Method and device for automatic planning of land seismic vibrator travel route

Abstract

The application discloses an automatic planning method and device for a walking route of a land controllable seismic source, and belongs to the field of physical exploration. The application introduces a TSP idea, and finally obtains a seismic source vehicle driving route which is short in path, less in barrier crossing, less in driving restriction, and in line with the driving operation habit of a driver through steps of constructing a map, setting relevant parameters and weight ratios, and solving the walking route of the land controllable seismic source by using a TNH combination algorithm. The application combines the advantages of a two-approximation algorithm, a Heuristic algorithm and an NSGA_II algorithm to propose the TNH combination algorithm for solving the walking route of the land controllable seismic source, so that the automatic planning of the walking route of the controllable seismic source is realized, the operation efficiency is accelerated, the accuracy of operation results is improved, the calculated route is more in line with the demand of field construction, and the exploration operation is further developed intelligently. The application is applied to the field of physical exploration to plan the walking route of the controllable seismic source.

Description

Technical Field

[0001] This invention belongs to the field of geophysical exploration and relates to a method for planning the movement route of a controllable seismic source, specifically an automatic planning method and device for the movement route of a controllable seismic source in an exploration block. Background Technology

[0002] In the oil exploration industry, seismic source work is required for geological exploration. Seismic source vehicles need to travel along specific routes to each seismic source point. However, these routes must not only be free of obstructions but also be designed to be rational, minimizing unnecessary travel. Traditional seismic source route planning involves manually connecting the seismic source points one by one. This method is not only inefficient but also prone to unavoidable human errors due to the large amount of wiring work.

[0003] The Traveling Salesman Problem (TSP) is a classic combinatorial optimization problem, widely used in various fields such as logistics and transportation route optimization, urban planning and tourism route planning, and production scheduling process sequence optimization. However, traditional TSP problem-solving methods have the following drawbacks: (1) High time and computational resource consumption: Traditional TSP algorithms usually use exhaustive search or dynamic programming to find the optimal solution. These methods require a lot of time and computational resources when dealing with large-scale problems because the complexity of the problem increases exponentially; (2) High labor costs: Traditional methods usually rely on manual intervention, such as manually planning routes or making complex adjustments, which leads to high labor costs, especially when dealing with complex problems; (3) Difficulty in handling constraints: If the TSP problem has additional constraints, such as limiting the time of vehicle travel or avoiding obstacles, traditional methods cannot easily integrate these constraints and require additional complex processing. Therefore, although traditional TSP problem-solving algorithms can obtain relatively good route solutions, in practical applications, these algorithms consume a lot of time and computational resources, making practical operation difficult. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide an automatic planning method for the controllable seismic source travel route in exploration blocks based on the TSP (Transmission of Seismic Project) approach, so as to solve the problems of high time and computing resource consumption, high labor costs and difficulty in handling constraints in the practical application of traditional TSP problem algorithms, and improve the efficiency and accuracy of seismic source vehicle route planning.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] An automatic planning method for the travel route of a controllable seismic source on land, the planning method comprising the following steps performed sequentially:

[0007] S1. Building the Map

[0008] Based on basic geographic information data, the planning area is divided into two types of terrain: passable areas and obstacle areas. The number and location of earthquake focal points are determined, and a map is constructed.

[0009] S2. Introduce the concept of the TSP problem, and set relevant parameters and their weights.

[0010] Each seismic source point is treated as a node, and the obstacle area is treated as an edge. Parameters including the shortest path between two nodes, turning angle, and obstacle avoidance are set, and the weight of each parameter is determined.

[0011] S3.TNH combined algorithm for solving the travel path of a controllable land seismic source

[0012] Based on the set relevant parameters and weight ratios, the travel path of the controllable seismic source on land is obtained by combining the two approximation algorithm, the NSGA-II algorithm and the Heuristic algorithm.

[0013] The basic implementation of the two approximation algorithm is to first find a minimum spanning tree, then perform an Euler traversal on that tree, and finally remove duplicate edges to obtain the solution to the TSP. The Heuristic algorithm is a greedy heuristic algorithm for TSP. The basic idea of ​​this algorithm is to continuously swap two nodes in the path until the path length can no longer be optimized. However, it cannot guarantee a globally optimal solution because it may get stuck in a local optimum and be unable to escape. The NSGA-II algorithm is a multi-objective optimization algorithm. The basic idea is to generate a new population through crossover and mutation operations of the genetic algorithm, and use methods such as non-dominated sorting and crowding distance to perform multi-objective optimization.

