CN111474579B - Automatic view changing method based on uniform coverage times - Google Patents
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Abstract
The invention discloses an automatic observing method based on uniform covering times, which mainly solves the problem that the prior art does not support the balanced automatic observing of the covering times. The method comprises the following steps: (S1) the system first calculates the number of original coverage before viewing; (S2) initially observing the obstacle point by using an automatic obstacle avoidance algorithm based on the shortest moving distance; (S3) performing an optimization calculation with the goal of the coverage uniformity using a simulated annealing method on the basis of the step (S2), so that the final microstructure satisfies the requirement of the coverage uniformity. Through the scheme, the invention achieves the purpose of one-key automatic viewing in the program, and has very high practical value and popularization value.
Description
Technical Field
The invention belongs to the technical field of seismic acquisition and observation, and particularly relates to an automatic observing changing method based on uniform coverage times.
Background
In the design process of the seismic acquisition observation system, the uniformity of the coverage times is an important basis for evaluating the quality of the observation system, the coverage times of the theoretical observation system in a full coverage area are uniform, and in the actual seismic exploration construction in the field, a barrier area where shot points and demodulator probes cannot be arranged often exists. Due to the fact that shot points and wave detection points in seismic exploration cannot be regularly arranged according to a designed observation system in the obstacle regions, seismic data acquisition cannot reach the designed covering times, the signal-to-noise ratio of a seismic stacking section is reduced, shallow layers in seismic data obtained through final processing are lost, and overall recognition of a structural block and resource evaluation of depression are influenced. Therefore, obstacle avoidance processing is required, the position of the shot point is adjusted to make up for the deficiency of data in the obstacle area and the deficiency of the coverage times, and the adjustment of the position of the shot point directly influences the uniformity of the overall coverage times of the observation system.
The traditional variable-view design is generally operated manually, mainly considering the covering times and the ground surface obstacle condition, and achieving the purpose of meeting the covering times by arranging a method of forcibly crossing the obstacle, enlarging the offset distance at two ends of the obstacle and blasting or adopting restitutive blasting. However, with the development of seismic exploration technology and the continuous expansion of production scale, and the continuous improvement of exploration precision requirements, the defects of manual variable-view design become more and more prominent, and the variable-view requirements of large-scale complex obstacle areas cannot be met. In recent years, a plurality of scholars study observation system changed design methods, chaulmoogra such as Chao, and the like [2] An observation system based on a 3S technology (GPS positioning, satellite remote sensing and geographic information system) is designed, and the observation system can be designed by different methods aiming at different observation areas, but the method has higher requirements on equipment, is not an automatic observing system in the true sense and needs manual intervention; the goddess of heavenly stems and earthly branches [3] Shallow earthquake obstacle-crossing and view-changing design software is developed, and obstacle-crossing and view-changing can be rapidly carried out on an acquisition site by utilizing the software without an automatic view-changing function; in addition, some researchers have proposed an automatic observing design method, but most of them aim at the shortest moving path to change the observation, and no consideration is given to whether the covering times are balanced after the observation.
The relevant references mentioned in the above are specifically as follows:
[1] the calculation method of the longitudinal and transverse coverage times in the King Jing, Dongjunpeng, three-dimensional observation system [ J ] West prospecting engineering, 2012,024(011) 125-.
[2] Chaulmoogra such as chaulmoogra, yinglu, Shiyiqing, et al. complex obstacle area three-dimensional earthquake observation system changed design method and application [ J ]. complex oil and gas reservoir, 2010,03(4):31-34.
[3] Development and application of the design software for changing shallow earthquake obstacle to the design of Juanjuan (Juanjuan) and shallow earthquake obstacle [ J ] earthquake engineering report 2016(3) -.
Disclosure of Invention
The invention aims to provide an automatic observing method based on uniform covering times, which mainly solves the problem that the prior art does not support the balanced automatic observing of the covering times.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
an automatic observing changing method based on uniform covering times comprises the following steps:
(S1) the system first calculates the number of original coverage before viewing;
(S2) initially observing the obstacle point using an automatic obstacle avoidance algorithm based on the shortest moving distance;
(S3) performing an optimization calculation with the goal of the coverage uniformity using a simulated annealing method on the basis of the step (S2), so that the final microstructure satisfies the requirement of the coverage uniformity.
