere center, and the foregoing steps are repeated. If there is no intersection, the current second sphere data is added to the current skeleton sphere data.

[0078] S140, re-performing the step of judging whether the current number of spheres and the current proportion of sphere skeletons satisfy the first preset condition until the current number of spheres and the current proportion of sphere skeletons satisfy the first preset condition.

[0079] In the embodiment, after adding one sphere data, it is necessary to detect again whether the existing number of spheres and the proportion of skeletons are lower than the set number or the proportion of skeletons. If not, new sphere center data is continuously generated randomly until the current number of spheres and the current proportion of sphere skeletons satisfy the first preset condition. Then, the total number of spheres, the sphere center coordinates, and the sphere diameter in the current skeleton sphere data are obtained.

[0080] S150, sequentially detecting whether the distance between the sphere center coordinates of each sphere and the sphere center coordinates of the remaining spheres is greater than the sum of the particle diameters, if all are greater than the sum of the particle diameters, obtaining the distance from the target sphere, the target sphere being the sphere closest to the current sphere, increasing the particle diameter of the current sphere to be adjacent to the target sphere to obtain the target skeleton sphere data, wherein, so the target skeleton sphere data includes the sphere center coordinates and the sphere particle diameter data of each sphere.

[0081] Specifically, assuming that the current total number of spheres is n, whether the distance between each sphere and the remaining spheres is greater than the sum of the radii is sequentially traversed, and if it is greater than the sum of the radii, the sphere radius is increased to be adjacent, and accordingly the skeleton sphere diameter data can be obtained.

[0082] Herein Figure 1 , the mixed natural gas hydrate grid model generation method further includes the steps of:

[0083] S200, constructing a pore-hydrate structure component according to the model range and the target skeleton sphere data.

[0084] In the embodiment, the internal sketch plotting function of abaqus is used, as shown in Figure 4 , a two-dimensional semicircle and its axis are constructed, and a standard component of a single sphere or ellipsoidal particle with a scale of unit 1 is generated by rotating around the axis for standby. As shown in Figure 5 , according to the target skeleton sphere data, a plurality of standard components are translated one by one to the sphere center position of the current skeleton sphere and scaled to the corresponding sphere particle diameter size by using the translation and scaling method, to obtain a sphere skeleton component with randomly distributed sphere diameters and positions. At the same time, a cubic component is generated according to the set model range, as shown in Figure 6 . Subsequently, the cubic component is hollowed inside according to the body sphere skeleton component by using Boolean operation, so as to obtain the pore-hydrate structure component, which is set as component 0, as shown in Figure 7 .

[0085] The pore-hydrate structure component is constructed according to the model range and the target skeleton sphere data, including:

[0086] obtaining a cubic component according to the model range, meshing the cubic component to obtain a discrete mesh model component;

[0087] obtaining a target characteristic skeleton set according to the target skeleton sphere data by using a sphere-in-cell lookup function;

[0088] deleting cells in the target characteristic skeleton set from the discrete mesh model component to obtain the pore-hydrate structure component.

[0089] Specifically, the cubic component is obtained according to the model range, and the cubic component is hexahedron meshed and further extracted as the discrete mesh model component. Then, the target characteristic skeleton set is obtained according to the target skeleton sphere data by using a sphere-in-cell lookup function, and the hexahedron cell set of the pore-hydrate structure component is obtained by deleting cells in the set through mesh editing.

[0090] S300, obtaining a shape ratio of a first hydrate and a second hydrate, and generating a first hydrate standard component and a second hydrate standard component according to the shape ratio of the first hydrate and the second hydrate.

[0091] The shape ratio of the first hydrate and the second hydrate is obtained. In this embodiment, the shape of the first hydrate is as shown in FIG. 1, which is a shape of no ball in the center position and 6 balls outside. The shape of the second hydrate is as shown in FIG. 2, which is a multi-layer ball nesting shape. Figure 8 Figure 9 The shape of the second hydrate is as shown in FIG. 2, which is a multi-layer ball nesting shape. Specifically, according to the obtained inner-outer ball diameter ratio of the first hydrate, a first hydrate standard component with no ball in the center position, 6 balls outside, and an outer diameter of 1 is obtained by copying and translating, and the first hydrate standard component is a discrete adjacent hydrate component. At the same time, according to the obtained separation length of each layer of the second hydrate, the second hydrate standard component in the nested type is obtained by merging after multi-layer ball nesting and retaining the boundary.