[0014] Each of the three algorithms mentioned above has its own advantages and disadvantages. Therefore, this invention proposes the TNH combined algorithm by combining the advantages of the two approximation algorithm, the Heuristic algorithm, and the NSGA_Ⅱ algorithm. This algorithm significantly solves the drawbacks of the above-mentioned individual solution methods, speeds up the calculation efficiency, improves the accuracy of the calculation results, and makes the calculated route more suitable for the actual use case.

[0015] As a first limitation of the automatic planning method for the walking route of the controllable seismic source on land, in step S1, the obstacle area can be simplified into linear or planar elements, and only the seismic source point to be reached, the prohibition line and the prohibition surface remain on these maps.

[0016] As a further limitation of the first limitation of the automatic planning method for the travel route of the controlled seismic source on land, in step S1, the geometric nodes of the obstacle area can be thinned to simplify the calculation, thereby ensuring that subsequent topological operations such as minimum path and intersection are as fast as possible.

[0017] As a second limitation on the automatic planning method for the travel route of the controlled seismic source on land, in step S2, the obtained Euclidean distance is used as the shortest path between the two nodes.

[0018] As a further limitation of the second limitation on the automatic planning method for the travel route of the controlled seismic source on land, the determination of the Euclidean distance includes the following two cases;

[0019] In the first case, when the line connecting two nodes p1(x1, y1, z1) and p2(x2, y2, z2) does not intersect the obstacle area, the Euclidean distance is calculated according to Formula 1:

[0020]

[0021] In the second case, when the line connecting two nodes p1(x1, y1, z1) and p2(x2, y2, z2) intersects the obstacle area, the Euclidean distance is calculated according to Formula 2:

[0022]

[0023] The second scenario is defined this way to address situations where there are too many obstacles and no way out, in which case the route will choose a way to forcibly cross the obstacles.

[0024] As a third limitation on the automatic planning method for the path of a controllable seismic source on land, in step S2, in the traditional TSP approach, the actual operation only searches for the next point near a current point. We define a search radius, such as 50m, and only search the data within the radius, stopping the search after finding a point. To ensure the optimal selection of the shortest path, this invention defines a minimum number of searches, such as 5, in the above situation. After defining the minimum number of searches, when using a certain point as the initial point and searching the data within a specified radius: if the number of satisfactory endpoints within the search radius exceeds 5, then at least 5 points are provided to the algorithm program for selection, and the most suitable point is selected; if the number of satisfactory endpoints within the search radius is less than 5, then all satisfactory points are provided to the algorithm program for selection, instead of determining the point after finding one, multiple points are found for comparison, and the most suitable point is selected.

[0025] As a fourth limitation on the automatic planning method for the movement route of the controlled seismic source on land, step S3 includes the following steps:

[0026] S31. Based on the set relevant parameters and weight ratios, an initial land-based controllable seismic source travel path is obtained through a two-approximation algorithm, which is used as the first-generation individual;

[0027] S32. Based on the NSGA-II algorithm, the aforementioned first-generation individuals are used as part of the parent generation for crossover during the genetic process to generate new paths;

[0028] S33. The new paths generated in the first generation of individuals are locally optimized using the Heuristic algorithm to obtain the optimized land-controlled seismic source travel path, which is the land-controlled seismic source travel route planned by the automatic planning method.

[0029] When combining the TSP method with the two approximation algorithm, Heuristic algorithm, and NSGA_II algorithm, many difficulties are often encountered. This invention solves these difficulties through the following method:

[0030] Challenge 1. Algorithm integration and coordination: Integrating different algorithms into a unified solution requires ensuring that they can work together effectively without interfering with or contradicting each other;

[0031] The solution proposed in this invention is as follows: To effectively integrate the two approximation algorithms, Heuristic, and NSGA_II, this invention defines clear interfaces and data exchange mechanisms to ensure that different algorithms can effectively share information and results. In addition, the parameters of the algorithms are adjusted and optimized to ensure that different algorithms do not conflict when working together. For example, the cross-operation of NSGA_II and the local optimization of Heuristic need to cooperate with each other to avoid compromising the quality of the solution.

