Vibroseis excitation control method and device based on time distance rule

Abstract

The invention discloses a time distance rule-based vibroseis excitation control method and device, and the method comprises the steps: carrying out the local search of the current planning data in a shot point distribution connected graph of a to-be-analyzed work area, and obtaining a local search optimal solution; during local search, simulating a plurality of vibroseis by using a simulation excitation model based on a TD rule to obtain actual cost; in the shot point distribution connected graph of the to-be-analyzed work area, segment migration local search is carried out between the planned paths of the vibroseis in the local search optimal solution, and a segment migration local optimal solution is obtained; when segment migration local search is carried out, a simulation excitation model based on a TD rule is utilized to obtain the actual cost; and taking the segment migration local optimal solution as current planning data, repeatedly executing the steps until an iteration termination condition is reached, and outputting the current planning data. According to the invention, deep fusion of the time distance rule and the path planning can be realized, and the production efficiency of the excitation control of the vibroseis is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration, and particularly to a controllable source excitation control system and method based on a time-distance rule. Background Art

[0002] This section aims to provide background or context for the embodiments of the present invention described in the claims. The descriptions herein are not admitted to be prior art merely because they are included in this section.

[0003] Seismic exploration is a method of artificially exciting seismic waves, analyzing their propagation mode underground, and obtaining the undulating shape and physical properties of underground strata. Currently, seismic exploration is the most important and widely used means for exploring underground mineral resources (such as oil). With the increasing difficulty of oil exploration, the requirements for the safety, accuracy, and efficiency of seismic exploration are also getting higher and higher. As one of the main technologies for seismic data acquisition, controllable sources are being used more and more widely.

[0004] A controllable source is a mechanical source that relies on a vibrator installed on a controllable source vehicle to continuously impact the ground to generate seismic waves. Compared with traditional explosive and heavy hammer excitation of seismic waves, a controllable source can customize parameters such as excitation frequency and sweep time according to different work areas and terrain conditions. At the same time, a controllable source does not generate vibration frequencies that do not propagate in the formation, does not damage rocks, and can save energy; it has strong anti-interference ability and can improve the signal-to-noise ratio of the collected data; it causes less damage to the ground and can be used for exploration in densely populated areas. The exploration using controllable sources has gone through the experimental stage and the large-scale application stage and is gradually becoming mature, and its advantages are becoming more and more prominent. With the requirement for acquisition efficiency, controllable sources have entered the high-efficiency acquisition stage, and the acquisition technology has made great progress, and several new sweep operation methods have emerged.

[0005] Currently, the excitation of controllable sources mainly uses manual control methods for path planning and excitation control, and there is still much room for improvement in efficiency. There is an urgent need to design targeted intelligent optimization algorithms to further improve efficiency and reduce exploration costs.

[0006] With the development of society, people's requirements for green environmental protection and safe and efficient operations are getting higher and higher. The use of controllable source high-efficiency acquisition technology will surely become the future development direction. One of the main factors restricting the use of controllable source high-efficiency acquisition technology is production efficiency, and production efficiency is closely related to the excitation method. Therefore, the optimization of controllable source excitation efficiency has become the focus of attention for controllable source high-efficiency acquisition technology.

[0007] In actual production, in order to increase the efficiency of exploration operations, multiple vibroseis trucks often need to operate simultaneously. When the excitation time intervals between them are short, harmonic interference is likely to occur. To avoid the mutual influence between the vibroseis trucks, it is necessary to control the excitation times of different sources. For every two vibroseis trucks separated by a certain distance, their startup intervals need to meet the given "Time-Distance Rule (TD Rule)". For the vibroseis trucks that do not currently meet the rule constraints, they need to wait until the conditions are met before they can start vibrating. For the vibroseis trucks that simultaneously meet the rule, the selection of the vibrating trucks needs to be carried out.

[0008] It can be seen that the total construction time of the vibroseis trucks consists of three parts: the scanning time of the vibroseis sources, the waiting time of the vibroseis trucks to avoid harmonic interference, and the moving time of the vibroseis trucks from the current shot point to the next shot point after the work is completed. Due to the requirements of the work area and the quality of the collected data, it is generally difficult to reduce the working time of the vibroseis trucks. Therefore, the optimization of the excitation efficiency focuses on reducing the moving time and the waiting time of the vibroseis trucks. The moving time mainly depends on the path planning of each vibroseis truck, and the total waiting time is closely related to factors such as the path planning of the vibroseis trucks and the selection of the vibrating trucks each time. Therefore, the optimization of the excitation efficiency is a multi-objective optimization problem.

[0009] In recent years, significant progress has been made in the high-efficiency acquisition technology of vibroseis. In fact, these high-efficiency acquisition methods of vibroseis all improve production efficiency around the constraints of "space" and "time". Here, space refers to the distance between vibroseis sources, and time refers to the time interval between the start of vibration of vibroseis sources. In dynamic sliding scanning, since different vibroseis excitation methods are integrated, and different excitation methods correspond to different time-distance rules, after organizing them, a function describing the distance between two groups of sources and the minimum startup time interval in dynamic sliding scanning is obtained, which is called the TD (Time&Distance) Rule. The TD Rule is an important function related to production efficiency and the quality of collected data in seismic acquisition, balancing the construction efficiency of vibroseis trucks and the harmonic interference caused by short startup intervals.