[0092] S400, obtaining a preset ratio, and constructing a first hydrate component and a second hydrate component according to the preset ratio, the skeleton sphere data, the first hydrate standard component, and the second hydrate standard component.

[0093] The preset ratio is a preset quantity ratio of the first hydrate and the second hydrate.

[0094] The construction of the first hydrate component and the second hydrate component according to the preset ratio, the skeleton sphere data, the first hydrate standard component, and the second hydrate standard component includes:

[0095] ​S410, divide the target skeleton sphere data into first skeleton sphere data and second skeleton sphere data according to the preset proportion, the preset proportion being a quantity proportion of the first hydrate and the second hydrate, the first skeleton sphere data including a sphere center coordinate and a sphere particle size data of each first skeleton sphere, and the second skeleton sphere data including a sphere center coordinate and a sphere particle size data of each second skeleton sphere;

[0096] S420, traverse the first skeleton sphere data, and scale the first hydrate standard component according to the first skeleton sphere data to obtain a plurality of first hydrate models with the same sphere particle size as each sphere in the first skeleton sphere data, and translate each first hydrate model to a corresponding first skeleton sphere position after randomly rotating the first hydrate model to obtain the first hydrate component;

[0097] S430, traverse the second skeleton sphere data, and scale the second hydrate standard component according to the second skeleton sphere data to obtain a plurality of second hydrate models with the same sphere particle size as each sphere in the second skeleton sphere data, and translate each second hydrate model to a corresponding first skeleton sphere position after randomly rotating the second hydrate model to obtain the second hydrate component.

[0098] Specifically, based on the target skeleton sphere data, the target skeleton sphere data is divided into two parts, first skeleton sphere data and second skeleton sphere data, according to the proportion of the first type and the second type of hydrate. Traverse each part of data respectively, and scale the first hydrate standard component and the second hydrate standard component according to the sphere diameter. After randomly rotating the first hydrate standard component and the second hydrate standard component, translate according to the sphere center data to obtain the first hydrate component composed of a plurality of first hydrate models and the second hydrate component composed of a plurality of second hydrate models. At the same time, the detailed sphere center and sphere diameter parameters of the first hydrate component and the second hydrate component are obtained.

[0099] Specifically, referring to Figure 10 , the first hydrate is circumscribed spherical, and according to the assigned first hydrate proportion, the radius of the circumscribed sphere in the first hydrate, and the relative position setting, the list of adjacent particle positions of the first hydrate is traversed, and a single first hydrate model is generated according to each position information and hydrate parameter information in turn to further obtain the first hydrate component. Referring to Figure 11The second hydrate is nested, and first, according to the proportion of the second hydrate, the center and radius list of the second hydrate required are obtained by using the center and radius list of the skeleton sphere. Then, according to the multi-layer sphere radius list in the second hydrate, the nested sphere components representing the second hydrate are sequentially generated by traversing the foregoing list. Finally, all the second hydrate models are combined to form the final second hydrate component.

[0100] S500, the pore-hydrate structure component, the first hydrate component and the second hydrate component are combined to obtain a target hydrate model.

[0101] In the embodiment, the target hydrate model is a grid model.

[0102] The first hydrate component and the second hydrate component are respectively constructed as a first hydrate hexahedron unit set and a second hydrate hexahedron unit set. Different unit sets are created as new components, including hexahedron grids representing the pore-hydrate structure component, the first hydrate component and the second hydrate component, and finally the pore-hydrate structure component, the first hydrate component and the second hydrate component are combined as a new grid model to obtain a target hydrate model, which is a mixed natural gas hydrate grid model as shown in Figure 12 、 Figure 13 .

[0103] In another embodiment, the pore-hydrate structure component, the first hydrate component and the second hydrate component can not be converted into a grid model, but the first hydrate component and the second hydrate component are assembled together, and their intersection component is obtained by Boolean operation. After reassembly, the redundant part is deleted. Thus, the pure pore-hydrate structure component, the first hydrate component and the second hydrate component are obtained, and the pore-hydrate structure component, the first hydrate component and the second hydrate component are assembled together to form the target hydrate model as shown in Figure 6 , and after further grid subdivision, the grid model of the target hydrate model, i.e. the mixed natural gas hydrate grid model, is obtained.

