Time distance rule based vibroseis firing control method and apparatus

Abstract

The application discloses a time distance rule-based controllable source excitation control method and device, and relates to the field of seismic exploration. The method comprises the following steps: performing local search on current planning data in a shot point distribution connected graph of a work area to be analyzed to obtain a local search optimal solution; when the local search is performed, a simulation excitation model based on a TD rule is used to simulate a plurality of controllable sources to obtain actual costs; performing segment migration local search between the planning paths of the controllable sources in the local search optimal solution in the shot point distribution connected graph of the work area to be analyzed to obtain a segment migration local optimal solution; when the segment migration local search is performed, the simulation excitation model based on the TD rule is used to obtain actual costs; the segment migration local optimal solution is taken as the current planning data, and the above steps are repeatedly executed until an iteration termination condition is reached, and the current planning data is output. The application can realize deep integration of the time distance rule and path planning, and improve the production efficiency of controllable source excitation control.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of oil and gas exploration, and particularly relates to a time-distance rule-based vibroseis excitation control system and method. BACKGROUND

[0002] This section is intended to provide background or context to the embodiments of the application recited in the claims. The description herein does not constitute admission that the prior publication 5, inventorship, or a combination of the foregoing, is prior art to the present application.

[0003] Seismic exploration is a method of obtaining the shape and physical properties of the underground strata by artificially exciting seismic waves and analyzing their propagation in the ground. Currently, seismic exploration is the most important and widely used means of exploring underground mineral resources (such as oil). As the difficulty of oil exploration increases, the safety, accuracy and efficiency of seismic exploration are increasingly required. As one of the main technologies for seismic data acquisition, the application of the vibroseis is becoming more and more widespread.

[0004] The vibroseis is a mechanical seismic source that relies on a vibrator installed on a vibroseis vehicle to continuously impact the ground to generate seismic waves. Compared with traditional explosives and heavy hammer excitation of seismic waves, the vibroseis can customize parameters such as excitation frequency and scanning time according to different work areas and terrain conditions. At the same time, the vibroseis does not produce seismic frequencies that do not propagate in the strata, does not damage the rock, can save energy, has strong anti-interference ability, can improve the signal-to-noise ratio of the collected data, and causes less damage to the ground, allowing exploration in densely populated areas. The vibroseis exploration has gone through the experimental stage, large-scale application stage, and gradually matured, and its advantages have become increasingly prominent. With the requirement for collection efficiency, the vibroseis has entered the high-efficiency collection stage, and the collection technology has made great progress, with several new scanning operation modes emerging.

[0005] Currently, the vibroseis excitation mainly uses manual control methods for path planning and excitation control, and there is a lot of room for improvement in efficiency. It is urgent to design targeted intelligent optimization algorithms to further improve efficiency and reduce exploration costs.

[0006] With the development of society, people's demand for green environmental protection and safe and efficient is becoming higher and higher. The use of high-efficiency collection technology of the vibroseis will certainly become the direction of future development. One of the main factors restricting the use of high-efficiency collection technology of the vibroseis is production efficiency, which is closely related to the excitation method. Therefore, the optimization of the excitation efficiency of the vibroseis has become the focus of the high-efficiency collection technology of the vibroseis.

[0007] In actual production, in order to increase the efficiency of exploration operation, multiple vibroseis trucks often need to operate simultaneously, and when the time interval of each other excitation is short, harmonic interference is prone to occur. In order to avoid the influence between the vibroseis trucks, the excitation time of different vibrators needs to be controlled. For every two vibrators with a certain distance, the start time interval needs to meet the given "time distance rule (TD rule)", and for the vibrators that do not meet the rule, they need to wait until the conditions are met before starting. For the vibrators that meet the rule, the selection of the starting vehicle is needed.

[0008] It can be seen that the total construction time of the vibroseis truck is composed of the scanning time of the vibroseis, the waiting time of the vibroseis truck to avoid harmonic interference, and the moving point time of the vibroseis truck from the current shot point to the next shot point after the work is finished. Due to the requirements of the work area and the quality of collected data, the working time of the vibroseis truck is generally difficult to reduce, so the optimization of the excitation efficiency is focused on reducing the moving point time and the waiting time of the vibroseis truck. The moving point time mainly depends on the planning of the path of each vibrator, and the total length of the waiting time is closely related to the planning of the path of the vibrator and the selection of the starting vehicle each time, so the optimization of the excitation efficiency is a multi-objective optimization problem.

[0009] In recent years, the high-efficiency acquisition technology of vibroseis has made great progress, and in fact, these high-efficiency acquisition methods of vibroseis are all around the constraints of'space' and 'time' to improve production efficiency. Here, the space refers to the distance between the vibrators, and the time refers to the time interval of starting vibration between the vibrators. In dynamic sliding scanning, different excitation methods are integrated, and each excitation method corresponds to a different time distance rule. After sorting, a function describing the distance between two groups of vibrators and the minimum start time interval in dynamic sliding scanning is obtained, which is called TD (Time & Distance) rule. The TD rule is an important function related to the production efficiency and data quality in seismic acquisition, which balances the construction efficiency of the vibrator and the harmonic interference caused by the short start time interval.