[0010] In pursuit of high efficiency, the sliding time T is usually shortened, which results in poor data quality, from no interference to mild interference, moderate interference, and even data aliasing. Harmonic interference suppression technology, adjacent gun interference suppression technology, aliasing data separation and other technologies have emerged as the times require. It is precisely because of the effective use of these technologies that the sliding time T can be gradually shortened and the efficiency is greatly improved step by step. However, it is not the case that the smaller T, the better, because interference suppression and data separation technology have their own applicable conditions and are detrimental to valid data. At this time, we can effectively reduce interference and improve data quality by adjusting the source spacing D. However, in actual production, D cannot be unlimitedly large. After production exploration and the development of denoising technology, we can find effective TD rules to ensure the balance between production efficiency and data quality.

[0011] TD rules are generally divided into conventional step-type TD rules and ladder-type TD rules. Conventional step-type TD rules are simple and easy to understand. Priorities are set from high to low according to acquisition efficiency. When the distance is close, it is alternating scanning, when the distance is slightly farther, it is sliding scanning, and when the distance is farther, it is synchronous scanning. The TD rule is in the form of a step function. The selection of parameters for the step-type TD rule is relatively simple, but the disadvantage is that the alternating scanning time is too long. At the right end of the alternating scanning stage, due to the large distance between the source vehicles, the harmonic interference is no longer obvious, but it is still less efficient than sliding scanning. The ladder-type TD rule further improves the sliding scanning of fixed time, that is, it corresponds to the time variation of the controllable vibrator. Through statistical analysis, it is found that the harmonic energy at the excitation point is very strong, which interferes with data acquisition more seriously. However, with the increase of propagation distance, the harmonic energy decreases in a curve that approximates an inverse function. At a distance far from the excitation point, the harmonic has the characteristic of linear slow attenuation. Therefore, when the two source vehicles are far apart, the sliding time can be reduced according to the attenuation law of the approximate harmonic energy at the far excitation point, thereby ensuring the quality of the acquired data and improving the acquisition efficiency. The ladder-type TD rule optimizes the fixed time interval of the sliding scan into a time interval that decreases in the form of a linear function on the basis of the conventional step-type TD rule. It is flexible and efficient and has been widely used and verified in actual production.

[0012] TD rules can be flexibly changed to meet the different needs of the project and meet exploration tasks with different focuses. TD rules suitable for the project can be determined by comprehensively considering the exploration efficiency, noise level and exploration method, which is of great significance to the completion of the entire project.

[0013] It is assumed here that when an excitation planning scheme satisfies the TD rule, it will adapt to the requirements of a specific scanning method. Therefore, when optimizing the excitation control, each vehicle path and vehicle start-up time are directly controlled under the condition of satisfying the TD rule, and no specific scanning method is discussed.Figure 1 Shown is a schematic diagram of a trapezoidal TD rule. When the distance between two vibrator trucks and the excitation time interval do not meet the TD rule, it will fall below the TD rule function, as shown in Figure 1 the cross-point markings in. At this time, due to harmonic effects, the collected data will become waste shots. Only the points above the TD rule function are valid excitations, as shown in Figure 1 the dot markings in.

[0014] Currently, the selection of starting vehicles and path planning still mainly rely on the judgment of manual experience, and there is still much room for improvement in efficiency. Summary of the Invention

[0015] In a first aspect, an embodiment of the present invention provides a vibrator excitation control method based on a time-distance rule, which can achieve the deep integration of the time-distance rule and path planning, and improve the production efficiency of vibrator excitation control. The method includes:

[0016] Obtain the current planning data of multiple vibrators; wherein, the planning data includes the positions and planned paths of the vibrators;

[0017] In the connected graph of shot point distributions in the work area to be analyzed, perform a local search on the current planning data to obtain a local search optimal solution; when performing the local search, use a simulation excitation model based on the time-distance TD rule to simulate multiple vibrators to obtain the actual cost;

[0018] In the connected graph of shot point distributions in the work area to be analyzed, perform a segment migration local search between the planned paths of each vibrator in the local search optimal solution to obtain a segment migration local optimal solution; when performing the segment migration local search, use a simulation excitation model based on the TD rule to simulate multiple vibrators to obtain the actual cost;

[0019] Take the segment migration local optimal solution as the current planning data, and repeat the above steps until the iteration termination condition is reached, and output the current planning data.

[0020] In a second aspect, an embodiment of the present invention further provides a vibrator excitation control device based on a time-distance rule, which can achieve the deep integration of the time-distance rule and path planning, and successfully predict the production efficiency under different work areas, which is of great significance for improving the production efficiency of actual vibrator high-efficiency acquisition. The device includes:

[0021] A planning data acquisition module, configured to acquire the current planning data of multiple vibrators; wherein, the planning data includes the positions and planned paths of the vibrators;

[0022] A local search module, which is used to perform local search on the current planning data in the connected graph of shot point distribution in the work area to be analyzed, so as to obtain the optimal solution of local search; when performing local search, a simulation excitation model based on the time distance TD rule is used to simulate multiple vibrators to obtain the actual cost;

[0023] A segment migration local search module, which is used to perform segment migration local search between the planned paths of each vibrator in the optimal solution of local search in the connected graph of shot point distribution in the work area to be analyzed, so as to obtain the optimal solution of segment migration local search; when performing segment migration local search, a simulation excitation model based on the TD rule is used to simulate multiple vibrators to obtain the actual cost;

[0024] An iteration module, which is used to use the optimal solution of segment migration local search as the current planning data, and repeat the above steps until the iteration termination condition is reached, and output the current planning data.