Further, the specific step of using the automatic obstacle avoidance algorithm based on the shortest moving distance in the step (S2) is as follows:
(S21) finding and traversing each obstacle point, finding a target grid point for each obstacle point;
(S22) marking the target grid points as available grid points while calculating a distance of each obstacle point from its corresponding target grid point;
(S23) sorting the obstacle points in descending order according to the distance;
(S24) judging whether the target grid point corresponding to the current obstacle point is available, if not, searching the target grid point of the current obstacle point again; if so, moving the obstacle point to the target grid point, and marking the target grid point as unavailable;
(S25) the step (S24) is performed for all obstacle points in sequence until all obstacle points are processed, and the algorithm execution ends.
Further, the target grid point in the step (S21) is a grid point that is closest to each obstacle point under the allowed condition, that is, the grid point is not occupied by other shots and is not in the obstacle area.
Further, in the step (S24), the target grid point is not available when occupied by other obstacle avoidance points.
Further, the specific steps of performing the optimization calculation with the uniform coverage times as the target in the step (S3) are as follows:
(S31) acquiring the original covering times from the step (S25);
(S32) setting an initial annealing temperature T and a maximum cycle number, and entering an iterative cycle while selecting a shot point that can be exchanged;
(S33) when finding the exchangeable shot, first randomly selecting an obstacle a, and then obtaining a list NGS of available neighboring grid points of the obstacle a;
(S34) entering list circulation, judging whether the maximum circulation times is reached, if yes, returning to the step (S33), and if not, randomly selecting a grid G in the list;
(S35) judging whether the obstacle point a is exchanged with the grid G, if not, marking the grid G as unavailable and returning to the step (S34), if so, calculating the fitness function value f (S34) 0 ) And moving the obstacle point a to the position of the grid G;
(S36) acquiring a shot point b closest to the grid G, and assigning the shot-detection relation of the shot point b to the obstacle point A;
(S37) adopting an incremental method to carry out rapid recalculation of the covering times and calculating a fitness function value f (S) 1 );
(S38) calculating the increment Δ T ═ f (S) 1 )-f(S 0 ) Judging whether the covering times become uniform, if so, accepting the exchange of the barrier point a and the shot point b, and if not, according to the probability e -ΔT/T Receiving the exchange of the obstacle point a and the shot point b; then, cooling the temperature T;
(S39) judging whether the maximum circulation times is reached, if not, returning to the step (S33), if so, reaching the circulation end condition, and ending the algorithm execution.
Specifically, the formula for performing the fast recounting of the number of times of coverage by the incremental method in the step (S37) is as follows: the current covering times are the last covering times, the covering times influenced by the obstacle point a and the covering times influenced by the shot point b.
Wherein, the original covering times before the observation is calculated in the step (S1) uses the document [1]The method of (1). In the step (S38), the number of times of coverage becomes more uniform when the increment Δ T < 0, where the fitness function is defined as (current number of times of coverage-original number of times of coverage) } (S) } 2 (ii) a Using a random seed to generate floating point numbers between 0 and 1 if the probability value e -ΔT/T >Floating point number, then receiving the exchange between barrier point a and shot point b; the temperature T is reduced using the formula T ═ λ T, where λ is 0.9.
Compared with the prior art, the invention has the following beneficial effects:
(1) compared with the traditional method, the manual observing change method has high automation degree, avoids the complex steps of manually designing the observing change scheme and carrying out interactive operation in the traditional method, and carries out one-key automatic observing change in the program; the optimal solution which can lead the uniformity of the covering times is searched by using a simulated annealing algorithm, and the changing effect is good; the automatic change of the large-scale work area can be processed, and the efficiency is high.
Drawings
FIG. 1 is a flow chart of the system of the present invention.
Fig. 2 is a flowchart of the automatic obstacle avoidance algorithm based on the shortest moving distance in the present invention.
