A method, device, equipment and readable medium for converging a seismic source travel path

Abstract

The application discloses a method for converging a seismic source travel path, comprising the following steps: reading an original path scheme containing multiple groups of seismic source travel paths, and generating multiple derivative path schemes based on the original path scheme through a random disturbance generation method, and taking all the derivative path schemes as a current parent population; generating a child population based on the current parent population through a roulette and a simulated annealing method, disturbing each scheme in the child population, and calculating a minimum evaluation value of the current child population and a corresponding scheme; and taking the current child population as a new current parent population and repeating the previous step to obtain multiple schemes meeting preset conditions, so as to obtain a converging path scheme of multiple groups of controllable seismic source travel paths. The application also discloses corresponding devices, computer equipment and readable storage media. The application realizes fast convergence of the whole algorithm without reducing optimal solutions of the algorithm, and provides a feasible implementation method for fast calculation of multiple groups of seismic source travel path schemes.

Description

Technical Field

[0001] This invention relates to the field of geophysical exploration data processing technology, and in particular to a method, apparatus, equipment, and readable medium for converging the trajectory of an earthquake source. Background Technology

[0002] In the field of petroleum seismic exploration, to improve the efficiency of field production and construction, it is necessary to use multiple sets of seismic sources to enhance excitation efficiency, ultimately shortening the total construction time. However, in practice, the locations of surface excitation points are relatively dispersed, and surface conditions and road connectivity vary greatly, making it difficult to obtain the optimal solution for theoretically planning the source travel path. One fundamental reason is the large number of field construction points, which leads to excessive computational complexity using conventional heuristic algorithms. This high computational complexity results in slow convergence speed and poor performance.

[0003] Currently, earthquake source path estimation algorithms are mainly divided into heuristic algorithms and conventional algorithms. Heuristic algorithms have significant advantages in balancing global optimal solution acquisition and computational complexity, and are therefore more widely used. One of the more commonly used algorithms is simulated annealing. However, this method suffers from problems such as slow convergence and low parallelism. Summary of the Invention

[0004] In view of this, the purpose of this invention is to propose a convergence method, apparatus, device, and readable medium for source path calculation. Population computation and roulette wheel algorithm are introduced during the convergence process, and random perturbation is added when determining the inverse convergence direction, thus sparsening the solution space for inverse convergence. Without reducing the optimal solution of the algorithm, the entire algorithm achieves rapid convergence, providing a practical and feasible implementation method for quickly obtaining multiple source path schemes.

[0005] To achieve the above objectives, one aspect of this invention provides a method for converging earthquake source paths, comprising the following steps: reading an original path scheme containing multiple sets of earthquake source paths, and generating multiple derived path schemes based on the original path schemes using a random perturbation generation method, and using all the derived path schemes as the current parent population; generating a child population based on the current parent population using roulette wheel and simulated annealing methods, perturbing each scheme in the child population, and obtaining the minimum evaluation value of the current child population and its corresponding scheme; and using the current child population as the new current parent population and repeating the previous step to obtain multiple schemes that meet preset conditions, thereby obtaining multiple converged path schemes for controllable earthquake source paths.

[0006] In some implementations, the original path scheme includes at least the number of source groups and path node sequence values, wherein the path node sequence values ​​are integers and do not overlap.

[0007] In some implementations, generating multiple derived path schemes based on the original path scheme using a random perturbation generation method includes: copying the original path scheme D0 to Di; setting the current position p to 2; randomly generating a random number q between 2 and N-1; if the current position p is not equal to the random number q, then swapping the node sequence value Vp of position p and the node sequence value Vq of position q, and determining whether p is less than N-1; if p is less than N-1, then incrementing p by 1 and repeating the previous step; if p is not less than N-1, then generating a derived path scheme is complete, and the evaluation value of the current scheme is calculated.

[0008] In some implementations, generating a child population based on the current parent population using roulette wheel and simulated annealing methods includes: cooling the current parent population by multiplying the current temperature by a preset constant, wherein the preset constant is greater than 0 and less than 1.

[0009] In some implementations, generating a child population based on the current parent population using roulette wheel and simulated annealing methods includes: randomly selecting several schemes from the parent population, calculating their distribution probabilities based on the evaluation values ​​of the several schemes, randomly generating a probability value, selecting a corresponding scheme based on the probability value and the distribution probability, and replicating it to generate a child scheme; determining whether the number of generated child schemes reaches a preset number; if the number of generated child schemes does not reach the preset number, repeating the above steps; if the number of generated child schemes reaches the preset number, using the generated child schemes as the child population.