[0025] In a third aspect, an embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above-mentioned vibrator excitation control method based on the time distance rule is implemented.

[0026] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned vibrator excitation control method based on the time distance rule is implemented.

[0027] In a fifth aspect, an embodiment of the present invention further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the above-mentioned vibrator excitation control method based on the time distance rule is implemented.

[0028] In an embodiment of the present invention, current planning data of multiple vibrators is obtained; wherein, the planning data includes the positions and planned paths of the vibrators. In the connected graph of shot point distributions in the work area to be analyzed, local search is performed on the current planning data to obtain the local search optimal solution. When performing local search, a simulation excitation model based on the TD rule is used to simulate multiple vibrators to obtain the actual cost. In the connected graph of shot point distributions in the work area to be analyzed, segment migration local search is performed between the planned paths of each vibrator in the local search optimal solution to obtain the segment migration local optimal solution. When performing segment migration local search, a simulation excitation model based on the TD rule is used to simulate multiple vibrators to obtain the actual cost. The segment migration local optimal solution is used as the current planning data, and the above steps are repeatedly executed until the iteration termination condition is reached, and the current planning data is output. Compared with the prior art technical solution that mainly relies on manual experience judgment for vibrator excitation control, in the embodiment of the present invention, local search is performed on the current planning data to obtain the local search optimal solution, and then segment migration local search is performed between the planned paths of each vibrator in the local search optimal solution to obtain the segment migration local optimal solution. During the above search process, a simulation excitation model based on the TD rule is used to simulate multiple vibrators to obtain the actual cost, realizing the deep integration of the TD rule and path planning, and improving the production efficiency of vibrator excitation control. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts. In the drawings:

[0030] Figure 1 Schematic diagram of the TD rule for efficient excitation of vibrators in an embodiment of the present invention;

[0031] Figure 2 Flowchart of the vibrator excitation control method based on the time-distance rule in an embodiment of the present invention;

[0032] Figure 3 Schematic diagram of the bilateral exchange local search method in an embodiment of the present invention;

[0033] Figure 4 Principle diagram of performing segment migration local search in an embodiment of the present invention;

[0034] Figure 5 Schematic diagram of the iteration convergence curve in an embodiment of the present invention;

[0035] Figure 6Structural block diagram of a controllable source excitation control device based on a time-distance rule according to an embodiment of the present invention;

[0036] Figure 7 Schematic diagram of a computer device in an embodiment of the present invention. Specific embodiments

[0037] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer and more understandable, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Herein, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0038] The inventors believe that the controllable source exploration technology is to use artificial seismic sources to generate seismic waves for exploration by controlling the spectral characteristics of the signals they generate. The controllable source acquisition technology has become an indispensable means for oil exploration due to its environmental protection, safety, and flexibility advantages. To increase the efficiency of exploration operations, multiple controllable source vehicles often need to operate simultaneously, visiting the pre-planned seismic source points in sequence within a specified area and starting vibration one by one. To avoid harmonic interference between the source vehicles, when two source vehicles with a relatively short distance need to start vibration simultaneously, it is necessary to control the excitation times of the two source vehicles so that they meet the conditions of the given "time-distance rule (TD rule)". The controllable source excitation problem can be described as how to allocate the seismic source points and plan the starting vibration paths of each vehicle in an environment of multiple source vehicles, so that the parallel operation time is the shortest under the conditions of meeting the TD rule. Currently, the method of manual control is mainly used for excitation path planning and control, and there is still a large room for improvement in efficiency. The present invention aims to design a targeted intelligent excitation optimization algorithm to further improve efficiency and reduce exploration costs.

[0039] Figure 2 Flowchart of a controllable source excitation control method based on a time-distance rule according to an embodiment of the present invention, including:

[0040] Step 201, obtaining the current planning data of multiple controllable sources; wherein, the planning data includes the positions and planned paths of the controllable sources;

[0041] Step 202, performing local search on the current planning data in the connected graph of shot point distributions in the work area to be analyzed to obtain a local search optimal solution; when performing local search, using a simulation excitation model based on the time-distance TD rule to simulate multiple controllable sources to obtain the actual cost;

[0042] Step 203, performing segment migration local search between the planned paths of each controllable source in the local search optimal solution in the connected graph of shot point distributions in the work area to be analyzed to obtain a segment migration local optimal solution; when performing segment migration local search, using a simulation excitation model based on the TD rule to simulate multiple controllable sources to obtain the actual cost;

[0043] Step 204: Use the local optimal solution of the segment migration as the current planning data, and repeat the above steps until the iteration termination condition is reached, and output the current planning data.

[0044] In the embodiments of the present invention, compared with the prior art in which the control of the vibroseis excitation mainly relies on the judgment of manual experience, the embodiments of the present invention perform a local search on the current planning data to obtain a local search optimal solution, and then perform a local search on the migration of segments between the planned paths of each vibroseis in the local search optimal solution to obtain a local optimal solution of the segment migration; in the above search process, a simulation excitation model based on the TD rule is used to simulate multiple vibroseises to obtain the actual cost, realizing the deep integration of the TD rule and path planning, and improving the production efficiency of the vibroseis excitation control.