[0032] Challenge 2. Computational resources and performance: Combining multiple algorithms may increase the demand for computational resources, especially when dealing with large-scale problems, which may lead to performance degradation;

[0033] The solution proposed in this invention is to reduce the demand for computing resources through reasonable resource management and algorithm parameter adjustment. This invention controls computational costs by limiting the number of iterations or the population size of NSGA_Ⅱ. Furthermore, it employs parallel computing to improve performance by distributing computational tasks of different algorithms to multiple processors or threads to accelerate computation.

[0034] Challenge 3. Problem specificity: Different problems may require different combinations of algorithms and parameter settings. A combination may be effective for one problem, but not for another.

[0035] The solution proposed in this invention involves analyzing and experimenting with specific problems to determine the optimal algorithm combination and parameter settings. An adaptive approach is used, selecting appropriate algorithms and parameter configurations based on the nature and scale of the problem. For example, when there are more than 5 types of obstacles, the obstacle accessibility level is selected; when there are more than 3 types of roads, the road priority level is selected; when the obstacle coverage area exceeds 50%, the maximum search range parameter is recommended to be reduced to 80,000, and the computation time limit parameter is recommended to be 6 minutes; when the coverage area exceeds 70%, the maximum search range parameter is recommended to be reduced to 50,000, and the computation time limit parameter is recommended to be 10 minutes; other parameter settings can remain unchanged.

[0036] Challenge 4. Convergence and optimization quality: Different algorithms may have different convergence speeds and optimization qualities. It is necessary to ensure that the overall algorithm can converge to a high-quality solution within a reasonable time.

[0037] The solution proposed in this invention is to balance the optimization performance of different algorithms through meticulous algorithm design and parameter tuning. For example, in NSGA_Ⅱ, parameters such as crossover probability and mutation probability are adjusted to affect convergence speed and diversity; in the Heuristic algorithm, a more refined local search strategy is introduced to improve optimization quality.

[0038] In summary, this invention overcomes the difficulties encountered when combining algorithms such as the two approximation algorithm, Heuristic algorithm, and NSGA_Ⅱ algorithm through careful problem analysis, algorithm optimization, and reasonable resource management, and achieves more efficient problem solving. It has also achieved good results in the practical application of solving the travel path of a controlled seismic source on land, improving the efficiency and accuracy of solving the travel path of a controlled seismic source on land.

[0039] This invention also provides an apparatus for automatically planning the path of a controllable land seismic source using the aforementioned method. The apparatus includes a map construction module, a module for setting relevant parameters and their weighting percentages, a TNH combined algorithm module for solving the path of a controllable land seismic source, and a central control module.

[0040] The map construction module is used to divide the planning area into two types of terrain, namely passable areas and obstacle areas, based on basic geographic information data, to determine the number and location of earthquake source points and construct a map.

[0041] The module for setting relevant parameters and their weight ratios is used to treat each seismic source point as a node and the obstacle area as an edge, setting parameters including the shortest path between two nodes, turning angle, and obstacle avoidance, and determining the weight ratio of each parameter.

[0042] The TNH combined algorithm module for solving the land-based controllable seismic source travel route is used to solve for the land-based controllable seismic source travel route by combining the two approximation algorithm, the NSGA-II algorithm, and the Heuristic algorithm.

[0043] The central control module is equipped with control software modules used to control the signal flow and data processing in the map construction module, the module for setting relevant parameters and their weight ratios, and the module for solving the land controllable seismic source travel route using the TNH combined algorithm.

[0044] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described automatic planning method for the travel route of a controllable land seismic source.

[0045] The present invention also provides a computer-readable storage medium storing a computer program that performs the automatic planning method for the travel route of a controllable land seismic source as described above.

[0046] By adopting the above technical solution, the technical progress achieved by this invention compared with the prior art is as follows:

[0047] ① To address the issues of excessive time and computational resources consumed by commonly used algorithms for automatically planning the route of seismic source vehicles and solving the TSP problem, this invention introduces the TSP approach to solve these problems. Specifically, by combining the advantages of the two approximation algorithm, the Heuristic algorithm, and the NSGA_Ⅱ algorithm, a TNH combined algorithm is proposed to solve the route of controllable seismic sources on land, enabling automatic planning of controllable seismic source routes. The application of this method not only accelerates computational efficiency but also improves the accuracy of the calculation results. Furthermore, the calculated route is more suitable for actual use, promoting the further development of intelligent exploration operations.