[0104] In summary, the embodiment provides a mixed natural gas hydrate grid model generation method, the method obtains preset parameters, the preset parameters include model range and sphere parameters, constructs target skeleton sphere data according to the preset parameters; constructs pore-hydrate structure components according to the model range and the target skeleton sphere data, then obtains the shape proportion of the first hydrate and the second hydrate, generates the first hydrate standard component and the second hydrate standard component according to the shape proportion of the first hydrate and the second hydrate, obtains a preset proportion, constructs the first hydrate component and the second hydrate component according to the preset proportion, the skeleton sphere data, the first hydrate standard component and the second hydrate standard component, and finally combines the pore-hydrate structure components, the first hydrate component and the second hydrate component to obtain a target hydrate model. The mixed natural gas hydrate grid model generation method provided in the embodiment can automatically construct a natural gas hydrate grid model meeting a certain range of porosity and mixed hydrate proportion, can facilitate the numerical simulation research of the ideal mixed hydrate grid model, can facilitate the research on the decomposition and transport mechanism of natural gas hydrate under the influence of multiple factors, can provide method support for the commercial development and numerical simulation prediction of natural gas hydrate, solves the problem that there is no mixed natural gas hydrate grid model generation method in the prior art, and it is difficult to predict the decomposition and transport mechanism of natural gas hydrate under the comprehensive action of multiple factors in the theoretical interval by combining numerical simulation technology.

[0105] It should be understood that, although each step in the flowchart shown in the drawings of the present application specification is shown in sequence according to the arrow, these steps are not necessarily executed in sequence according to the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other sequences. Moreover, at least part of the steps in the flowchart can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence of these sub-steps or stages is not necessarily sequential, but can be executed in rotation or alternation with other steps or at least part of the sub-steps or stages of other steps.

[0106] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0107] Example 2

[0108] Based on the above embodiments, the present invention also provides a hybrid natural gas hydrate mesh model generation device, such as... Figure 14 As shown, the hybrid natural gas hydrate mesh model generation device includes:

[0109] A sphere data construction module is used to obtain preset parameters, including model range and sphere parameters, and to construct target skeleton sphere data based on the preset parameters, as described in Embodiment 1.

[0110] A pore-hydrate construction module is used to construct pore-hydrate structural components based on the model range and the target skeleton sphere data, as specifically described in Example 1;

[0111] A hydrate construction module is used to obtain the morphological ratio of a first hydrate and a second hydrate, and to generate standard components of a first hydrate and a second hydrate based on the morphological ratio of the first hydrate and the second hydrate.

[0112] According to the preset proportion, the skeleton sphere data, the first hydrate standard component and the second hydrate standard component, a first hydrate component and a second hydrate component are constructed, and details are described in Embodiment I.

[0113] A hydrate model obtaining module is configured to combine the pore-hydrate structure component, the first hydrate component and the second hydrate component to obtain a target hydrate model, and details are described in Embodiment I.

[0114] Embodiment III

[0115] Based on the above embodiments, the application further provides a terminal, as shown in the accompanying drawings. Figure 15 The terminal includes a processor 10 and a memory 20. Figure 15 Only some components of the terminal are shown, but it should be understood that all the shown components are not required, and more or fewer components can be alternatively implemented.

[0116] The memory 20 can be an internal storage unit of the terminal in some embodiments, such as a hard disk or a memory of the terminal. The memory 20 can also be an external storage device of the terminal in other embodiments, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 20 can include both an internal storage unit and an external storage device of the terminal. The memory 20 is used to store application software and various data installed on the terminal. The memory 20 can also be used to temporarily store data that has been output or will be output. In an embodiment, a hybrid natural gas hydrate grid model generation program 30 is stored on the memory 20, and the hybrid natural gas hydrate grid model generation program 30 can be executed by the processor 10 to implement the hybrid natural gas hydrate grid model generation method in the application.

[0117] The processor 10 can be a central processing unit (CPU), a microprocessor or other chip in some embodiments, and is used to run program codes or process data stored in the memory 20, such as executing the super-resolution image quality evaluation method, etc.

[0118] In an embodiment, referring to the flowchart of Figure 15 When the processor 10 executes the hybrid natural gas hydrate grid model generation program 30 in the memory 20, the following steps are implemented.