[0010] In order to pursue high efficiency, usually take the way to shorten the sliding time T, followed by the data quality deterioration, from non-interference to mild interference, moderate interference, and even the data aliasing. Emergence of harmonic interference suppression technology, adjacent interference suppression technology, aliasing data separation technology. It is due to the effective use of these technologies that the sliding time T can be gradually shortened, and the efficiency can be greatly improved step by step. But not the smaller the better, because the interference suppression and data separation technology has its own applicable conditions, and has damage to the effective data. At this time, we can adjust the source spacing D, which can effectively reduce the interference and improve the data quality. But D can not be too large in actual production. Through the production exploration and the development of denoising technology, the effective TD rule can be found to balance the production efficiency and data quality.

[0011] TD rules are generally divided into conventional step TD rules and ladder TD rules. The conventional step TD rule is simple and easy to understand. According to the collection efficiency from high to low, the priority is set. When the distance is short, it is alternating scanning, when the distance is slightly far, it is sliding scanning, and when the distance is far, it is synchronous scanning. The TD rule presents a ladder function pattern. The selection of step TD rule parameters is relatively simple, but the disadvantage is that the alternating scanning time is too long. At the right end of the alternating scanning stage, the harmonic interference is no longer obvious because the distance between the source vehicles is large, but it is still less efficient than using sliding scanning. The ladder TD rule further improves the fixed time sliding scanning. That is, it corresponds to the controllable source time variation. Through statistical analysis, it is found that the harmonic energy is very strong at the excitation point, and the data collection interference is more serious. But with the increase of the propagation distance, the harmonic energy decreases in an approximate inverse function curve. In a place far from the excitation point, the harmonic has the characteristics of linear slow decay. Therefore, when the distance between the two source vehicles is far, the sliding time can be reduced according to the decay law of the harmonic energy at the far excitation point, so as to ensure the quality of the collected data and improve the collection efficiency. The ladder TD rule is based on the conventional step TD rule. The fixed time interval of sliding scanning is optimized to a time interval that decreases in a linear function form. It has the characteristics of flexibility and high efficiency, and has been widely applied and verified in actual production.

[0012] TD rules can be flexibly changed according to different needs of the excitation project, meet different exploration tasks, and comprehensively consider the exploration efficiency, noise size and exploration method to determine the TD rule suitable for the project, which is of great significance to the completion of the whole project.

[0013] Here we assume that when a shooting plan meets the TD rule, it will adapt to the requirements of a specific scanning mode. Therefore, when optimizing the shooting control, the vehicle path and vehicle vibration time are directly controlled under the condition of meeting the TD rule, and it is no longer discussed which specific scanning mode it is. For example,Figure 1 TD rule function, such as Figure 1 The middle fork point is marked, at this time, due to the harmonic influence, the data collected will become a waste shot, only the points above the TD rule function are effective shots, such as Figure 1 The middle circle point is marked.

[0014] At present, the selection and path planning of the starting vehicle still mainly rely on artificial experience judgment, and the efficiency still has a large space for improvement. SUMMARY

[0015] In a first aspect, the embodiments of the present application provide a time-distance rule based controlled source shooting control method, which can realize deep integration of time-distance rule and path planning, and improve the production efficiency of controlled source shooting control. The method comprises the following steps:

[0016] obtaining current planning data of a plurality of controlled sources; wherein the planning data comprises point positions and planning paths of the controlled sources;

[0017] performing local search on the current planning data in a shot point distribution connected graph of a work area to be analyzed to obtain a local search optimal solution; in the local search, a simulation shooting model based on a time-distance (TD) rule is used to simulate the plurality of controlled sources to obtain actual costs;

[0018] performing segment migration local search between the planning paths of the controlled sources in the local search optimal solution in the shot point distribution connected graph of the work area to be analyzed to obtain a segment migration local optimal solution; in the segment migration local search, the simulation shooting model based on the TD rule is used to simulate the plurality of controlled sources to obtain actual costs;

[0019] repeating the above steps by taking the segment migration local optimal solution as the current planning data until an iteration termination condition is reached, and outputting the current planning data.

[0020] In a second aspect, the embodiments of the present application further provide a time-distance rule based controlled source shooting control device, which can realize deep integration of time-distance rule and path planning, successfully predict the production efficiency in different work areas, and is of great significance for improving the production efficiency of actual controlled source efficient acquisition. The device comprises the following steps:

[0021] a planning data obtaining module, configured to obtain current planning data of a plurality of controlled sources; wherein the planning data comprises point positions and planning paths of the controlled sources;

[0022] The local search module is configured to perform local search on the current planning data in the shot distribution connected graph of the work area to be analyzed to obtain a local search optimal solution; and when performing the local search, the actual cost is obtained by simulating the multiple vibrators using a simulation shooting model based on a time distance (TD) rule.