[0048] ② In this invention, the path is first initialized using a two-approximation algorithm. This is because the two-approximation algorithm is a heuristic method that can quickly generate an initial solution, significantly reducing the initial solution generation time compared to the traditional exhaustive search method. Then, the NSGA_Ⅱ algorithm effectively utilizes these initial solutions during the evolution process, generates new paths through cross-referencing, incorporates constraints into the problem's objective function or constraint set, and generates solutions that meet the constraints, while maintaining diversity through multiple strategies. Finally, the Heuristic method is used for local optimization to ensure that more constraints are met. The advantage of this combination of three algorithms is that it fully leverages the characteristics of different algorithms to solve the problem more efficiently, overcoming the drawbacks of traditional TSP problem solving, such as high time and computational resource consumption, high labor costs, and difficulty in handling constraints. It also avoids the shortcomings of strong subjectivity and large errors caused by human intervention.

[0049] ③ The automatic planning method for the land-based controllable seismic source travel route proposed in this invention initializes a path as the initial route using a two-approximation algorithm. Then, during the genetic process, individuals provided by the two-approximation algorithm are used as a part of the parent generation for crossover to generate a new route using NSGA-II. Finally, the Heuristic algorithm is used for local optimization. In the process of planning the land-based controllable seismic source travel route through the automatic planning method, the different algorithms can work together after integration during the multi-algorithm fusion process, ensuring that the overall algorithm can converge to a high-quality solution within a reasonable time. The final result is a seismic source vehicle travel route that is short, has few obstacles, has few restrictions on the seismic source vehicle's travel, and is in line with the driver's operating habits and the needs of actual field production work.

[0050] ④ The apparatus, electronic equipment, and storage medium provided by this invention for the automatic planning method of the walking route of a controllable seismic source on land have complete hardware and software supporting facilities, which facilitates the promotion and use of this testing method.

[0051] This invention is applied to the field of geophysical exploration to rationally and efficiently plan the travel route of a controllable seismic source vehicle, and is particularly suitable for exploration areas with a large number of seismic source points, a wide distribution range, and many obstacles. Attached Figure Description

[0052] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0053] Figure 1 This is a flowchart of the automatic planning method for the travel route of a controllable seismic source on land in Embodiment 1 of the present invention;

[0054] Figure 2 This is a screenshot of the process in Embodiment 1 of the present invention, showing the import of designed source point data and obstacle data into the source route design software.

[0055] Figure 3 This is the interface for setting relevant parameters in Embodiment 1 of the present invention;

[0056] Figure 4 The result of the land-based controllable seismic source travel route designed using the planning method of the present invention in Embodiment 1 of the present invention;

[0057] Figure 5 This is a structural block diagram of an automatic planning device for the walking route of a controllable seismic source on land, according to Embodiment 2 of the present invention; in the figure: 1-central control module, 2-map construction module, 3-setting relevant parameters and their weight ratio module, 4-TNH combined algorithm to solve the walking route of the controllable seismic source on land. Detailed Implementation

[0058] The present invention will be further described in detail below with reference to specific embodiments and accompanying drawings. It should be understood that the described embodiments are preferred examples of the present invention and are only used to explain the present invention and do not limit the present invention.

[0059] Example 1: An automatic planning method for the travel route of a controllable land seismic source

[0060] Because the exploration area is quite large, it has been divided into multiple exploration blocks according to the conventional practice of those skilled in the art. This embodiment uses a specific exploration block as an example to provide an automatic planning method for the travel route of a controllable seismic source on land. The flowchart is as follows: Figure 1 As shown, this embodiment is based on the software operation of our company's automatic planning of the controllable seismic source travel route. The planning method includes the following steps performed in sequence:

[0061] S1. Building the Map

[0062] The designed seismic source point data and construction map data are displayed using ArcGIS software. The obstacle data in the construction area, collected through image recognition technology, manual collection, and big data, are imported. The planned area is divided into two types of terrain: passable areas and obstacle areas. For obstacle areas, they are simplified into linear or polygonal features. In this way, only the reachable points, prohibition lines, and prohibition surfaces remain on the map, thus completing the map construction.