[0045] In the embodiments of the present invention, the vibroseis is a vibroseis vehicle. Specifically, in actual implementation, in order to optimize the excitation efficiency of the vibroseis, it is necessary to shorten its total working time as much as possible. In an actual work area, the method of dividing the work area by multiple groups of vibroseis vehicles is generally adopted. The construction time of multiple vibroseis vehicles is the actual cost, and the actual cost is expressed by the following formula:

[0046] T = max i (T iw + T ir + T im )

[0047] where T is the actual cost, T iw is the scanning time of the i-th vibroseis, T ir is the waiting time of the i-th vibroseis to avoid harmonic interference, and T im is the moving time of the i-th vibroseis from the current shot point to the next shot point after the work is completed.

[0048] Since the scanning duration often depends on the project conditions and the work area and is generally a fixed value, the present invention designs an algorithm for the waiting time and the moving time and performs modeling optimization. A vibroseis path optimization model is established for the moving time, and a simulation excitation model based on the TD rule is designed for the waiting time.

[0049] The following introduces the vibroseis path optimization model. Since in a work area, the shot points to be collected are already determined, and each shot point only needs to be collected once. In actual situations, the starting point of the vibroseis vehicle is generally fixed. If there is only one group of vibroseises, the vibroseis path optimization model can be expressed as:

[0050]

[0051] x = (x(1) , x (2) , …, x (j) , …, x (n) ) ∈ P n

[0052] Wherein, x is the driving path of the vibroseis, and n is the total number of shot points in the driving path of the vibroseis; is the distance between the i-th shot point and the (i + 1)-th shot point on the driving path of the vibroseis, and P n is the set of all permutations of the shot points that the vibroseis needs to pass through.

[0053] However, for the sake of high-efficiency acquisition, multiple groups of vibroseis often operate simultaneously in the same work area. Therefore, multi-path planning for fixed shot points is required. At the same time, the biggest difference between this path optimization problem and the conventional path optimization problem is that it is hoped that the turning angle is as small as possible. Therefore, the turning angle of each shot point is added as a penalty term to the calculation of the total driving cost. If a vehicle travels from point A through point B to point C, the path cost is:

[0054] Cost(A, B, C) = (c A,B + c B,C ) + α · (π - θ A,B,C )

[0055] Where: α - penalty term coefficient; c A,B - the distance from vertex A to vertex B; θ A,B,C - the included angle between vertices A, B, and C.

[0056] Since the improvement of the excitation efficiency of the vibroseis is a multi-objective optimization problem, both path optimization and the optimization of the excitation sequence of the vibroseis (i.e., the positions of the vibroseis) can improve the excitation efficiency. Therefore, it is expected to obtain a locally optimal solution optimized in multiple aspects. Specifically, the length and turning angle of the path within each vibroseis can be iteratively optimized through bilateral path exchange of the vibroseis. On this basis, the point allocation between vehicles can be optimized and updated iteratively according to the TD rule lower segment migration method in turn, so as to optimize the path shot point division and the operation time under the TD rule constraint. By repeating the above two iterations, a locally optimal solution can be obtained, thereby realizing the deep integration of path optimization and vibroseis position optimization, and obtaining a feasible solution with the minimum operation time under the TD rule.

[0057] In step 201, the current planning data of multiple vibroseis are obtained; wherein, the planning data includes the positions and planned paths of the vibroseis;

[0058] Adding the path turning penalty term, the vibroseis path optimization model is:

[0059]

[0060] x = (x (1) , x (2) ,..., x (j) ,..., x (n) ) ∈ P n

[0061] where x is the travel path of the vibrator, and n is the total number of shot points in the travel path of the vibrator; is the distance between the i-th shot point and the (i + 1)-th shot point on the travel path of the vibrator, and P n is the set of all permutations of the shot points that the vibrator needs to pass through, α is the penalty term coefficient, is the included angle formed by the (i - 1)-th, i-th, and (i + 1)-th shot points in the travel path of the vibrator.

[0062] The above vibrator path optimization model represents the moving point time of each vibrator. In the embodiments of the present invention, the vibrator path optimization model represented by the multiple vibrators is adopted.

[0063] The moving point time of the vibrator is optimized through the vibrator path optimization model, the production time is shortened, and the production efficiency is improved.

[0064] In step 202, in the shot point distribution connectivity graph of the work area to be analyzed, local search is performed on the current planning data to obtain the local search optimal solution; when performing local search, the actual cost is obtained by simulating multiple vibrators using the simulation excitation model based on the TD rule;

[0065] In the embodiments of the present invention, it is necessary to optimize both the vibrator position and the path simultaneously, which is a multi-objective optimization problem. Therefore, according to the foregoing model, a two-stage iterative local search method is designed, with the bilateral exchange local search method as the core of the vibrator path optimization iteration and the lower segment migration local search method based on the TD rule as the measurement index of the vibrator path cost, and they are deeply integrated to realize the simulation of efficient excitation of the vibrator under different conditions.

[0066] When the starting point of the fixed vibration source vehicle is fixed, the path optimization problem of a single vibrator is a TSP problem (Traveling Salesman Problem), and the bilateral exchange local search method is a local optimization algorithm. This method reduces the path distance by changing the order of the passing points in a path. If the distance of the path is reduced, the improved path is retained. Otherwise, the path returns to the situation before modification. Among multiple vibrators, the specific steps of the bilateral exchange local search method are described as follows.