[0010] In some implementations, calculating the probability distribution based on the evaluation values ​​of the plurality of schemes includes: taking the reciprocal of the logarithm of the evaluation values ​​of the plurality of schemes and summing them to obtain an intermediate value; dividing the reciprocal of the logarithm of the evaluation values ​​of the plurality of schemes by the intermediate value to obtain the probability distribution corresponding to the plurality of schemes.

[0011] In some implementations, perturbing each scheme in the subpopulation includes: setting the current position p to 2, calculating the current acceptable inverse evaluation value; randomly generating a random number q between 2 and N; if the current position p is not equal to the random number q, calculating and comparing the evaluation value before and after the change; if the evaluation value before the change is not less than the evaluation value after the change, subtracting the evaluation value before the change from the evaluation value after the change to obtain the evaluation difference, and determining whether to accept the change based on the evaluation difference, the random probability value, and the current acceptable inverse evaluation value; if the change is accepted, deleting the value corresponding to position p from the queue and inserting it into position q; determining whether p is less than N-1; if p is less than N-1, incrementing p by 1, returning to the process of randomly generating a random number q between 2 and N and repeating the above steps; if p is not less than N-1, calculating the evaluation value of the current scheme and completing the perturbation of the current scheme.

[0012] In some implementations, the method further includes: if the current position p is equal to the random number q, then further determine whether p is less than N-1; if p is less than N-1, then add 1 to p, return to the process of randomly generating a random number q between 2 and N and repeat the above steps; if p is not less than N-1, then calculate the evaluation value of the current scheme and complete the perturbation of the current scheme.

[0013] In some implementations, the method further includes: if the pre-change evaluation value is less than the post-change evaluation value, then delete the value corresponding to position p from the queue and insert it into position q; determine whether p is less than N-1, if p is less than N-1, then increment p by 1, return to the method of randomly generating a random number q between 2 and N and repeat the above steps; if p is not less than N-1, then calculate the evaluation value of the current scheme and complete the perturbation of the current scheme.

[0014] In some implementations, the method further includes: if the change is not accepted, then further determine whether p is less than N-1; if p is less than N-1, then add 1 to p, return to the above steps of randomly generating a random number q between 2 and N; if p is not less than N-1, then calculate the evaluation value of the current scheme and complete the perturbation of the current scheme.

[0015] In some implementations, calculating and comparing the pre-change and post-change evaluation values ​​includes: calculating the evaluation values ​​of the three line segments before the change and summing them to obtain the pre-change evaluation value; calculating the evaluation values ​​of the three line segments after the change and summing them to obtain the post-change evaluation value; wherein the three line segments before the change are from position p-1 to position p, from position p to position p+1, and from position q-1 to position q, and the three line segments after the change are from position p-1 to position p+1, from position q-1 to position p, and from position p to position q.

[0016] In some implementations, determining whether to accept a change based on the evaluation difference, the random probability value, and the current acceptable inverse evaluation value includes: randomly generating a random probability value greater than 0 and less than 1, and comparing the evaluation value with the current acceptable inverse evaluation value; if the evaluation value is greater than the current acceptable inverse evaluation value, then the change is not accepted; if the evaluation value is not greater than the current acceptable inverse evaluation value, but is greater than 1 / 4 of the current acceptable inverse evaluation value, then determining whether to accept a change based on the random probability value and the current acceptable inverse evaluation value; if the evaluation value is not greater than 1 / 4 of the current acceptable inverse evaluation value, then the change is accepted.

[0017] In some implementations, determining whether to accept a change based on the random probability value and the current acceptable inverse evaluation value includes: if the evaluation value is not greater than the current acceptable inverse evaluation value, but is greater than 1 / 2 of the current acceptable inverse evaluation value, then further determining whether the random probability value is less than the function value of the current acceptable inverse evaluation value, wherein the function value is obtained by adding 1 to the current acceptable inverse evaluation value, taking the logarithm, subtracting 1 from the logarithm, and then dividing by 2; if the random probability value is less than the function value of the current acceptable inverse evaluation value, then the change is accepted; if the random probability value is not less than the function value of the current acceptable inverse evaluation value, then the change is not accepted; if the evaluation value is not greater than 1 / 2 of the current acceptable inverse evaluation value, but is greater than 1 / 4 of the current acceptable inverse evaluation value, then further determining whether the random probability value is less than the current acceptable inverse evaluation value; if the random probability value is less than the current acceptable inverse evaluation value, then the change is accepted; if the random probability value is not less than the current acceptable inverse evaluation value, then the change is not accepted.

[0018] In some implementations, the current subpopulation is used as the new current parent population, and the previous step is repeated to obtain multiple schemes that meet preset conditions, thereby obtaining convergence path schemes for multiple sets of controllable seismic source travel paths. This includes: obtaining the minimum evaluation value of the current subpopulation and its corresponding scheme, and repeating the previous step; in response to the same scheme appearing more than a preset number of times, stopping the repetition of the previous step and outputting the scheme; in response to the current temperature being less than a preset temperature, stopping the repetition of the previous step and outputting the scheme; and using the output scheme as the convergence path scheme for multiple sets of controllable seismic source travel paths.