[0023] The segment migration local search module is configured to perform segment migration local search between the planned paths of the multiple vibrators in the local search optimal solution in the shot distribution connected graph of the work area to be analyzed to obtain a segment migration local optimal solution; and when performing the segment migration local search, the actual cost is obtained by simulating the multiple vibrators using a simulation shooting model based on the TD rule.

[0024] The iteration module is configured to repeatedly execute the above steps by taking the segment migration local optimal solution as the current planning data until an iteration termination condition is reached, and output the current planning data.

[0025] In a third aspect, an embodiment of the present application further provides a computer device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the above-mentioned time distance rule-based vibrator shooting control method when executing the computer program.

[0026] In a fourth aspect, an embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program implements the above-mentioned time distance rule-based vibrator shooting control method when executed by a processor.

[0027] In a fifth aspect, an embodiment of the present application further provides a computer program product, which comprises a computer program, and the computer program implements the above-mentioned time distance rule-based vibrator shooting control method when executed by a processor.

[0028] In the embodiment of the present application, current planning data of a plurality of controllable sources is obtained; wherein, the planning data comprises point positions and planning paths of the controllable sources; local search is performed on the current planning data in a shot point distribution connectivity graph of a work area to be analyzed to obtain a local search optimal solution; in the local search, a simulation excitation model based on TD rules is used to simulate the plurality of controllable sources to obtain actual costs; segment migration local search is performed between the planning paths of the controllable sources in the local search optimal solution in the shot point distribution connectivity graph of the work area to be analyzed to obtain a segment migration local optimal solution; in the segment migration local search, the simulation excitation model based on TD rules is used to simulate the plurality of controllable sources to obtain actual costs; the segment migration local optimal solution is taken as the current planning data, and the above steps are repeatedly executed until an iteration termination condition is reached, and the current planning data is output. Compared with the prior art in which controllable source excitation control is mainly performed by relying on manual experience, the embodiment of the present application performs local search on the current planning data to obtain a local search optimal solution, then performs segment migration local search between the planning paths of the controllable sources in the local search optimal solution to obtain a segment migration local optimal solution; in the above search process, the simulation excitation model based on TD rules is used to simulate the plurality of controllable sources to obtain actual costs, thereby realizing deep integration of TD rules and path planning and improving the production efficiency of controllable source excitation control. BRIEF DESCRIPTION OF DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings. In the drawings:

[0030] Figure 1 TD rule schematic diagram for efficient controllable source excitation in the embodiment of the present application;

[0031] Figure 2 Flowchart of the controllable source excitation control method based on the time distance rule in the embodiment of the present application;

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

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

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

[0035] Figure 6A structural block diagram of the controllable source excitation control device based on a time distance rule in the embodiment of the present application is shown in the figure.

[0036] Figure 7 A schematic diagram of the computer device in the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0037] To make the purpose, technical scheme and advantages of the embodiment of the present application clearer and more understandable, the embodiment of the present application is further described in detail below with reference to the drawings. Herein, the schematic embodiment of the present application and its description are used to explain the present application but not as a limitation to the present application.

[0038] The inventor believes that the controllable source exploration technology is to explore by means of artificial seismic source through controlling the frequency spectrum characteristics of the signal generated by the artificial seismic source, and the controllable source acquisition technology has become an indispensable means for oil exploration with its advantages of environmental protection, safety and flexibility. In order to increase the efficiency of exploration operation, multiple controllable source vehicles often need to operate simultaneously, sequentially visit the pre-planned source points in the specified area and vibrate one by one. In order to avoid harmonic interference between the source vehicles, when two source vehicles with a short distance need to vibrate at the same time, the vibration time of the two source vehicles needs to be controlled so as to meet the given "time distance rule (TD rule)". The controllable source excitation problem can be described as how to allocate the source points and plan the vibration path of each vehicle in the environment of multiple source vehicles so as to make the parallel operation time shortest under the condition of meeting the TD rule. At present, the manual control method is mainly used for excitation path planning and control, and the efficiency has a large room for improvement. The present application aims to design a targeted intelligent excitation optimization algorithm to further improve the efficiency and reduce the exploration cost.

[0039] Figure 2 A flow chart of the controllable source excitation control method based on the time distance rule in the embodiment of the present application is shown in the figure, which comprises:

[0040] Step 201, obtaining current planning data of multiple controllable sources; wherein, the planning data comprises the point and the planned path of the controllable source;

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

[0043] Step 204, taking the segment migration local optimal solution as the current planning data, repeatedly performing the above steps until reaching the iteration termination condition, and outputting the current planning data.

[0044] Compared with the prior art, in the embodiment of the present application, the current planning data is locally searched to obtain a local optimal solution, and then segment migration local search is performed between the planning paths of each controllable vibrator in the local optimal solution to obtain a segment migration local optimal solution; in the above search process, the actual cost is obtained by simulating the multiple controllable vibrators by using the simulation excitation model based on the TD rule, the TD rule and the path planning are deeply integrated, and the production efficiency of the controllable vibrator excitation control is improved.