[0063] The source point data includes the number and location of the source points;

[0064] You can also define buffers according to actual needs to prevent edge problems in obstacle areas. Linear features become polygonal features after a buffer is created, and polygonal features remain polygonal features after a buffer is created.

[0065] To simplify calculations, the geometric nodes of obstacle elements in the obstacle region are thinned out to ensure that subsequent topological operations such as minimum path and intersection are performed as quickly as possible.

[0066] in, Figure 2 This is a screenshot of the process of importing designed source point data and obstacle data into source path design software for a certain project. The dots represent shot points and the lines represent obstacles.

[0067] S2. Introduce the concept of the TSP problem, and set relevant parameters and their weights.

[0068] S21. Setting relevant parameters

[0069] According to the construction requirements, the task range of each group of seismic source vehicles can be marked by drawing lines. Because the TSP problem idea is introduced, before the automatic planning of the seismic source route, each seismic source point needs to be treated as a node and the obstacle area as an edge. Parameters including the shortest path between two nodes, turning angle and obstacle avoidance are set according to the specific construction situation.

[0070] The purpose of setting the turning angle parameter is to set the turning angle range of the route according to driving habits, so as to avoid the phenomenon of the vibration source vehicle making multiple U-turns or making large-angle turns.

[0071] Using Euclidean distance as the shortest path between two nodes, the calculation of Euclidean distance includes the following two cases:

[0072] In the first case, when the line connecting two nodes p1(x1, y1, z1) and p2(x2, y2, z2) does not intersect the obstacle area, the Euclidean distance is calculated according to Formula 1:

[0073]

[0074] In the second case, when the line connecting two nodes p1(x1, y1, z1) and p2(x2, y2, z2) intersects the obstacle area, the Euclidean distance is calculated according to Formula 2:

[0075]

[0076] The imported obstacle data can also be categorized into five levels, from one to five. The lower the level, the higher the priority of passing through. At the same time, certain obstacles can be set to be impassable.

[0077] In addition, parameters such as travel distance and path width can be set; for example, the travel distance includes the maximum distance of a complete seismic source route, and the maximum or minimum distance of a single straight line; path width: set the minimum passable road width to avoid the road width being less than the width of the seismic source vehicle, thus preventing it from passing through normally;

[0078] This invention, based on the traditional TSP approach, defines a minimum search quantity when searching for the next point near a given point and within a specified radius. Specifically:

[0079] In the traditional TSP (Tracking Point Solution) approach, real-world operations only search for the next point near a given point. We define a search radius, such as 50m, and only search within this radius, stopping the search once a point is found. To ensure optimal selection of the shortest path, this invention defines a minimum number of searches, such as 5. After defining this minimum number of searches, when starting from a given point and searching within a specified radius: if the number of satisfying endpoints within the search radius exceeds 5, at least 5 points are provided to the algorithm for selection, with the most suitable point being chosen; if the number of satisfying endpoints within the search radius is less than 5, all satisfying points are provided to the algorithm for selection, rather than determining the endpoint after finding one, but rather comparing multiple points and selecting the most suitable one.

[0080] The interface for setting relevant parameters is as follows Figure 3 As shown, after importing the seismic source point data and obstacle data, relevant parameters can be adjusted according to actual construction needs, such as obstacle level, road priority level, turning range restriction, prohibition of U-turns, and shortest path.

[0081] S22. Setting the weight percentage of different parameters

[0082] Based on the different needs of industry professionals in their actual work regarding local policy requirements, terrain conditions, and completion time, the weight percentages of parameters such as the shortest path, turning angle, and obstacle avoidance between the two nodes are determined.

[0083] S3.TNH combined algorithm for solving the travel path of a controllable land seismic source

[0084] Based on the constructed map, the set parameters and weights, and through the combined application of the two approximation algorithm, the NSGA-II algorithm, and the Heuristic algorithm, the path of the controllable seismic source on land is obtained, specifically including:

[0085] S31. Based on the set relevant parameters and weight ratios, an initial land-based controllable seismic source travel path is obtained through a two-approximation algorithm, which is used as the first-generation individual;

[0086] S32. Based on the NSGA-II algorithm, the aforementioned first-generation individuals are used as part of the parent generation for crossover during the genetic process to generate new paths;

[0087] S33. The new paths generated in the first generation of individuals are locally optimized using the Heuristic algorithm to obtain the optimized land-controlled seismic source travel path, which is the land-controlled seismic source travel route planned by the automatic planning method.