[0019] In another aspect, this invention provides a convergence device for seismic source travel paths, comprising: an initialization module configured to read an original path scheme containing multiple sets of seismic source travel paths, and generate multiple derived path schemes based on the original path schemes using a random perturbation generation method, and use all the derived path schemes as the current parent population; a convergence module configured to generate a subpopulation based on the current parent population using roulette wheel and simulated annealing methods, perturb each scheme in the subpopulation, and obtain the minimum evaluation value of the current subpopulation and its corresponding scheme; and an output module configured to use the current subpopulation as the new current parent population and repeat the steps in the convergence module to obtain multiple schemes that meet preset conditions, thereby obtaining multiple sets of converged path schemes for controllable seismic source travel paths.

[0020] In another aspect of the present invention, a computer device is provided, comprising: at least one processor; and a memory storing computer instructions executable on the processor, the instructions, when executed by the processor, implementing the steps of the above-described method.

[0021] In another aspect, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method steps.

[0022] The present invention has at least the following beneficial technical effects: In the process of obtaining multiple sets of source travel paths, the simulated annealing algorithm is parallelized, and a modified roulette wheel selection algorithm is used to select the best individuals in the population, which effectively narrows the range of candidate schemes. When the random walk algorithm obtains the scheme, it treats the inverse convergence acceptance method differently. Under the condition of ensuring the minimum total path value, it is better adapted to the special characteristics of the source travel path in seismic exploration, which is conducive to the simulated annealing algorithm to converge globally more quickly, and provides an effective guarantee for obtaining the ideal theoretical planning and design path scheme more accurately. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of an embodiment of the convergence method for the earthquake source travel path provided by the present invention;

[0025] Figure 2 This is an initial schematic diagram generated using actual data;

[0026] Figure 3 This is a schematic diagram illustrating the monitoring of calculation results obtained using the convergence method provided by this invention.

[0027] Figure 4 The final result diagram of the scheme obtained by using the convergence method provided by this invention is shown below;

[0028] Figure 5 A schematic diagram of an embodiment of the convergence device for the earthquake source travel path provided by the present invention;

[0029] Figure 6 A schematic diagram of an embodiment of the computer device provided by the present invention;

[0030] Figure 7 A schematic diagram illustrating an embodiment of the computer-readable storage medium provided by the present invention. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to specific examples and the accompanying drawings.

[0032] It should be noted that all uses of "first" and "second" in the embodiments of the present invention are for the purpose of distinguishing two entities or parameters with the same name but different names. It is clear that "first" and "second" are only for the convenience of expression and should not be construed as limiting the embodiments of the present invention. Subsequent embodiments will not explain this in detail.

[0033] Based on the above objectives, a first aspect of the present invention provides an embodiment of a method for converging the trajectory of an earthquake source. Figure 1 This diagram illustrates an embodiment of the convergence method for the earthquake source travel path provided by the present invention. Figure 1 As shown, the convergence method for the source travel path in this embodiment of the invention includes the following steps:

[0034] 001. Read the original path scheme containing multiple sets of earthquake source travel paths, and generate multiple derived path schemes based on the original path scheme using the random perturbation generation method, and use all derived path schemes as the current parent population.

[0035] 002. Based on the current parent population, generate a child population using roulette wheel and simulated annealing methods. Perturb each scheme in the child population and find the minimum evaluation value of the current child population and its corresponding scheme.

[0036] 003. Take the current subpopulation as the new current parent population and repeat the previous step to obtain multiple schemes that meet the preset conditions, thereby obtaining multiple sets of convergence path schemes for the controllable source travel paths.

[0037] In this embodiment, Figure 2 The actual seismic source point sequence and its initial scheme shown are presented. For a given multi-source path scheme P, a new multi-source path scheme P' is obtained through a certain calculation method. By introducing population computing and roulette wheel algorithm, the parallelism of the entire algorithm is improved. Random perturbation is added when determining the inverse convergence direction, which sparsifies the solution space of inverse convergence and relatively improves the convergence speed of the entire algorithm. The final series of scheme evaluation values ​​are shown below. Figure 3 As shown, the calculated path is as follows Figure 4 As shown, the calculation result is close to the global optimal result.

[0038] In some embodiments of the present invention, the original path scheme includes at least the number of source groups and path node sequence values, wherein the path node sequence values ​​are integers and do not overlap.