[0045] In the embodiment of the present application, the controllable vibrator is a vibrator truck, and in specific implementation, in order to optimize the excitation efficiency of the controllable vibrator, the total working time thereof is shortened as much as possible, and in an actual work area, a multi-group vibrator truck is generally used for slice operation, and the construction time of the multiple controllable vibrators is the actual cost, which is expressed by the following formula:

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

[0047] Wherein, T is the actual cost, T iw is the scanning time of the i th controllable vibrator, T ir is the waiting time of the i th controllable vibrator to avoid harmonic interference, and T im is the moving point time of the i th controllable vibrator from the current shot point to the next shot point after the i th controllable vibrator is worked.

[0048] Since the scanning time is often determined by the project condition and the work area and is generally a fixed value, the present application designs an algorithm for the waiting time and the moving point time and optimizes the modeling, establishes a controllable vibrator path optimization model for the moving point time, and designs a simulation excitation model based on the TD rule for the waiting time.

[0049] The controllable vibrator path optimization model is described below. Since the shot points to be collected are determined in a work area, each shot point needs to be collected only once, and the starting point of the vibrator truck is generally fixed in the actual situation. If there is only one controllable vibrator, the controllable vibrator 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 controlled source, n is the total number of shot points in the driving path of the controlled source; is the interval between the i-th shot point and the i+1-th shot point on the driving path of the controlled source, P n is the set of all permutations of the shot points that the controlled source needs to pass through.

[0053] But in order to be efficient in acquisition, often there are multiple groups of controlled sources in the same work area for simultaneous operation, so multiple path planning is needed for fixed shot points. At the same time, the biggest difference between this path optimization problem and the conventional path optimization problem is that the smaller the turning angle is, the better it is, so the turning angle of each shot point is added as a penalty term to the total driving cost calculation. If a vehicle travels from point A to point C after passing through point B, the path cost is:

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

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

[0056] Since the improvement of the controlled source excitation efficiency is a multi-objective optimization problem, both path optimization and controlled source excitation sequence optimization (i.e. controlled source point position) can improve the excitation efficiency, so a local optimal solution that is optimized in multiple aspects is expected. Specifically, the length and turning angle of the path in each controlled source can be iteratively optimized through the double-sided exchange of the controlled source path, and then the point position distribution between vehicles is iteratively optimized and updated according to the segment migration method under the TD rule, to realize the optimization of path shot point division and operation time under the TD rule constraint, and then the above two iterations are repeated to obtain a local optimal solution, so as to realize the deep integration of path optimization and controlled source point position optimization, and obtain a feasible solution with the minimum operation time under the TD rule.

[0057] In step 201, current planning data of a plurality of controlled sources is obtained; wherein the planning data includes the point position and the planned path of the controlled source;

[0058] After adding the path turning penalty term, the controlled source path optimization model is:

[0059]

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

[0061] Wherein, x is the driving path of the controlled source, n is the total number of shot points in the driving path of the controlled source; is the interval between the i th shot point and the i+1 th shot point on the driving path of the controlled source, P n is the set of all permutations of the shot points that the controlled source needs to pass through, and alpha is the penalty term coefficient, is the angle formed by the i-1 th, i th and i+1 th shot points in the driving path of the controlled source.

[0062] The above controlled source path optimization model represents the moving point time of each controlled source, and the embodiment of the present application adopts the controlled source path optimization model represented by the plurality of controlled sources.

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

[0064] In step 202, local search is performed on the current planning data in the shot point distribution connected graph of the work area to be analyzed to obtain a local search optimal solution; when performing local search, a simulation excitation model based on TD rules is used to simulate a plurality of controlled sources to obtain actual costs;

[0065] The embodiment of the present application simultaneously optimizes the controlled source point position and path, and is a multi-objective optimization problem, therefore, a two-stage iterative local search method is designed according to the foregoing model, a double exchange local search method is used as the core of the controlled source path optimization iteration, a TD rule under segment migration local search method is used as the measurement index of the controlled source path cost, and the two are deeply integrated, so that the simulation of efficient excitation of the controlled source under different conditions is realized.

[0066] In the case of a fixed source vehicle starting point, the path optimization problem of a single controlled source is a TSP problem (traveling salesman problem), and the double exchange local search method is a local optimization algorithm, which reduces the path distance by changing the order of the points passed through in a path. If the distance of the path is reduced, the improved path is retained. Otherwise, the path returns to the original state. In a plurality of controlled sources, the specific steps of the double exchange local search method are described as follows.

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

[0068] In the shot distribution connected graph of the work area to be analyzed, the following double-sided exchange local search method is used to perform local search on the current planning data to obtain a local search optimal solution:

[0069] In the shot distribution connected graph, two different shots are randomly selected, and the cost of the current planning data obtained by simulating a plurality of vibrators by using a simulation excitation model based on the TD rule is used as the current actual cost;

[0070] The intermediate path including the two shots is reversed to obtain a neighbor solution; the intermediate path is a path in the planning path of the current planning data;

[0071] The cost of the new planning data composed of the neighbor solution obtained by simulating a plurality of vibrators by using a simulation excitation model based on the TD rule is used as the new actual cost;

[0072] When the new actual cost is less than the current actual cost, the intermediate path including the two shots is updated to the neighbor solution;

[0073] The above steps are repeatedly executed until a local optimal solution is obtained.