[0067] In one embodiment, in the connection graph of shot points in the work area to be analyzed, local search is performed on the current planning data to obtain the local search optimal solution, including:

[0068] In the connection graph of shot points in the work area to be analyzed, the following bilateral exchange local search method is used to perform local search on the current planning data to obtain the local search optimal solution:

[0069] In the connection graph of shot points, randomly select two different shot points, and use the simulation excitation model based on the TD rule to simulate multiple vibrators to obtain the cost of the current planning data as the current actual cost;

[0070] Reverse the intermediate path including the two shot points to obtain a neighboring solution; the intermediate path is a segment of the planned path of the current planning data;

[0071] Use the simulation excitation model based on the TD rule to simulate multiple vibrators to obtain the cost of the new planning data composed of the neighboring solution as the new actual cost;

[0072] When the new actual cost is less than the current actual cost, update the intermediate path including the two shot points to the neighboring solution;

[0073] Repeat the above steps until the local optimal solution is obtained.

[0074] See Figure 3 , the current path in the current planning data is, for example, from A to H and then back to A, passing through all the shot points that a vibrator needs to pass through. Assume this is the shortest path; randomly select two different shot points and reverse the intermediate route including these two shot points. At this time, a neighboring solution will be obtained. For example, randomly select points C and F, then the old path will be divided into three segments; flip the middle segment to get a new path. If the cost of the new path is less than the current path, then update the path; if the total length of the new path is greater than the current path, then the shortest path is not updated, and finally it converges to a local optimal solution. Then it can be considered that this path is the shortest path.

[0075] In step 203, in the connection graph of shot points in the work area to be analyzed, perform segment migration local search between the planned paths of each vibrator in the local search optimal solution to obtain the segment migration local optimal solution; when performing segment migration local search, use the simulation excitation model based on the TD rule to simulate multiple vibrators to obtain the actual cost;

[0076] Since the TD rule is an important constraint for the excitation of vibroseis, under the condition of meeting the TD rule, the total operation time should be minimized as much as possible. Therefore, the embodiment of the present invention realizes a cost optimization method based on the segment migration between different vibroseis paths in the simulation excitation model based on the TD rule. The purpose is to reduce the driving cost of the longest vehicle by trying to transfer the entire path segment of the longest vehicle to the path of another vehicle, thereby achieving load balancing between vehicles. This method redistributes the shot points of each path based on the longest completion time of each path under the TD rule.

[0077] See Figure 4 This is the schematic diagram of the segment migration local search in the embodiment of the present invention. In one embodiment, in the shot point distribution connection graph of the work area to be analyzed, local search for segment migration is performed between the planned paths of each vibroseis in the local search optimal solution to obtain the local optimal solution of segment migration, including:

[0078] In the planned paths of each vibroseis in the local search optimal solution, randomly select two different shot points, and use the simulation excitation model based on the TD rule to simulate multiple vibroseis to obtain the cost of the local search optimal solution as the current actual cost;

[0079] Disconnect the intermediate path including the two shot points, and after disconnection, migrate one of the two obtained planned paths to the planned path of another vibroseis to obtain new planned data; the intermediate path is a segment of the planned path of the current planned data;

[0080] Use the simulation excitation model based on the TD rule to simulate multiple vibroseis to obtain the cost of the new planned data as the new actual cost;

[0081] When the new actual cost is less than the current actual cost, replace the current planned data with the new planned data;

[0082] Repeat the above steps until the local optimal solution of segment migration is obtained.

[0083] In specific implementation, since multiple groups of vibroseis need to meet the constraints of the TD rule during the exploration process, the TD rule not only constrains the spatial distance between two vibroseis but also constrains the time series of the excitation points of the vibroseis. Therefore, a simulation excitation model based on the TD rule is designed for the multi-path exploration of vibroseis in combination with the actual situation:

[0084] min x cost TD (x,λ)

[0085] Where: cost is the cost of the path operation obtained through simulation after considering the TD rule; x is the planning data, including the allocation of vibroseis positions and the path planning scheme; λ is the parameter set required for the TD rule constraint. The parameter set includes the number of vibroseis vehicles and the distribution of shot points. The following gives the steps of simulating multiple vibroseis using the simulation excitation model based on the TD rule.

[0086] In one embodiment, simulating multiple vibroseis using the simulation excitation model based on the TD rule includes:

[0087] Put all the source states into the dynamic loop pool, and the dynamic loop pool classifies and updates the states of the sources in real time;

[0088] According to the current planning data, calculate the distances between different vibroseis at preset intervals;

[0089] According to the predefined TD rule, excite the vibroseis with the state of ready in a certain priority order, and modify the state of the excited vibroseis to working;

[0090] For the vibroseis in the ready state, after the predefined TD rule is satisfied between this vibroseis and the vibroseis with the state of working, this vibroseis enters the priority sorting, and the state is updated to ready;

[0091] When all the vibroseis complete the shot points of their respective bundles, obtain the actual cost.

[0092] In specific implementation, to ensure the uniformity of the excitation times of the vibroseis and prevent the increase of the overall actual cost caused by some vibroseis waiting for too long, it is set to sort the priority order from small to large according to the excitation times of the currently ready-to-start vibroseis, and perform excitation in sequence according to the priority. After excitation, the state of this vibroseis is updated to working. The states such as the movement, waiting, and working of the vibroseis are all reflected in the model. Embedding this simulation excitation model based on the TD rule into the local search can optimize the waiting time of the vibroseis and improve the production efficiency.