[0039] In this embodiment, the original path scheme D0 containing multiple sets of earthquake source travel paths is read, which includes at least the number of earthquake source groups T and path node sequence values ​​Vi (i = 1, 2, ..., N). For ease of explanation, the path node sequence values ​​Vi are represented by integers, and it is required that the sequence values ​​in the queue do not overlap.

[0040] In some embodiments of the present invention, generating multiple derived path schemes based on the original path scheme using a random perturbation generation method includes: copying from the original path scheme D0 to Di; setting the current position p to 2; randomly generating a random number q between 2 and N-1; if the current position p is not equal to the random number q, then swapping the node sequence value Vp of position p and the node sequence value Vq of position q, and determining whether p is less than N-1; if p is less than N-1, then incrementing p by 1 and repeating the previous step; if p is not less than N-1, then generating a derived path scheme is complete, and the evaluation value of the current scheme is calculated.

[0041] In this embodiment, based on the given population size M, M-1 derived path schemes Di (i = 1, 2, ..., M-1) are generated from the original scheme D0. For any derived path scheme Di, the generation method adopts a random perturbation generation method, and the specific method is as follows:

[0042] a) Copy the original path scheme D0 to Di as is;

[0043] b) Set the current position p to 2;

[0044] c) Randomly generate a number q between 2 and N-1;

[0045] d) If p is not equal to q, swap the node sequence value Vp at position p with the node sequence value Vq at position q;

[0046] e) Increment p by 1. If p is less than N, go to c; otherwise, go to f.

[0047] f) Calculate the evaluation value f of this scheme using a certain method, and the generation is complete.

[0048] In some embodiments of the present invention, generating a child population based on the current parent population through roulette wheel and simulated annealing methods includes: cooling the current parent population by multiplying the current temperature by a preset constant, wherein the preset constant is greater than 0 and less than 1.

[0049] In this embodiment, a cooling process is performed by multiplying the current temperature by a constant c between (0,1), typically set to 0.999.

[0050] In some embodiments of the present invention, generating a child population based on the current parent population using roulette wheel and simulated annealing methods includes: randomly selecting several schemes from the parent population, calculating their distribution probabilities based on the evaluation values ​​of the several schemes, randomly generating a probability value, selecting the corresponding scheme based on the probability value and the distribution probability, and replicating it to generate a child scheme; determining whether the number of generated child schemes reaches a preset number; if the number of generated child schemes does not reach the preset number, repeating the above steps; if the number of generated child schemes reaches the preset number, using the generated child schemes as the child population.

[0051] In this embodiment, for the current parent population F, an improved roulette wheel betting and improved simulated annealing method is used to generate a child population C. The specific method is as follows:

[0052] a) Randomly select 3 schemes x1, x2, x3 from the parent population;

[0053] b) Calculate the reciprocal of the logarithm of the evaluation value of each option ti (i = 0, 1, 2), and sum the values ​​of ti to obtain the value S. Divide the reciprocal of the logarithm of the evaluation value of each option ti by S to obtain the probability distribution pi of the three options.

[0054]

[0055] c) Randomly generate a probability value of (0,1), and use this value as a basis to obtain the corresponding scheme x from the three schemes, and copy it to generate the sub-scheme Cxi;

[0056] d) If the number of schemes in the current subpopulation reaches M, exit; otherwise, go to step a to continue.

[0057] In some embodiments of the present invention, calculating the probability distribution based on the evaluation values ​​of several schemes includes: taking the reciprocal of the logarithm of the evaluation values ​​of several schemes and summing them to obtain an intermediate value; dividing the reciprocal of the logarithm of the evaluation values ​​of several schemes by the intermediate value to obtain the probability distribution corresponding to the several schemes.

[0058] In some embodiments of the present invention, perturbing each scheme in the subpopulation includes: setting the current position p to 2, calculating the current acceptable inverse evaluation value; randomly generating a random number q between 2 and N; if the current position p is not equal to the random number q, calculating the evaluation value before the change and the evaluation value after the change and comparing them; if the evaluation value before the change is not less than the evaluation value after the change, subtracting the evaluation value before the change from the evaluation value after the change to obtain the evaluation difference, and determining whether to accept the change based on the evaluation difference, the random probability value, and the current acceptable inverse evaluation value; if the change is accepted, deleting the value corresponding to position p from the queue and inserting it into position q; determining whether p is less than N-1; if p is less than N-1, incrementing p by 1, returning to randomly generating a random number q between 2 and N and repeating the above steps; if p is not less than N-1, calculating the evaluation value of the current scheme and completing the perturbation of the current scheme.