[0074] Referring to Figure 3 , the current path in the current planning data is as follows: from A to H and then back to A, passing through all the shots of a vibrator, and it is assumed that this path is the shortest path; two different shots are randomly selected, and the route in the middle of the two shots is reversed, so that a neighbor solution is obtained; for example, C and F are randomly selected, and the old path is divided into three segments; the middle segment is reversed to obtain a new path. If the cost of the new path is less than that of the current path, the path is updated; if the total length of the new path is greater than that of the current path, the shortest path is not updated, and finally converges to a local optimal solution. It can be considered that the path is the shortest path.

[0075] In step 203, in the shot distribution connected graph of the work area to be analyzed, segment migration local search is performed between the planning 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, the actual cost is obtained by simulating a plurality of vibrators by using a simulation excitation model based on the TD rule;

[0076] Since the TD rule is an important constraint of vibroseis excitation, the total operation time is as short as possible under the condition of meeting the TD rule, therefore, the embodiment of the application realizes a cost optimization method based on segment migration between different vibroseis paths based on the simulation excitation model of the TD rule, the purpose is to try to transfer the path segment of the longest vehicle to another vehicle path, and then reduce the driving cost of the longest vehicle, and achieve load balancing between vehicles, and the method redistributes the shot points of each path according to the longest completion time of each path under the TD rule.

[0077] Referring to Figure 4 For the principle of segment migration local search in the embodiment of the application, in an embodiment, in the shot point distribution connected graph of the work area to be analyzed, segment migration local search is performed between the planned paths of each vibroseis in the local search optimal solution, and a segment migration local optimal solution is obtained, including:

[0078] In the planned paths of each vibroseis in the local search optimal solution, two different shot points are randomly selected, and the cost of the local search optimal solution is obtained by simulating multiple vibroseises based on the simulation excitation model of the TD rule, as the current actual cost;

[0079] Disconnect the middle path including the two shot points, and one of the two planned paths obtained after disconnection is migrated to the planned path of another vibroseis, and new planning data is obtained; the middle path is a path in the planned path of the current planning data;

[0080] The cost of the new planning data is obtained by simulating multiple vibroseises based on the simulation excitation model of the TD rule, as the new actual cost;

[0081] When the new actual cost is less than the current actual cost, the new planning data replaces the current planning data;

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

[0083] In specific implementation, since multiple groups of vibroseises need to meet the constraint of the TD rule in the exploration process, the TD rule not only constrains the spatial distance of two vibroseises, but also constrains the time sequence of the vibroseis excitation point, therefore, the simulation excitation model based on the TD rule is designed for the actual vibroseis multi-path exploration:

[0084] min x cost TD (x,λ)

[0085] Wherein: cost is the cost of the path operation obtained by simulation considering the TD rule; x is the planning data, including the controllable source point distribution and the path planning scheme; and λ is the parameter set required by the TD rule constraint. The parameter set includes the number of source vehicles and the shot distribution. The following gives the steps of simulating multiple controllable sources by using the simulation excitation model based on the TD rule.

[0086] In an embodiment, the simulation of multiple controllable sources by using the simulation excitation model based on the TD rule comprises the following steps.

[0087] All source states are put into a dynamic circulation pool which classifies and updates the states of the sources in real time.

[0088] According to the current planning data, the distance between different controllable sources is calculated every preset period.

[0089] According to the predefined TD rule, the controllable sources in the ready state are excited in a certain priority order, and the state of the controllable source to be excited is modified to working.

[0090] For the controllable source in the ready state, when the controllable source and the controllable source in the working state satisfy the predefined TD rule, the controllable source is entered into the priority order and the state is updated to ready.

[0091] When all controllable sources complete the shot points of the beam, the actual cost is obtained.

[0092] In specific implementation, in order to ensure the uniformity of the excitation times of the controllable sources and prevent the increase of the overall actual cost caused by the long waiting time of some controllable sources, the excitation times of the controllable sources currently ready to start are set in the order from small to large, and the controllable sources are excited in the order of priority. After excitation, the state of the controllable source is updated to working. The movement, waiting, working and other states of the controllable sources are reflected in the model. The simulation excitation model based on the TD rule is embedded into the local search, so that the waiting time of the controllable sources can be optimized and the production efficiency can be improved.

[0093] In step 204, the segment migration local optimal solution is taken 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.

[0094] In specific implementation, 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 embodiments of the application.