[0088] The controllable seismic source routes obtained above can be further checked by industry professionals. If a small part of the route needs to be modified due to special circumstances during future construction, industry professionals can also manually delete or add routes through the software that automatically plans the controllable seismic source routes, so that the final route is more in line with actual needs.

[0089] Because the two approximation algorithm, NSGA-II algorithm, and Heuristic algorithm each have their own advantages and disadvantages when used individually to solve for the walking route of a controllable seismic source on land. For example, the Heuristic algorithm is a greedy heuristic algorithm based on TSP. The basic idea of ​​this algorithm is to continuously exchange two nodes in the path until the path length can no longer be optimized. However, it cannot guarantee a globally optimal solution because it may get stuck in a local optimum and be unable to escape. Therefore, this invention proposes the TNH combined algorithm by combining the advantages of the two approximation algorithm, the Heuristic algorithm, and the NSGA-II algorithm. This algorithm can significantly solve the drawbacks of the above-mentioned individual solution methods, speed up the calculation efficiency, improve the accuracy of the calculation results, and make the calculated route more consistent with the actual use case.

[0090] The results of the land-based controllable seismic source travel route designed using the planning method of this invention are as follows: Figure 4 As shown, once the relevant parameters are set, it only takes 4 seconds to plan the route of the controllable seismic source on land.

[0091] Example 2: An automatic planning device for the travel route of a controllable land seismic source.

[0092] This embodiment provides a device for automatically planning the travel route of a controllable seismic source on land. The structural block diagram of the device is as follows. Figure 5 As shown, the device includes a map construction module 2, a module for setting relevant parameters and their weighting percentages 3, a TNH combined algorithm module 4 for solving the traverse path of a controllable land seismic source, and a central control module 1.

[0093] The map construction module 2 is used to divide the planning area into two types of terrain, namely passable areas and obstacle areas, based on basic geographic information data, to determine the number and location of earthquake source points and construct a map.

[0094] The module 3 for setting relevant parameters and their weight ratios is used to set parameters including the shortest path between two nodes, turning angle, and obstacle avoidance, taking each seismic source point as a node and the obstacle area as an edge, and to determine the weight ratio of each parameter.

[0095] The TNH combined algorithm module 4 for solving the land controllable seismic source travel route is used to solve for the land controllable seismic source travel route by combining the two approximation algorithm, NSGA-II algorithm and Heuristic algorithm.

[0096] The central control module 1 is equipped with control software, which is used to control the signal flow and data processing in the map construction module 2, the module 3 for setting relevant parameters and their weight ratios, and the module 4 for solving the land controllable seismic source travel route using the TNH combined algorithm.

[0097] Example 3: A computer device

[0098] This embodiment provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, to realize the above-mentioned automatic planning method for the movement route of a controllable land seismic source.

[0099] The aforementioned memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0100] The processor described above may be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. The processor is used to execute the computer-readable instructions stored in the memory.

[0101] Those skilled in the art will understand that, in order to solve the technical problem of how to achieve a good user experience, this embodiment may also include well-known structures such as communication buses and interfaces, and these well-known structures should also be included within the protection scope of this disclosure.

[0102] Example 4: A computer-readable storage medium

[0103] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described automatic planning method for the movement route of a controllable land seismic source.

[0104] The computer-readable storage medium stores non-transitory computer-readable instructions thereon. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the methods described in the foregoing embodiments are performed.

[0105] The aforementioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or portable hard drive), media with built-in rewritable non-volatile memory (e.g., memory card), and media with built-in ROM (e.g., ROM cartridge).

[0106] The above description is merely an optional embodiment of this disclosure and is not intended to limit this disclosure. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the protection scope of this disclosure.