[0059] In this embodiment, each scheme Ci in the subpopulation is perturbed, and the specific method is as follows:

[0060] a) Set the current position p to 2 and calculate the current acceptable inverse evaluation value Pt;

[0061] b) Randomly generate a number q between 2 and N;

[0062] c) If p is equal to q, go to step h; otherwise continue;

[0063] d) Calculate the evaluation values disi of the current three line segments, which are positions p - 1, p; p, p + 1; and q - 1, q respectively, and sum them up to obtain the evaluation value Sf before the change;

[0064] e) Calculate the evaluation values disi of the three line segments after the change, which are positions p - 1, p + 1; and q - 1, p; p, q respectively, and sum them up to obtain the evaluation value Sh after the change;

[0065] f) If sh < sf, delete the value at the current position p from the queue, insert it at the original position q, and go to step h;

[0066] g) Obtain the evaluation difference before and after Sm = sh - sf, randomly generate a probability value P in (0, 1), and decide whether to accept the change according to the following formula:

[0067]

[0068] If the change is accepted, delete the value at the current position p from the queue and insert it at the original position q;

[0069] h) Increment p by 1. If p is less than N, go to b; otherwise go to f;

[0070] f) Calculate the evaluation value f of this solution in a certain way, and the generation is completed.

[0071] In some embodiments of the present invention, the method further includes: if the current position p is equal to the random number q, further determine whether p is less than N - 1. If p is less than N - 1, increment p by 1, return to randomly generate a random number q from 2 to N, and repeat the above steps; if p is not less than N - 1, calculate the evaluation value of the current solution and complete the perturbation of the current solution.

[0072] In some embodiments of the present invention, the method further includes: if the evaluation value before the change is less than the evaluation value after the change, delete the value corresponding to the position p from the queue and insert it at the position q; determine whether p is less than N - 1. If p is less than N - 1, increment p by 1, return to randomly generate a random number q from 2 to N, and repeat the above steps; if p is not less than N - 1, calculate the evaluation value of the current solution and complete the perturbation of the current solution.

[0073] In some embodiments of the present invention, the method further includes: if the change is not accepted, further determine whether p is less than N - 1. If p is less than N - 1, increment p by 1, return to randomly generate a random number q from 2 to N, and repeat the above steps; if p is not less than N - 1, calculate the evaluation value of the current solution and complete the perturbation of the current solution.

[0074] In some embodiments of the present invention, calculating and comparing the pre-change evaluation value and the post-change evaluation value includes: calculating the evaluation values ​​of the three line segments before the change and summing them to obtain the pre-change evaluation value; calculating the evaluation values ​​of the three line segments after the change and summing them to obtain the post-change evaluation value; wherein the three line segments before the change are from position p-1 to position p, from position p to position p+1, and from position q-1 to position q, and the three line segments after the change are from position p-1 to position p+1, from position q-1 to position p, and from position p to position q.

[0075] In some embodiments of the present invention, determining whether to accept a change based on the evaluation difference, a random probability value, and the current acceptable inverse evaluation value includes: randomly generating a random probability value greater than 0 and less than 1, and comparing the evaluation value with the current acceptable inverse evaluation value; if the evaluation value is greater than the current acceptable inverse evaluation value, then the change is not accepted; if the evaluation value is not greater than the current acceptable inverse evaluation value, but is greater than 1 / 4 of the current acceptable inverse evaluation value, then determining whether to accept a change based on the random probability value and the current acceptable inverse evaluation value; if the evaluation value is not greater than 1 / 4 of the current acceptable inverse evaluation value, then the change is accepted.

[0076] In some embodiments of the present invention, determining whether to accept a change based on a random probability value and a current acceptable inverse evaluation value includes: if the evaluation value is not greater than the current acceptable inverse evaluation value and is greater than 1 / 2 of the current acceptable inverse evaluation value, then further determining whether the random probability value is less than a function value of the current acceptable inverse evaluation value, wherein the current acceptable inverse evaluation value is incremented by 1, the logarithm is taken, and the logarithm is decremented by 1 and divided by 2 to obtain the function value; if the random probability value is less than a function value of the current acceptable inverse evaluation value, then the change is accepted; if the random probability value is not less than a function value of the current acceptable inverse evaluation value, then the change is not accepted; if the evaluation value is not greater than 1 / 2 of the current acceptable inverse evaluation value and is greater than 1 / 4 of the current acceptable inverse evaluation value, then further determining whether the random probability value is less than the current acceptable inverse evaluation value; if the random probability value is less than the current acceptable inverse evaluation value, then the change is accepted; if the random probability value is not less than the current acceptable inverse evaluation value, then the change is not accepted.

[0077] In some embodiments of the present invention, taking the current subpopulation as the new current parent population and repeating the previous step to obtain multiple schemes that meet preset conditions, thereby obtaining convergence path schemes for multiple sets of controllable seismic source travel paths, includes: obtaining the minimum evaluation value of the current subpopulation and its corresponding scheme, and repeating the previous step; in response to the same scheme appearing more than a preset number of times, stopping the repetition of the previous step and outputting the scheme; in response to the current temperature being less than a preset temperature, stopping the repetition of the previous step and outputting the scheme; and using the output scheme as the convergence path scheme for multiple sets of controllable seismic source travel paths.