[0093] In step 204, use the segment migration local optimal solution as the current planning data, and repeat the above steps until the iteration termination condition is reached, and output the current planning data.

[0094] Specifically, the iteration termination condition can be that the fluctuation of the actual cost in the iteration convergence curve is within a preset range.

[0095] The following gives a specific embodiment to illustrate the specific application of the method proposed in the embodiment of the present invention.

[0096] In a first work area, a connected graph with 500 shot points is constructed, providing the determined number and coordinates of the shot points. The number of vibrators is 4. Since the work area is generally rectangular in actual exploration, test problems use rectangular lattices of different scales. The distance between each shot point is 50 meters, and random perturbations following a two-dimensional normal distribution are added. The given vibrator speed is 10 m / s, and the maximum constraint distance in the TD rule is 400 m. When the distance between two vibrators is greater than or equal to 400 m, the sliding time is 0 s; when the distance between two vibrators is greater than or equal to 0 m and less than 400 m, the sliding time is 8 - 0 s (D and T have a linear variation relationship). The operation time is 6 s, and the shot points on the path of each vibrator are evenly distributed.

[0097] Implement the method proposed by the present invention for the above example. The iterative convergence curve of the final method is as Figure 5 shown. The fluctuation of the actual cost is within the preset range, and the iteration ends. It can be seen that through the iterative optimization of the algorithm, the optimization effect of local search is very significant. Since the initial is a random solution (the current planning data), the optimization effect of the first iterative optimization is often the most significant, and the algorithm converges quickly. Due to the relatively good initial random solution, a certain selection of the initial solution is made in subsequent calculations to reduce the number of iterations and improve the operation efficiency.

[0098] The embodiment of the present invention also proposes a vibrator excitation control generation device based on the time-distance rule. Its principle is similar to the vibrator excitation control generation method based on the time-distance rule, and will not be elaborated here.

[0099] Figure 6 It is a schematic diagram of the vibrator excitation control generation device based on the time-distance rule in the embodiment of the present invention, including:

[0100] A planning data acquisition module 601 for acquiring the current planning data of multiple vibrators; wherein, the planning data includes the positions and planned paths of the vibrators;

[0101] A local search module 602 for performing local search on the current planning data in the connected graph of the shot point distribution in the work area to be analyzed to obtain the local search optimal solution; when performing local search, a simulation excitation model based on the TD rule is used to simulate multiple vibrators to obtain the actual cost;

[0102] A segment migration local search module 603 for performing segment migration local search between the planned paths of each vibrator in the local search optimal solution in the connected graph of the shot point distribution in the work area to be analyzed to obtain the segment migration local optimal solution; when performing segment migration local search, a simulation excitation model based on the TD rule is used to simulate multiple vibrators to obtain the actual cost;

[0103] An iterative module 604, configured to use the local optimal solution of the segment migration as the current planning data, and repeatedly execute the above steps until the iterative termination condition is reached, and output the current planning data.

[0104] In one embodiment, the local search module is specifically configured to:

[0105] In the connected graph of shot point distributions in the work area to be analyzed, perform local search on the current planning data using the following bilateral exchange local search method to obtain the local search optimal solution:

[0106] In the connected graph of shot point distributions, randomly select two different shot points, and use the simulation excitation model based on the TD rule to simulate multiple vibrators to obtain the cost of the current planning data as the current actual cost;

[0107] Reverse the intermediate path including the two shot points to obtain a neighboring solution; the intermediate path is a segment of the planned path in the current planning data;

[0108] Use the simulation excitation model based on the TD rule to simulate multiple vibrators to obtain the cost of the new planning data composed of the neighboring solution as the new actual cost;

[0109] When the new actual cost is less than the current actual cost, update the intermediate path including the two shot points to the neighboring solution;

[0110] Repeat the above steps until the local optimal solution is obtained.

[0111] In one embodiment, the segment migration local search module is specifically configured to:

[0112] In the planned paths of each vibrator in the local search optimal solution, randomly select two different shot points, and use the simulation excitation model based on the TD rule to simulate multiple vibrators to obtain the cost of the local search optimal solution as the current actual cost;

[0113] Disconnect the intermediate path including the two shot points, and migrate one of the two obtained planned paths after disconnection to the planned path of another vibrator to obtain new planning data; the intermediate path is a segment of the planned path in the current planning data;

[0114] Use the simulation excitation model based on the TD rule to simulate multiple vibrators to obtain the cost of the new planning data as the new actual cost;

[0115] When the new actual cost is less than the current actual cost, replace the current planning data with the new planning data;

[0116] Repeat the above steps until the segment migration local optimal solution is obtained.

[0117] In one embodiment, the actual cost is expressed by the following formula:

[0118] T = max i (T iw + T ir + T im )

[0119] where T is the actual cost, T iw is the scanning time of the i-th vibrator, T ir is the waiting time of the i-th vibrator to avoid harmonic interference, T im is the moving time of the i-th vibrator from the current shot point to the next shot point after the work of the i-th vibrator ends;

[0120] The moving time of each vibrator truck is expressed by the following formula:

[0121]

[0122] x = (x (1) , x (2) ,..., x (j) ,..., x (n) ) ∈ P n

[0123] where x is the driving path of the vibrator, and n is the total number of shot points in the driving path of the vibrator; is the distance between the i-th shot point and the (i + 1)-th shot point on the driving path of the vibrator, and P n is the set of all permutations of the shot points that the vibrator needs to pass through, α is the penalty term coefficient, is the included angle formed by the (i - 1)-th, i-th, and (i + 1)-th shot points in the driving path of the vibrator.