[0096] In a work area, a connected graph with 500 shot points is constructed, and the determined shot point number and coordinates are provided, and the number of vibroseis is 4. Since in actual exploration, the work area is generally rectangular, the test problem adopts a rectangular lattice with different scales, the interval between each shot point is 50 meters, random disturbance subject to two-dimensional normal distribution is added, the given vibroseis speed is 10 m / s, the maximum constraint distance in the TD rule is 400 m, when the distance between two vibroseis is greater than or equal to 400 m, the sliding time is 0 s; when the distance between two vibroseis 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 change relationship). The operation time is 6 s, and the shot points of each vibroseis path are evenly distributed.

[0097] The method proposed in the present application is implemented for the above example, and the iteration convergence curve of the final method is as shown in Figure 5 The actual cost fluctuates within the preset range, the iteration ends, and it can be seen that the optimization effect of the local search is very significant through the algorithm iteration optimization. Since the initial solution is a random solution (current planning data), the optimization effect of the first iteration is often the most significant, and the algorithm converges faster. Due to the better initial random solution, the initial solution is selected in the subsequent calculation to reduce the number of iterations and improve the running efficiency.

[0098] The embodiment of the present application also proposes a vibroseis excitation control generation device based on a time distance rule, which has a principle similar to the vibroseis excitation control generation method based on a time distance rule, and details are not repeated here.

[0099] Figure 6 The present application is based on a time distance rule for a vibroseis excitation control generation device, and the schematic diagram comprises:

[0100] The planning data obtaining module 601 is used for obtaining the current planning data of the plurality of vibroseis; wherein, the planning data comprises the point position and the planning path of the vibroseis;

[0101] The local search module 602 is used for performing local search on the current planning data in the shot point distribution connected graph of the work area to be analyzed, and obtaining the local search optimal solution; when performing local search, the actual cost is obtained by simulating the plurality of vibroseis by using the simulation excitation model based on the TD rule;

[0102] The segment migration local search module 603 is used for performing segment migration local search between the planning paths of each vibroseis in the local search optimal solution in the shot point distribution connected graph of the work area to be analyzed, and obtaining the segment migration local optimal solution; when performing segment migration local search, the actual cost is obtained by simulating the plurality of vibroseis by using the simulation excitation model based on the TD rule;

[0103] The iteration module 604 is configured to repeat the above steps by taking the local optimal solution of the segment migration as the current planning data until an iteration termination condition is reached, and output the current planning data.

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

[0105] In the shot distribution connectivity graph of the work area to be analyzed, the following double-sided exchange local search method is used to perform local search on the current planning data to obtain a local optimal solution:

[0106] In the shot distribution connectivity graph, two different shots are randomly selected, and the cost of the current planning data is obtained by simulating a plurality of vibrators using a simulation excitation model based on the TD rule as the current actual cost.

[0107] The intermediate path including the two shots is reversed to obtain a neighbor solution; the intermediate path is a segment of the planning path of the current planning data.

[0108] The cost of the new planning data composed of the neighbor solution is obtained by simulating a plurality of vibrators using a simulation excitation model based on the TD rule as a new actual cost.

[0109] When the new actual cost is less than the current actual cost, the intermediate path including the two shots is updated to the neighbor solution.

[0110] The above steps are repeated until a local optimal solution is obtained.

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

[0112] In the planning path of each vibrator in the local optimal solution, two different shots are randomly selected, and the cost of the local optimal solution is obtained by simulating a plurality of vibrators using a simulation excitation model based on the TD rule as the current actual cost.

[0113] The intermediate path including the two shots is disconnected, and one of the two planning paths obtained after disconnection is migrated to the planning path of another vibrator to obtain new planning data; the intermediate path is a segment of the planning path of the current planning data.

[0114] The cost of the new planning data is obtained by simulating a plurality of vibrators using a simulation excitation model based on the TD rule as a new actual cost.

[0115] When the new actual cost is less than the current actual cost, the new planning data is substituted for the current planning data.

[0116] The above steps are repeated until a segment migration local optimal solution is obtained.

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

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

[0119] wherein T is the actual cost, T iw is the scanning time of the i-th controlled source, T ir is the waiting time of the i-th controlled source to avoid harmonic interference, T im is the moving time of the i-th controlled source from the current shot point to the next shot point after the i-th controlled source finishes working;

[0120] The moving time of each source vehicle is expressed by the following formula:

[0121]

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

[0123] wherein x is the driving path of the controlled source, and n is the total number of shot points in the driving path of the controlled source; is the distance between the i-th shot point and the i+1-th shot point in the driving path of the controlled source, P n is the set of full permutations of the shot points to be passed through by the controlled source, and a is the penalty term coefficient, is the angle formed by the i-1-th, i-th and i+1-th shot points in the driving path of the controlled source.

[0124] In an embodiment, a simulation excitation model based on the TD rule is used to simulate a plurality of controlled sources, including:

[0125] All source states are put into a dynamic circulation pool, which classifies and updates the states of the sources in real time;

[0126] According to the current planning data, the distance between different controlled sources is calculated every preset period;

[0127] According to the predefined TD rule, the controlled sources with ready states are excited in a certain priority order, and the states of the excited controlled sources are modified to working;

[0128] When the controllable seismic source in the preparation state meets the predefined TD rule between the controllable seismic source and the controllable seismic source in the working state, the controllable seismic source is entered into the priority queue, and the state is updated to be ready;

[0129] When all controllable seismic sources complete the shot points of the online beam, the actual cost is obtained.