[0078] In this embodiment, the minimum evaluation value of the current subpopulation and the corresponding scheme px are obtained. If px appears more than 100 times during the calculation, the process is terminated; if the temperature FT is less than 1e-6, the process is terminated.

[0079] The specific implementation of the present invention is further described below with reference to specific embodiments. Actual data from a 3D seismic exploration project in northern China is used. Specifically, this includes:

[0080] 1) Set the initial temperature FT and the initial acceptable inverse evaluation value TH. Generally, set FT to around 0.7 and TH to around 5 times the minimum point spacing. Read the original path scheme D0 containing multiple sets of source paths, which includes at least the number of source groups T and path node sequence values ​​Vi (i = 1, 2, ..., N). For ease of explanation, the path node sequence values ​​Vi are represented by integers, and it is required that the sequence values ​​in the queue do not overlap.

[0081] 2) Based on the given population size M, generate M-1 derived path schemes Di (i = 1, 2, ..., M-1) from the original scheme D0. For any derived path scheme Di, the generation method adopts a random perturbation generation method, as follows:

[0082] a) Copy the original path scheme D0 to Di as is;

[0083] b) Set the current position p to 2;

[0084] c) Randomly generate a number q between 2 and N-1;

[0085] d) If p is not equal to q, swap the node sequence value Vp at position p with the node sequence value Vq at position q;

[0086] e) Increment p by 1. If p is less than N, go to c; otherwise, go to f.

[0087] f) Calculate the evaluation value f of this scheme using some method, and the generation is complete. Treat all path schemes Di (i = 0, 1, 2, ..., M-1) as a whole D, and regard them as the current parent population F.

[0088] 3) Perform a cooling process by multiplying the current temperature by a constant c between (0,1), typically set to 0.999.

[0089] f t =f t *c

[0090] 4) For the current parent population F, the improved roulette wheel betting + improved simulated annealing method is used to generate the child population C. The specific method is as follows:

[0091] a) Randomly select 3 solutions x1, x2, x3 from the parent population;

[0092] b) Calculate the reciprocal of the logarithm of the evaluation value of each solution ti (i = 0, 1, 2), and sum ti to obtain the value S. Divide the reciprocal of the logarithm of the evaluation value of each solution ti by S to obtain the probability distribution pi of the three solutions;

[0093]

[0094] c) Randomly generate a probability value in (0, 1), and obtain the corresponding solution x from the three solutions based on this value, and copy to generate the sub-solution Cxi;

[0095] d) If the number of solutions in the current sub-population reaches M, exit; otherwise, go back to step a to continue;

[0096] 5) Perturb each solution Ci in the sub-population. The specific method is as follows:

[0097] a) Set the current position p to 2, and calculate the current acceptable inverse evaluation value Pt;

[0098] P t = TH * f t

[0099] b) Randomly generate a number q from 2 to N;

[0100] c) If p is equal to q, go to step h; otherwise, continue;

[0101] d) Calculate the evaluation values disi of the current three line segments, which are positions p - 1, p; p, p + 1; and q - 1, q respectively, and sum them to obtain the pre-change evaluation value Sf

[0102] e) Calculate the evaluation values disi of the three line segments after the change, which are positions p - 1, p + 1; and q - 1, p; p, q respectively, and sum them to obtain the post-change evaluation value Sh;

[0103] f) If sh < sf, delete the value at the current position p from the queue and insert it at the original position q, and go to step h;

[0104] g) Obtain the evaluation difference before and after Sm = sh - sf, randomly generate a probability value P in (0, 1), and decide whether to accept the change according to the following formula:

[0105]

[0106] If the change is accepted, delete the value at the current position p from the queue and insert it at the original position q;

[0107] h)Increase p by 1; if p is less than N, go to b; otherwise go to f.

[0108] f) Calculate the evaluation value f of this scheme using a certain method, and the generation is complete.

[0109] 6) Calculate the minimum evaluation value of the current subpopulation and the corresponding scheme px. If px appears more than 100 times during the calculation, exit; if the temperature FT is less than 1e-6, exit.

[0110] 7) Set the child population to the parent population, then proceed to step 3).

[0111] Finally, obtaining px represents the desired multiple controllable seismic source paths.

[0112] It should be noted that the steps in each embodiment of the above-mentioned convergence method for the earthquake source path can be intersected, substituted, added, or deleted. Therefore, these reasonable permutations and combinations of the convergence method for the earthquake source path should also fall within the protection scope of this invention, and the protection scope of this invention should not be limited to the embodiments.