[0124] In one embodiment, simulating multiple vibrators using a simulation excitation model based on the TD rule includes:

[0125] Putting all the vibrator states into a dynamic loop pool, and the dynamic loop pool classifies and updates the states of the vibrators in real time;

[0126] Calculating the distances between different vibrators every preset period according to the current planning data;

[0127] Exciting the vibrators with the state of ready according to a certain priority order according to the predefined TD rule, and modifying the state of the excited vibrators to working;

[0128] For a vibroseis in a standby state, after a predefined TD rule is satisfied between this vibroseis and a vibroseis in a working state, this vibroseis is sorted by priority and its state is updated to ready;

[0129] When all vibroseis have completed the shot points of their respective bundles, the actual cost is obtained.

[0130] An embodiment of the present invention also provides a computer device, Figure 7 which is a schematic diagram of the computer device in the embodiment of the present invention. The computer device 700 includes a memory 710, a processor 720, and a computer program 730 stored on the memory 710 and executable on the processor 720. When the processor 720 executes the computer program 730, the above-described vibroseis excitation control method based on the time-distance rule is implemented.

[0131] An embodiment of the present invention also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-described vibroseis excitation control method based on the time-distance rule is implemented.

[0132] An embodiment of the present invention also provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the above-described vibroseis excitation control method based on the time-distance rule is implemented.

[0133] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0134] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0135] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in one or more of the processes and / or blocks Figure 1 one or more processes and / or blocks Figure 1 specified in the block or blocks.

[0136] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more of the processes and / or blocks Figure 1 one or more processes and / or blocks Figure 1 specified in the block or blocks.

[0137] The specific embodiments described above further elaborate on the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for controlling the excitation of a vibrator based on a time-distance rule, characterized in that, it includes: Obtain the current planning data of multiple vibrators; wherein, the planning data includes the positions and planned paths of the vibrators; In the connected graph of shot point distribution in the work area to be analyzed, perform local search on the current planning data to obtain the local search optimal solution; when performing local search, use a simulation excitation model based on the time-distance TD rule to simulate multiple vibrators to obtain the actual cost; In the connected graph of shot point distribution in the work area to be analyzed, perform segment migration local search between the planned paths of each vibrator in the local search optimal solution to obtain the segment migration local optimal solution; when performing segment migration local search, use a simulation excitation model based on the TD rule to simulate multiple vibrators to obtain the actual cost; Take the segment migration local optimal solution as the current planning data, and repeat the above steps until the iteration termination condition is reached, and output the current planning data.

2. The method according to claim 1, characterized in that, In the connected graph of shot point distribution in the work area to be analyzed, perform local search on the current planning data to obtain the local search optimal solution, including: In the connected graph of shot point distribution in the work area to be analyzed, use the following bilateral exchange local search method to perform local search on the current planning data to obtain the local search optimal solution: In the connected graph of shot point distribution, randomly select two different shot points, use a simulation excitation model based on the TD rule to simulate multiple vibrators to obtain the cost of the current planning data as the current actual cost; Reverse the intermediate path including the two shot points to obtain a neighboring solution; the intermediate path is a segment of the planned path in the current planning data; Use a simulation excitation model based on the TD rule to simulate multiple vibrators to obtain the cost of the new planning data composed of the neighboring solution as the new actual cost; When the new actual cost is less than the current actual cost, update the intermediate path including the two shot points to the neighboring solution; Repeat the above steps until the local optimal solution is obtained.

3. The method according to claim 1, characterized in that, In the connected graph of shot point distribution in the work area to be analyzed, perform segment migration local search between the planned paths of each vibrator in the local search optimal solution to obtain the segment migration local optimal solution, including: In the planned paths of each vibrator in the local search optimal solution, randomly select two different shot points, use a simulation excitation model based on the TD rule to simulate multiple vibrators to obtain the cost of the local search optimal solution as the current actual cost; Disconnect the intermediate path including the two shot points, and after disconnection, migrate one of the two obtained planned paths to the planned path of another vibrator to obtain new planning data; the intermediate path is a segment of the planned path in the current planning data; Use a simulation excitation model based on the TD rule to simulate multiple vibrators to obtain the cost of the new planning data as the new actual cost; When the new actual cost is less than the current actual cost, replace the current planning data with the new planning data; Repeat the above steps until the segment migration local optimal solution is obtained.

4. The method according to claim 1, wherein, the actual cost is expressed by the following formula: T = max i (T iw + T ir + T im ) Among them, T is the actual cost, T iw is the scanning time of the i-th vibrator, T ir is the waiting time of the i-th vibrator to avoid harmonic interference, T im is the moving time of the i-th vibrator from the current shot point to the next shot point after the work is completed; the moving point time of each vibrator truck is expressed by the following formula: x = (x (1) , x (2) ,..., x (j) ,..., x (n) ) ∈ P n Wherein, x is the traveling path of the vibroseis, and n is the total number of shot points in the traveling path of the vibroseis; is the distance between the i-th shot point and the (i + 1)-th shot point on the traveling path of the vibroseis, and P n is the set of all permutations of the shot points that the vibroseis needs to pass through, α is the penalty term coefficient, is the included angle formed by the (i - 1)-th, i-th, and (i + 1)-th shot points in the traveling path of the vibroseis.