Fig. 3 is a flowchart of an automatic obstacle avoidance algorithm based on uniform coverage times.
Fig. 4 is a schematic diagram of the arrangement relationship of a shot point in a work area (AB is an obstacle area) according to the present invention.
FIG. 5 is a schematic diagram of the arrangement relationship of shots near the obstacle area after the automatic changing of the invention by using the shortest moving distance algorithm.
Fig. 6 is a schematic diagram of arrangement relationship of shot points near an obstacle area after the automatic obstacle avoidance algorithm based on uniform coverage times is used in the invention.
FIG. 7 is a diagram of an original coverage count of a work area according to the present invention.
FIG. 8 is a schematic diagram of the coverage times of a work area after being automatically changed by using a shortest moving distance algorithm.
Fig. 9 is a schematic diagram of the number of coverage of a work area after an automatic obstacle avoidance algorithm based on uniform coverage is used.
Detailed Description
The present invention is further illustrated by the following examples in conjunction with the figures and examples, and embodiments of the present invention include, but are not limited to, the following examples.
Examples
As shown in fig. 1, an automatic viewing method based on uniform coverage times includes the following steps:
(S1) the system first calculates the number of original coverage before viewing;
(S2) initially observing the obstacle point by using an automatic obstacle avoidance algorithm based on the shortest moving distance;
(S3) performing optimization calculation with the coverage uniformity as a target on the basis of the step (S2), so that the final viewing structure satisfies the requirement of coverage uniformity.
In step (S2), all obstacle points are first found based on the automatic obstacle avoidance algorithm with the shortest moving distance, and then the nearest grid point (denoted as a target grid point) is found for each obstacle point under an allowance condition, where the allowance condition refers to the maximum number of grids that the obstacle point specified by the user moves in the inline direction and the crossline direction, and the target grid point must be an available grid point (a grid point that is not occupied by other shot points and is not in an obstacle area). And then sorting the obstacle avoidance points in a descending manner according to the distance between each obstacle point and the target grid point. And finally, moving each obstacle avoidance point to a target grid point according to the sequence, recording the target grid point as unavailable, searching the target grid point with the nearest distance to the current obstacle avoidance point again if the target grid point corresponding to the current obstacle avoidance point is unavailable (occupied by other obstacle avoidance points), moving the target grid point to the target grid point and recording the target grid point as unavailable. After all the obstacle points are processed in sequence, the algorithm execution is finished, and the specific flow is shown in fig. 2.
Optimization of the coverage number balance is performed on the basis of the step (S2). The algorithm firstly obtains the original covering times, then sets the initial simulated annealing temperature T (the initial value of T is set as 1000), sets the maximum cycle time of 200, enters the cycle, iteratively searches exchangeable shot points, and selects the optimal scheme. When searching for exchangeable shots, firstly randomly selecting an obstacle point a, then obtaining a list NGS of available nearby grid points of the obstacle point a, and selecting an exchangeable grid G in the nearby grid list according to exchangeable conditions, wherein the exchangeable conditions mean that no other shots are placed in the grid G. And after the exchange between the obstacle point a and the grid G is finished, searching a shot point B closest to the grid G, and assigning the shot-detection relation of the shot point B to the obstacle point a. Then, an incremental method is adopted to carry out rapid recalculation on the covering times, namely the current covering times are the covering times of the last time, the covering times influenced by the obstacle point a and the covering times influenced by the shot point b, an incremental value delta T is calculated, if the delta T is less than 0, the covering times are more balanced, and the exchange result is received; otherwise, calculating probability value e -ΔT/T The random seed is used to generate a floating point number between 0 and 1, and if the probability value is greater than the floating point number, the swap is accepted. And finally, cooling the temperature T, and entering the next circulation. When the loop termination condition is reached, that is, the number of loops reaches 200, the algorithm execution is ended, and the specific flow is shown in fig. 3.