[0113] Based on the above objectives, a second aspect of the present invention provides a convergence device for the travel path of an earthquake source. Figure 5 This diagram illustrates an embodiment of the source travel path convergence device provided by the present invention. Figure 5 As shown, the source path convergence device of this invention includes the following modules: an initialization module 011, configured to read an original path scheme containing multiple sets of source paths, and generate multiple derived path schemes based on the original path schemes using a random perturbation generation method, and use all derived path schemes as the current parent population; a convergence module 012, configured to generate a subpopulation based on the current parent population using roulette wheel and simulated annealing methods, perturb each scheme in the subpopulation, and obtain the minimum evaluation value of the current subpopulation and its corresponding scheme; and an output module 013, configured to use the current subpopulation as the new current parent population and repeat the steps in the convergence module 012 to obtain multiple schemes that meet preset conditions, thereby obtaining multiple sets of convergence path schemes for controllable source paths.

[0114] In view of the above objectives, a third aspect of the present invention provides a computer device. Figure 6 The diagram shown is a schematic representation of an embodiment of the computer device provided by the present invention. Figure 6 As shown, the computer device of this embodiment includes the following means: at least one processor 021; and a memory 022, the memory 022 storing computer instructions 023 that can be executed on the processor, the instructions implementing the steps of the above method when executed by the processor.

[0115] The present invention also provides a computer-readable storage medium. Figure 7 The diagram shown is a schematic representation of an embodiment of the computer-readable storage medium provided by the present invention. Figure 7 As shown, computer-readable storage medium 031 stores a computer program 032 that, when executed by a processor, performs the methods described above.

[0116] Finally, it should be noted that those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program for the convergence method of the seismic source travel path can be stored in a computer-readable storage medium. When executed, the program can include the processes of the embodiments of the above methods. The storage medium for the program can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. The above computer program embodiments can achieve the same or similar effects as any of the corresponding foregoing method embodiments.

[0117] Furthermore, the method disclosed in the embodiments of the present invention can also be implemented as a computer program executed by a processor, which may be stored in a computer-readable storage medium. When the computer program is executed by the processor, it performs the functions defined in the method disclosed in the embodiments of the present invention.

[0118] Furthermore, the above-described method steps and system units can also be implemented using a controller and a computer-readable storage medium for storing a computer program that enables the controller to perform the functions of the above-described steps or units.

[0119] Those skilled in the art will also understand that the various exemplary logic blocks, modules, circuits, and algorithm steps described in conjunction with the disclosure herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability between hardware and software, the functionality of various illustrative components, blocks, modules, circuits, and steps has been generally described. Whether this functionality is implemented as software or as hardware depends on the specific application and the design constraints imposed on the system as a whole. Those skilled in the art can implement the functionality in various ways for each specific application, but such implementation decisions should not be construed as departing from the scope of the embodiments disclosed herein.

[0120] In one or more exemplary designs, functionality may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functionality may be stored as one or more instructions or code on or transmitted via a computer-readable medium. Computer-readable media include computer storage media and communication media, including any medium that facilitates the transfer of a computer program from one location to another. Storage media may be any available medium accessible to a general-purpose or special-purpose computer. By way of example, and not limitation, computer-readable media may include RAM, ROM, EEPROM, CD-ROM or other optical disc storage devices, disk storage devices or other magnetic storage devices, or any other medium that may be used to carry or store the required program code in the form of instructions or data structures and is accessible to a general-purpose or special-purpose computer or a general-purpose or special-purpose processor. Furthermore, any connection may be appropriately referred to as computer-readable media. For example, if software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DOL), or wireless technologies such as infrared, radio, and microwave, then the aforementioned coaxial cable, fiber optic cable, twisted pair, DOL, or wireless technologies such as infrared, radio, and microwave are all included in the definition of media. As used herein, disks and optical discs include compact discs (CDs), laser discs, optical discs, digital versatile discs (DVDs), floppy disks, and Blu-ray discs, where disks typically reproduce data magnetically, while optical discs reproduce data optically using lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0121] The above are exemplary embodiments disclosed in this invention. However, it should be noted that various changes and modifications can be made without departing from the scope of the embodiments of this invention as defined by the claims. The functions, steps, and / or actions of the methods according to the disclosed embodiments described herein do not need to be performed in any particular order. Furthermore, although the elements disclosed in the embodiments of this invention may be described or claimed individually, they may be understood as multiple unless explicitly limited to a singular number.

[0122] It should be understood that, as used herein, the singular form “a” is intended to include the plural form as well, unless the context clearly supports an exception. It should also be understood that, as used herein, “and / or” refers to any and all possible combinations of one or more of the associated listed items.