5. The method according to claim 1, wherein, simulating multiple vibrators by using a simulation excitation model based on the TD rule, including: putting all the vibrator states into a dynamic loop pool, and the dynamic loop pool classifies and updates the states of the vibrators in real time; calculating the distances between different vibrators every preset period according to the current planning data; exciting the vibrators in the ready state in a certain priority order according to the predefined TD rule, and modifying the state of the excited vibrator to working; for the vibrator in the ready state, after the predefined TD rule is satisfied between the vibrator and the vibrator in the working state, the vibrator enters the priority sorting and updates the state to ready; when all the vibrators complete the shot points of the wire harness where they are located, the actual cost is obtained.

6. A vibrator excitation control device based on the time-distance rule, wherein, it includes: a planning data acquisition module for acquiring the current planning data of multiple vibrators; wherein, the planning data includes the positions and planning paths of the vibrators; a local search module for performing local search on the current planning data in the shot point distribution connectivity graph of the work area to be analyzed to obtain the local search optimal solution; when performing local search, simulating multiple vibrators by using a simulation excitation model based on the time-distance TD rule to obtain the actual cost; a segment migration local search module for performing segment migration local search between the planning paths of each vibrator in the local search optimal solution in the shot point distribution connectivity graph of the work area to be analyzed to obtain the segment migration local optimal solution; when performing segment migration local search, simulating multiple vibrators by using a simulation excitation model based on the TD rule to obtain the actual cost; an iteration module for using the segment migration local optimal solution as the current planning data, repeating the above steps until the iteration termination condition is reached, and outputting the current planning data.

7. The device according to claim 6, wherein, the local search module is specifically used for: performing local search on the current planning data in the shot point distribution connectivity graph of the work area to be analyzed by using the following bilateral exchange local search method to obtain the local search optimal solution: randomly selecting two different shot points in the shot point distribution connectivity graph, and simulating multiple vibrators by using a simulation excitation model based on the TD rule to obtain the cost of the current planning data as the current actual cost; reversing the intermediate path including the two shot points to obtain a neighboring solution; the intermediate path is a section of the planning path of the current planning data; simulating multiple vibrators by using a simulation excitation model based on the TD rule to obtain the cost of the new planning data composed of the neighboring solution as the new actual cost; when the new actual cost is less than the current actual cost, updating the intermediate path including the two shot points to the neighboring solution; repeating the above steps until the local optimal solution is obtained.

8. The device according to claim 6, wherein, The segment migration local search module is specifically used for: Randomly select two different shot points from the planned paths of each controllable vibration source in the local search optimal solution, and use the simulation excitation model based on the TD rule to simulate multiple controllable vibration sources to obtain the cost of the local search optimal solution as the current actual cost; Disconnect the intermediate path including the two shot points, and migrate one of the two obtained planned paths after disconnection to the planned path of another controllable vibration source to obtain new planned data; the intermediate path is a section of the planned path of the current planned data; Use the simulation excitation model based on the TD rule to simulate multiple controllable vibration sources to obtain the cost of the new planned data as the new actual cost; When the new actual cost is less than the current actual cost, replace the current planned data with the new planned data; Repeat the above steps until the segment migration local optimal solution is obtained.

9. The device according to claim 6, wherein, The actual cost is expressed by the following formula: T = max i (T iw + T ir + T im ) Among them, T is the actual cost, T iw is the scanning time of the i-th vibrator, T ir is the waiting time of the i-th vibrator to avoid harmonic interference, T im is the moving time of the i-th vibrator from the current shot point to the next shot point after the work is completed; The moving point time of each vibration source vehicle is expressed by the following formula: x = (x (1) , x (2) , …, x (j) , …, x (n) ) ∈ P n Wherein, x is the traveling path of the vibrator, and n is the total number of shot points in the traveling path of the vibrator; is the distance between the i-th shot point and the (i + 1)-th shot point on the traveling path of the vibrator, and P n is the set of all permutations of the shot points that the vibrator needs to pass through, α is the penalty term coefficient, is the included angle formed by the (i - 1)-th, i-th, and (i + 1)-th shot points in the traveling path of the vibrator.

10. The device according to claim 6, wherein, Using the simulation excitation model based on the TD rule to simulate multiple controllable vibration sources includes: Put all the vibration source states into a dynamic loop pool, and the dynamic loop pool classifies and updates the states of the vibration sources in real time; According to the current planned data, calculate the distances between different controllable vibration sources every preset period; According to the predefined TD rule, excite the controllable vibration sources with the state of ready in a certain priority order, and modify the state of the excited controllable vibration source to working; For the controllable vibration sources in the ready state, after the predefined TD rule is satisfied between the controllable vibration source and the controllable vibration source with the state of working, the controllable vibration source enters the priority sorting and updates the state to ready; When all the controllable vibration sources complete the shot points of their respective wire harnesses, the actual cost is obtained.

11. A computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein, When the processor executes the computer program, it implements the method according to any one of claims 1 to 5.

12. A computer-readable storage medium, wherein, The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the method according to any one of claims 1 to 5.

13. A computer program product, wherein, The computer program product includes a computer program, and when the computer program is executed by a processor, it implements the method according to any one of claims 1 to 5.

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