Claims

1. An automatic planning method for the travel route of a controllable land seismic source, characterized in that, This planning method includes the following steps performed sequentially: S1. Building a Map Based on basic geographic information data, the planning area is divided into two types of terrain: passable areas and obstacle areas. The number and location of earthquake focal points are determined, and a map is constructed. S2. Introduce the TSP problem concept, and set relevant parameters and their weighting percentages. Each seismic source point is treated as a node, and the obstacle area is treated as an edge. Parameters including the shortest path between two nodes, turning angle, and obstacle avoidance are set, and the weight of each parameter is determined. S3. TNH combined algorithm for solving the travel path of a controllable land seismic source. Based on the set relevant parameters and weight ratios, the travel path of the controllable seismic source on land is obtained by combining the two approximation algorithm, the NSGA-II algorithm and the Heuristic algorithm. Step S3 includes the following steps: S31. Based on the set relevant parameters and weight ratios, an initial land-based controllable seismic source travel path is obtained through a two-approximation algorithm, which is used as the first-generation individual; S32. Based on the NSGA-II algorithm, the aforementioned first-generation individuals are used as part of the parent generation for crossover during the genetic process to generate new paths; S33. The new paths generated in the first generation of individuals are locally optimized using the Heuristic algorithm to obtain the optimized land-controlled seismic source travel path, which is the land-controlled seismic source travel route planned by the automatic planning method.

2. The automatic planning method for the travel route of a controllable seismic source on land according to claim 1, characterized in that, In step S1, the obstacle region can be simplified into linear features or planar features.

3. The automatic planning method for the travel route of a controllable seismic source on land according to claim 2, characterized in that, In step S1, the geometric nodes of the obstacle region can be thinned out to simplify the calculation.

4. The automatic planning method for the travel route of a controllable seismic source on land according to claim 1, characterized in that, In step S2, the Euclidean distance is used as the shortest path between the two nodes.

5. The automatic planning method for the travel route of a controllable seismic source on land according to claim 4, characterized in that, The determination of the Euclidean distance includes the following two cases; In the first case, when the line connecting two nodes p1(x1, y1, z1) and p2(x2, y2, z2) does not intersect the obstacle area, the Euclidean distance is calculated according to Formula 1: Official 1 In the second case, when the line connecting two nodes p1(x1, y1, z1) and p2(x2, y2, z2) intersects the obstacle area, the Euclidean distance is calculated according to Formula 2: Official 2.

6. The automatic planning method for the travel route of a controllable seismic source on land according to claim 1, characterized in that, In step S2, based on the traditional TSP approach, when searching for the next point near a given point, a minimum search quantity is defined when searching within a specified radius.

7. A device for automatically planning the travel route of a controllable land seismic source, characterized in that, The device includes a map construction module, a module for setting relevant parameters and their weighting percentages, a TNH combined algorithm module for solving the trajectory of a controllable land seismic source, and a central control module. The map construction module is used to divide the planning area into two types of terrain, namely passable areas and obstacle areas, based on basic geographic information data, to determine the number and location of earthquake source points and construct a map. The module for setting relevant parameters and their weight ratios is used to treat each seismic source point as a node and the obstacle area as an edge, setting parameters including the shortest path between two nodes, turning angle, and obstacle avoidance, and determining the weight ratio of each parameter. The TNH combined algorithm module for solving the land controllable seismic source travel route is used to solve for the land controllable seismic source travel route based on the set relevant parameters and weight ratios, through the combined application of the two approximation algorithm, NSGA-II algorithm and Heuristic algorithm. The process of obtaining the travel path of a controllable land-based seismic source includes the following steps: S31. Based on the set relevant parameters and weight ratios, an initial land-based controllable seismic source travel path is obtained through a two-approximation algorithm, which is used as the first-generation individual; S32. Based on the NSGA-II algorithm, the aforementioned first-generation individuals are used as part of the parent generation for crossover during the genetic process to generate new paths; S33. The new paths generated in the first generation of individuals are locally optimized using the Heuristic algorithm to obtain the optimized land-controlled seismic source travel path, which is the land-controlled seismic source travel route planned by the automatic planning method. The central control module is equipped with control software modules used to control the signal flow and data processing in the map construction module, the module for setting relevant parameters and their weight ratios, and the module for solving the land controllable seismic source travel route using the TNH combined algorithm.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the automatic planning method for the travel route of a controllable seismic source on land, as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that executes the automatic planning method for the travel route of a land-based controllable seismic source as described in any one of claims 1 to 6.

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