Fig. 4 is a schematic diagram showing an arrangement relationship of shot points near an obstacle area before a first work area is changed, rectangles distributed at equal intervals in the longitudinal direction in the diagram represent preset shot points, areas marked as a and B are the obstacle area, the preset shot points are distributed in the obstacle area, and the original coverage times of the first work area are shown in fig. 7. After the obstacle avoidance is automatically performed by using the moving distance-based shortest algorithm, all shot points in the original obstacle area are completely moved out of the obstacle area, the moved shot points are arranged along the vicinity of the obstacle area, the arrangement of the shot points in the vicinity of the obstacle area is shown in fig. 5, and the coverage times of the work area are shown in fig. 8. After the optimization is performed by using the algorithm with uniform coverage times, the arrangement relationship of the shot points near the obstacle area changes again, as shown in fig. 6, and the corresponding coverage times are as shown in fig. 9, which shows that the coverage times of the first work area become more uniform and closer to the original coverage times of the first work area before observation by using the optimization algorithm based on uniform coverage times.
The above embodiments are only preferred embodiments of the present invention, and are not intended to limit the scope of the present invention, but all changes that can be made by applying the principles of the present invention and performing non-inventive work on the basis of the principles shall fall within the scope of the present invention.
Claims (4)
1. An automatic observing method based on uniform covering times is characterized by comprising the following steps:
(S1) the system first calculates the number of original coverage before viewing;
(S2) initially observing the obstacle point using an automatic obstacle avoidance algorithm based on the shortest moving distance; the method comprises the following specific steps:
(S21) finding and traversing each obstacle point, finding a target grid point for each obstacle point;
(S22) marking the target grid points as available grid points while calculating a distance of each obstacle point from its corresponding target grid point;
(S23) sorting the obstacle points in descending order according to the distance;
(S24) judging whether the target grid point corresponding to the current obstacle point is available, if not, searching the target grid point of the current obstacle point again; if the target grid point is available, the obstacle point moves to the target grid point, and meanwhile the target grid point is marked as unavailable;
(S25) sequentially performing the step (S24) for all obstacle points until all obstacle points are processed, and ending the algorithm execution;
(S3) performing an optimization calculation with the goal of the coverage times being uniform using a simulated annealing method on the basis of the step (S2), so that the final microstructure satisfies the requirement of the coverage times being uniform; the method comprises the following specific steps:
(S31) acquiring the original covering times from the step (S25);
(S32) setting an initial annealing temperature T and a maximum cycle number, and entering an iterative cycle while selecting a shot point that can be exchanged;
(S33) when finding the exchangeable shot, first randomly selecting an obstacle a, and then obtaining a list NGS of available neighboring grid points of the obstacle a;
(S34) entering list circulation, and simultaneously judging whether the maximum circulation times is reached, if so, returning to the step (S33), and if not, randomly selecting a grid G in the list;
(S35) determining whether the obstacle point a is exchanged with the grid G, if not, marking the grid G as unavailable and returning to the step (S34), and if so, calculating a first fitness function value f (S34) 0 ) And moving the obstacle point a to the position of the grid G;
(S36) acquiring a shot point b closest to the grid G, and assigning the shot-detection relation of the shot point b to the obstacle point A;
(S37) adopting an incremental method to carry out rapid recalculation of the covering times and calculating a second fitness function value f (S) 1 );
(S38) calculating the increment Δ T ═ f (S) 1 )-f(S 0 ) Judging whether the covering times become uniform, if so, accepting the exchange between the barrier point a and the shot point b, and if not, according to the probability e -ΔT/T Receiving the exchange of the obstacle point a and the shot point b; then, cooling the temperature T;
(S39) judging whether the maximum circulation times is reached, if not, returning to the step (S33), if so, reaching the circulation end condition, and ending the algorithm execution.
2. The method of claim 1, wherein the target grid point in the step (S21) is a closest grid point to each obstacle point under a condition that the closest grid point is allowed, that is, the grid point is not occupied by other shots and is not in an obstacle area.
3. The method of claim 2, wherein the step (S24) is performed when the target grid point is occupied by other obstacle avoidance points.
4. The method of claim 3, wherein the step (S37) of fast recounting the covering times by using an incremental method is characterized in that: the current covering times are the last covering times, the covering times influenced by the obstacle point a and the covering times influenced by the shot point b.
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