[0119] obtaining preset parameters, the preset parameters including a model range and sphere parameters, and constructing target skeleton sphere data according to the preset parameters;

[0120] constructing a pore-hydrate structure component according to the model range and the target skeleton sphere data;

[0121] obtaining a morphological ratio of a first hydrate and a second hydrate, and generating a first hydrate standard component and a second hydrate standard component according to the morphological ratio of the first hydrate and the second hydrate;

[0122] obtaining a preset ratio, and constructing a first hydrate component and a second hydrate component according to the preset ratio, the skeleton sphere data, the first hydrate standard component and the second hydrate standard component;

[0123] combining the pore-hydrate structure component, the first hydrate component and the second hydrate component to obtain a target hydrate model.

[0124] The sphere parameters include a sphere particle size list, a minimum sphere number and a minimum sphere skeleton ratio, wherein the sphere skeleton ratio is a ratio of a sphere volume to the model range.

[0125] The constructing target skeleton sphere data according to the preset parameters includes:

[0126] randomly generating a plurality of first spheres that do not intersect according to the sphere particle size list, and obtaining first sphere parameters, the first sphere parameters including a sphere number, a sphere center coordinate of each first sphere and a sphere particle size;

[0127] determining whether a current sphere number and a current sphere skeleton ratio satisfy a first preset condition;

[0128] If the first preset condition is not satisfied, a second sphere is randomly generated, and it is determined whether the second sphere satisfies a second preset condition, and if the second preset condition is satisfied, the current second sphere data is added to the current skeleton sphere data;

[0129] The step of determining whether the current sphere number and the current sphere skeleton ratio satisfy the first preset condition is re-executed until the current sphere number and the current sphere skeleton ratio satisfy the first preset condition;

[0130] sequentially detecting whether the distance between the center coordinate of each sphere and the center coordinate of the rest of the spheres is greater than the particle diameter sum, if all are greater than the particle diameter sum, obtaining the distance from the target sphere, the target sphere being the sphere closest to the current sphere, increasing the particle diameter of the current sphere to be adjacent to the target sphere to obtain the target skeleton sphere data, wherein, so the target skeleton sphere data includes the center coordinate of each sphere and its sphere particle diameter data.

[0131] wherein, the second sphere is randomly generated, including:

[0132] generating a random point in the model range as the center of the second sphere, and randomly obtaining the sphere particle diameter of the current second sphere according to the preset sphere particle diameter list;

[0133] detecting the intersection relationship between the second sphere and the current skeleton sphere, if intersecting, deleting the second sphere, and repeating the step of generating a random point in the model range as the center of the second sphere until the second sphere does not intersect with the current skeleton sphere.

[0134] wherein, the first preset condition is:

[0135] the current number of spheres is greater than the minimum number of spheres and the current skeleton ratio of spheres is greater than the minimum skeleton ratio of spheres;

[0136] the second preset condition is that the second sphere does not intersect with the current existing sphere.

[0137] wherein, the pore-hydrate structure component is constructed according to the model range and the target skeleton sphere data, including:

[0138] a cubic component is obtained according to the model range, the cubic component is meshed to obtain a discrete mesh model component;

[0139] a target representation skeleton set is obtained according to the target skeleton sphere data by using a sphere-in-cell lookup function;

[0140] the cells in the target representation skeleton set are deleted in the discrete mesh model component to obtain the pore-hydrate structure component.

[0141] wherein, the first hydrate component and the second hydrate component are constructed according to the preset ratio, the skeleton sphere data, the first hydrate standard component and the second hydrate standard component, including:

[0142] According to the preset proportion, the target skeleton sphere data is divided into first skeleton sphere data and second skeleton sphere data, the preset proportion is the quantity proportion of the first hydrate and the second hydrate, the first skeleton sphere data includes the sphere center coordinate and the sphere particle size data of each first skeleton sphere, and the second skeleton sphere data includes the sphere center coordinate and the sphere particle size data of each second skeleton sphere;

[0143] The first hydrate standard part is scaled according to the first skeleton sphere data by traversing the first skeleton sphere data, a plurality of first hydrate models with the same sphere particle size as the first skeleton sphere data are obtained, each first hydrate model is translated to the corresponding first skeleton sphere position after being randomly rotated, and the first hydrate part is obtained.

[0144] The second hydrate standard part is scaled according to the second skeleton sphere data by traversing the second skeleton sphere data, a plurality of second hydrate models with the same sphere particle size as the second skeleton sphere data are obtained, each second hydrate model is translated to the corresponding first skeleton sphere position after being randomly rotated, and the second hydrate part is obtained.