[0130] The embodiment of the present application further provides a computer device, Figure 7 For the schematic diagram of the computer device in the embodiment of the present application, the computer device 700 comprises a memory 710, a processor 720, and a computer program 730 stored in the memory 710 and capable of running on the processor 720, and the processor 720 implements the controllable seismic source firing control method based on the time distance rule when the computer program 730 is executed.

[0131] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the controllable seismic source firing control method based on the time distance rule.

[0132] The embodiment of the present application further provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the controllable seismic source firing control method based on the time distance rule.

[0133] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt 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.) containing computer usable program codes.

[0134] The present application is described with reference to flowcharts and / or block diagrams of the method, device (system), and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the 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 a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices produce a device for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The function of the device specified in one flow or multiple flows and / or blocks Figure 1 The function of the device specified in one flow or multiple flows and / or 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 function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the flow Figure 1 The functions of a flow or multiple flows and / or a block or multiple blocks in conjunction with the disclosed aspects can be implemented on practitioners' computers in an interactive mode or in a batch mode. Figure 1

[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 such that the instructions that are executed on the computer or other programmable apparatus provide steps for implementing the functions specified in the flow Figure 1 The functions of a flow or multiple flows and / or a block or multiple blocks in conjunction with the disclosed aspects can be implemented on practitioners' computers in an interactive mode or in a batch mode. Figure 1

[0137] The above detailed description merely describes specific embodiments of the application, and the purpose of the above detailed description is to explain the principles and technical solutions of the application, and the beneficial effects of the application. It should be understood that the above detailed description is only a specific embodiment of the application, and is not used to limit the protection scope of the application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application should be included in the protection scope of the application.​​

Claims

1. A time-distance rule based vibroseis firing control method, characterized in that, The method comprises the following steps: obtaining current planning data of a plurality of controllable vibrators; wherein, the planning data comprises point positions and planning paths of the controllable vibrators; performing local search on the current planning data in a shot point distribution connectivity graph of a work area to be analyzed to obtain a local search optimal solution; in the local search, a simulation excitation model based on a time distance (TD) rule is used to simulate the plurality of controllable vibrators to obtain actual costs; performing segment migration local search between the planning paths of the controllable vibrators in the local search optimal solution in the shot point distribution connectivity graph of the work area to be analyzed to obtain a segment migration local optimal solution; in the segment migration local search, the simulation excitation model based on the TD rule is used to simulate the plurality of controllable vibrators to obtain actual costs; repeating the above steps by taking the segment migration local optimal solution as the current planning data until an iteration termination condition is reached, and outputting the current planning data; in the shot point distribution connectivity graph of the work area to be analyzed, performing local search on the current planning data to obtain a local search optimal solution, comprising: in the shot point distribution connectivity graph of the work area to be analyzed, performing local search on the current planning data by using a double-sided exchange local search method to obtain a local search optimal solution; in the shot point distribution connectivity graph, randomly selecting two different shot points, using the simulation excitation model based on the TD rule to simulate the plurality of controllable vibrators to obtain a cost of the current planning data as a current actual cost; reversing an intermediate path between the two shot points to obtain a neighbor solution; the intermediate path is a segment path in the planning path of the current planning data; using the simulation excitation model based on the TD rule to simulate the plurality of controllable vibrators to obtain a cost of new planning data composed of the neighbor solution as a new actual cost; when the new actual cost is less than the current actual cost, updating the intermediate path between the two shot points to the neighbor solution; repeating the above steps until the local optimal solution is obtained; in the shot point distribution connectivity graph of the work area to be analyzed, performing segment migration local search between the planning paths of the controllable vibrators in the local search optimal solution to obtain a segment migration local optimal solution, comprising: in the planning paths of the controllable vibrators in the local search optimal solution, randomly selecting two different shot points, using the simulation excitation model based on the TD rule to simulate the plurality of controllable vibrators to obtain a cost of the local search optimal solution as a current actual cost; disconnecting an intermediate path between the two shot points, and migrating one of two planning paths obtained after the disconnection to a planning path of another controllable vibrator to obtain new planning data; the intermediate path is a segment path in the planning path of the current planning data; using the simulation excitation model based on the TD rule to simulate the plurality of controllable vibrators to obtain a cost of the new planning data as a new actual cost; when the new actual cost is less than the current actual cost, replacing the current planning data with the new planning data; repeating the above steps until the segment migration local optimal solution is obtained.

2. The method of claim 1, wherein, The actual cost is represented by the following formula: wherein, is the actual cost, is the scanning time of the i-th vibrator, is the waiting time of the i-th vibrator to avoid harmonic interference, 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 point moving time of each vibrator truck is represented by the following formula: wherein, is the travel path of the controllable source, n is the total number of shot points in the travel path of the controllable source; is the interval between the i-th shot point and the i+1-th shot point on the travel path of the controllable source, is the set of all permutations of the shot points that the controllable source needs to pass through, is the coefficient of the penalty term, is the angle formed by the i-1-th, i-th and i+1-th shot points in the travel path of the controllable source.