[0145] Embodiment four

[0146] The application further provides a computer readable storage medium, wherein one or more programs are stored, the one or more programs can be executed by one or more processors to implement the steps of the mixed natural gas hydrate grid model generation method.

[0147] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for generating a hybrid natural gas hydrate mesh model, characterized in that, The method includes: Obtain preset parameters, including model range and sphere parameters, and construct target skeleton sphere data based on the preset parameters; The sphere parameters include a list of sphere diameters, a minimum number of spheres, and a minimum sphere skeleton ratio, wherein the sphere skeleton ratio is the ratio of the volume occupied by the spheres to the model range; Construct a pore-hydrate structure component based on the model range and the target skeleton sphere data; Obtain the morphological ratio of the first hydrate and the second hydrate, and generate standard components of the first hydrate and the second hydrate based on the morphological ratio of the first hydrate and the second hydrate. Obtain a preset ratio, and construct a first hydrate component and a second hydrate component based on the preset ratio, the target skeleton sphere data, the first hydrate standard component, and the second hydrate standard component; The pore-hydrate structure component, the first hydrate component, and the second hydrate component are combined to obtain the target hydrate model; The step of constructing the target skeleton sphere data according to the preset parameters includes: Multiple non-intersecting first spheres are randomly generated based on the sphere particle size list, and the parameters of the first spheres are obtained. The first sphere parameters include the number of spheres, the center coordinates of each first sphere, and the particle size of the sphere. Determine whether the current number of spheres and the current proportion of the sphere skeleton meet the first preset condition; If the first preset condition is not met, a second sphere is randomly generated, and it is determined whether the second sphere meets the second preset condition. If the second preset condition is met, the current second sphere data is added to the current skeleton sphere data. Repeat the step of determining whether the current number of spheres and the current proportion of the sphere skeleton meet the first preset condition until the current number of spheres and the current proportion of the sphere skeleton meet the first preset condition. The distance between the center coordinates of each sphere and the center coordinates of the other spheres is sequentially checked to see if it is greater than the sum of the particle sizes. If it is greater than the sum of the particle sizes, the distance to the target sphere is obtained. The target sphere is the sphere closest to the current sphere. The particle size of the current sphere is increased to be adjacent to the target sphere to obtain the target skeleton sphere data. The target skeleton sphere data includes the center coordinates of each sphere and its particle size data. The construction of the first hydrate component and the second hydrate component based on the preset ratio, the target skeleton sphere data, the first hydrate standard component, and the second hydrate standard component includes: The target skeleton sphere data is divided into first skeleton sphere data and second skeleton sphere data according to the preset ratio. The preset ratio is the quantity ratio of the first hydrate and the second hydrate. The first skeleton sphere data includes the center coordinates of each first skeleton sphere and its sphere diameter data. The second skeleton sphere data includes the center coordinates of each second skeleton sphere and its sphere diameter data. Traverse the first skeleton sphere data, scale the first hydrate standard component according to the first skeleton sphere data to obtain multiple first hydrate models with the same particle size as each sphere in the first skeleton sphere data, randomly rotate the first hydrate model and translate each first hydrate model to the corresponding first skeleton sphere position to obtain the first hydrate component. Traverse the second skeleton sphere data, scale the second hydrate standard component according to the second skeleton sphere data to obtain multiple second hydrate models with the same particle size as each sphere in the second skeleton sphere data, randomly rotate the second hydrate model and translate each second hydrate model to the corresponding first skeleton sphere position to obtain the second hydrate component.

2. The method for generating a hybrid natural gas hydrate mesh model according to claim 1, characterized in that, The random generation of the second sphere includes: A random point is generated within the model range as the center of the second sphere, and the particle size of the current second sphere is randomly obtained according to the preset particle size list. Detect the intersection relationship between the second sphere and the current skeleton sphere. If they intersect, delete the second sphere and repeat the step of generating a random point as the center of the second sphere within the model range until the second sphere and the current skeleton sphere no longer intersect.

3. The method for generating a hybrid natural gas hydrate mesh model according to claim 1, characterized in that, The first preset condition is: The current number of spheres is greater than the minimum number of spheres and the current sphere skeleton ratio is greater than the minimum sphere skeleton ratio; The second preset condition is: the second sphere does not intersect with any existing sphere.