3. The method of claim 1, wherein, the simulation excitation model based on the TD rule comprises: Put all the source states into a dynamic circulation pool which classifies the states of the sources and updates in real time; According to the current planning data, calculate the distance between different controllable sources every preset period; According to the pre-defined TD rule, fire the controllable source in the ready state in a certain priority order, and modify the state of the controllable source to be fired to be working; For the controllable source in the preparation state, after the controllable source and the controllable source in the working state satisfy the pre-defined TD rule, the controllable source enters the priority order and the state is updated to be ready; When all controllable sources complete the shot points of the beam line, the actual cost is obtained.

4. A time-distance rule based controlled source excitation control device, characterized in that, Comprise: A planning data obtaining module is configured to obtain current planning data of a plurality of controllable sources; wherein the planning data comprises point positions and planning paths of the controllable sources; A local search module is configured to perform local search on the current planning data in a shot point distribution connected graph of a work area to be analyzed to obtain a local search optimal solution; when performing local search, a simulation firing model based on a time distance (TD) rule is used to simulate the plurality of controllable sources to obtain an actual cost; A segment migration local search module is configured to perform segment migration local search between the planning paths of each controllable source in the local search optimal solution in the shot point distribution connected graph of the work area to be analyzed to obtain a segment migration local optimal solution; when performing segment migration local search, a simulation firing model based on the TD rule is used to simulate the plurality of controllable sources to obtain an actual cost; An iteration module is configured to take the segment migration local optimal solution as the current planning data, repeatedly execute the above steps until an iteration termination condition is reached, and output the current planning data; The local search module is specifically configured to: in the shot point distribution connected graph of the work area to be analyzed, perform local search on the current planning data by using a double-sided exchange local search method to obtain a local search optimal solution; in the shot point distribution connected graph, randomly select two different shot points, use a simulation firing model based on the TD rule to simulate the plurality of controllable sources to obtain a cost of the current planning data as a current actual cost; reverse an intermediate path between the two shot points to obtain a neighbor solution; the intermediate path is a segment of the planning path of the current planning data; use the simulation firing model based on the TD rule to simulate the plurality of controllable sources to obtain a cost of new planning data composed of the neighbor solution as a new actual cost; when the new actual cost is less than the current actual cost, update the intermediate path between the two shot points to the neighbor solution; repeatedly execute the above steps until a local optimal solution is obtained; The segment migration local search module is specifically configured to: in the planning path of each controllable seismic source in the local search optimal solution, randomly select two different shot points, simulate the multiple controllable seismic sources by using the simulation excitation model based on the TD rule to obtain a cost of the local search optimal solution as a current actual cost; disconnect an intermediate path including the two shot points, and migrate one of the two planning paths obtained after the disconnection to the planning path of another controllable seismic source to obtain new planning data; the intermediate path is a segment of the planning path of the current planning data; simulate the multiple controllable seismic sources by using the simulation excitation model based on the TD rule to obtain a cost of the new planning data as a 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 a segment migration local optimal solution is obtained.

5. The apparatus of claim 4, wherein, The actual cost is represented by the following formula: wherein, is the actual cost, is the scanning time of the i-th vibrator, is the waiting time of the i-th vibrator to avoid harmonic interference, is the moving time of the i-th vibrator from the current shot point to the next shot point after the i-th vibrator stops working. The point-moving time of each seismic source vehicle is represented by the following formula: wherein, is the travel path of the controllable source, n is the total number of shot points in the travel path of the controllable source; is the interval between the i-th shot point and the i+1-th shot point on the travel path of the controllable source, is the set of full permutations of shot points that the controllable source needs to pass through, is the penalty term coefficient, is the angle formed by the i-1-th, i-th and i+1-th shot points in the travel path of the controllable source.

6. The apparatus of claim 4, wherein, The simulation of the multiple controllable seismic sources by using the simulation excitation model based on the TD rule comprises: putting all the seismic source states into a dynamic circulation pool, which classifies and updates the states of the seismic sources in real time; calculating the distances between different controllable seismic sources every preset period according to the current planning data; according to the pre-defined TD rule, exciting the controllable seismic sources in the ready state in a certain priority order, and modifying the state of the controllable seismic source to be excited to working; for the controllable seismic source in the ready state, when the controllable seismic source and the controllable seismic source in the working state satisfy the pre-defined TD rule, the controllable seismic source enters the priority order and is updated to the ready state; when all the controllable seismic sources complete the shot points of the line beam, the actual cost is obtained.

7. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the method of any one of claims 1 to 3 when executing the computer program.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the method of any one of claims 1 to 3.

9. A computer program product, characterised in that, The computer program product comprises a computer program, and the computer program is executed by the processor to implement the method of any one of claims 1 to 3.

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