4. The method for generating a hybrid natural gas hydrate mesh model according to claim 1, characterized in that, The construction of the pore-hydrate structure component based on the model range and the target skeleton sphere data includes: Based on the model range, a cubic component is obtained, and the cubic component is meshed to obtain a discrete mesh model component; Using a sphere cell lookup function, the target representation skeleton set is obtained based on the target skeleton sphere data; The cells in the target characterization skeleton set are deleted from the discrete mesh model component to obtain the pore-hydrate structure component.

5. A hybrid natural gas hydrate mesh model generation device, characterized in that, include: A sphere data construction module is used to obtain preset parameters, including model range and sphere parameters, and construct target skeleton sphere data based on the preset parameters. The sphere parameters include a list of sphere diameters, a minimum number of spheres, and a minimum sphere skeleton ratio, wherein the sphere skeleton ratio is the ratio of the volume occupied by the spheres to the model range; A pore-hydrate construction module, which is used to construct pore-hydrate structural components based on the model range and the target skeleton sphere data; A hydrate construction module is used to obtain the morphological ratio of a first hydrate and a second hydrate, and to generate standard components of a first hydrate and a second hydrate based on the morphological ratio of the first hydrate and the second hydrate. Obtain a preset ratio, and construct a first hydrate component and a second hydrate component based on the preset ratio, the target skeleton sphere data, the first hydrate standard component, and the second hydrate standard component; A hydrate model acquisition module is used to combine the pore-hydrate structure component, the first hydrate component, and the second hydrate component to obtain a target hydrate model. The step of constructing the target skeleton sphere data according to the preset parameters includes: Multiple non-intersecting first spheres are randomly generated based on the sphere particle size list, and the parameters of the first spheres are obtained. The first sphere parameters include the number of spheres, the center coordinates of each first sphere, and the particle size of the sphere. Determine whether the current number of spheres and the current proportion of the sphere skeleton meet the first preset condition; If the first preset condition is not met, a second sphere is randomly generated, and it is determined whether the second sphere meets the second preset condition. If the second preset condition is met, the current second sphere data is added to the current skeleton sphere data. Repeat the step of determining whether the current number of spheres and the current proportion of the sphere skeleton meet the first preset condition until the current number of spheres and the current proportion of the sphere skeleton meet the first preset condition. The distance between the center coordinates of each sphere and the center coordinates of the other spheres is sequentially checked to see if it is greater than the sum of the particle sizes. If it is greater than the sum of the particle sizes, the distance to the target sphere is obtained. The target sphere is the sphere closest to the current sphere. The particle size of the current sphere is increased to be adjacent to the target sphere to obtain the target skeleton sphere data. The target skeleton sphere data includes the center coordinates of each sphere and its particle size data. The construction of the first hydrate component and the second hydrate component based on the preset ratio, the target skeleton sphere data, the first hydrate standard component, and the second hydrate standard component includes: The target skeleton sphere data is divided into first skeleton sphere data and second skeleton sphere data according to the preset ratio. The preset ratio is the quantity ratio of the first hydrate and the second hydrate. The first skeleton sphere data includes the center coordinates of each first skeleton sphere and its sphere diameter data. The second skeleton sphere data includes the center coordinates of each second skeleton sphere and its sphere diameter data. Traverse the first skeleton sphere data, scale the first hydrate standard component according to the first skeleton sphere data to obtain multiple first hydrate models with the same particle size as each sphere in the first skeleton sphere data, randomly rotate the first hydrate model and translate each first hydrate model to the corresponding first skeleton sphere position to obtain the first hydrate component. Traverse the second skeleton sphere data, scale the second hydrate standard component according to the second skeleton sphere data to obtain multiple second hydrate models with the same particle size as each sphere in the second skeleton sphere data, randomly rotate the second hydrate model and translate each second hydrate model to the corresponding first skeleton sphere position to obtain the second hydrate component.

6. A terminal, characterized in that, The terminal includes: a processor and a computer-readable storage medium communicatively connected to the processor. The computer-readable storage medium is adapted to store multiple instructions, and the processor is adapted to invoke the instructions in the computer-readable storage medium to execute the steps of the method for generating a hybrid natural gas hydrate grid model according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores one or more programs, which can be executed by one or more processors to implement the steps of the method for generating a hybrid natural gas hydrate grid model as described in any one of claims 1-4.

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