[0123] The embodiment numbers disclosed in the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0124] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0125] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples. Within the framework of the invention, technical features of the above embodiments or different embodiments can be combined, and many other variations of different aspects of the invention exist, which are not provided in the details for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.

Claims

1. A method for converging the trajectory of an earthquake source, characterized in that, Includes the following steps: Read the original path scheme containing multiple sets of earthquake source travel paths, and generate multiple derived path schemes based on the original path scheme using a random perturbation generation method, and use all the derived path schemes as the current parent population. Based on the current parent population, a child population is generated using roulette wheel and simulated annealing methods. Each scheme in the child population is perturbed, and the minimum evaluation value of the current child population and its corresponding scheme are obtained. as well as The current subpopulation is used as the new current parent population and the previous step is repeated to obtain multiple schemes that meet the preset conditions, thereby obtaining multiple sets of convergence path schemes for the controllable source travel paths. Based on the original path scheme, multiple derived path schemes are generated using a random perturbation generation method, including: Copy from the original path scheme D0 to Di; Set the current position p to 2; A random number q between 2 and N-1 is randomly generated. If the current position p is not equal to the random number q, the node sequence value Vp of position p and the node sequence value Vq of position q are swapped, and it is determined whether p is less than N-1. If p is less than N-1, then increment p by 1 and repeat the previous step; If p is not less than N-1, then a derived path scheme is generated and the evaluation value of the current scheme is calculated. Generating a child population based on the current parent population using roulette wheel and simulated annealing methods includes: Several schemes are randomly selected from the parent population, and their distribution probabilities are calculated based on the evaluation values ​​of the schemes. A probability value is randomly generated, and a corresponding scheme is selected based on the probability value and the distribution probability, and the scheme is copied to generate a sub-scheme. Determine whether the number of generated sub-solutions has reached the preset number. If the number of generated sub-solutions has not reached the preset number, repeat the above steps. If the number of generated sub-solutions has reached the preset number, then the generated sub-solutions are taken as subpopulations. Perturbing each scheme in the subpopulation includes: Set the current position p to 2 and calculate the current acceptable inverse evaluation value; A random number q between 2 and N is generated. If the current position p is not equal to the random number q, the evaluation value before the change and the evaluation value after the change are calculated and compared. If the pre-change evaluation value is not less than the post-change evaluation value, then the pre-change evaluation value is subtracted from the post-change evaluation value to obtain the evaluation difference, and a decision is made on whether to accept the change based on the evaluation difference, the random probability value, and the current acceptable inverse evaluation value. If the change is accepted, the value corresponding to position p is removed from the queue and inserted into position q; Determine if p is less than N-1. If p is less than N-1, increment p by 1, return to the previous step of generating a random number q between 2 and N, and repeat the above steps. If p is not less than N-1, then calculate the evaluation value of the current scheme and complete the perturbation of the current scheme.

2. The convergence method for the source travel path according to claim 1, characterized in that, The original path scheme includes at least the number of source groups and path node sequence values, wherein the path node sequence values ​​are integers and do not overlap.

3. The convergence method for the source travel path according to claim 1, characterized in that, Generating a child population based on the current parent population using roulette wheel and simulated annealing methods includes: The current parent population is cooled by multiplying the current temperature by a preset constant, which is greater than 0 and less than 1.

4. The convergence method for the source travel path according to claim 1, characterized in that, The probability distribution of the proposed schemes is calculated based on their evaluation values, including: Calculate the reciprocal of the logarithm of the evaluation values ​​of the given schemes, and sum them to obtain an intermediate value; The probability distribution corresponding to the several schemes is obtained by dividing the reciprocal of the logarithm of the evaluation value of the several schemes by the median value.

5. The convergence method for the source travel path according to claim 1, characterized in that, Also includes: If the current position p is equal to the random number q, then further determine whether p is less than N-1. If p is less than N-1, then add 1 to p, return to the process of randomly generating a random number q between 2 and N, and repeat the above steps. If p is not less than N-1, then calculate the evaluation value of the current scheme and complete the perturbation of the current scheme.

6. The convergence method for the source travel path according to claim 1, characterized in that, Also includes: If the pre-change evaluation value is less than the post-change evaluation value, then the value corresponding to position p is deleted from the queue and inserted into position q; Determine if p is less than N-1. If p is less than N-1, increment p by 1, return to the previous step of generating a random number q between 2 and N, and repeat the above steps. If p is not less than N-1, then calculate the evaluation value of the current scheme and complete the perturbation of the current scheme.

7. The convergence method for the source travel path according to claim 1, characterized in that, Also includes: If the change is not accepted, then further determine whether p is less than N-1. If p is less than N-1, then add 1 to p, return to the above steps, generate a random number q between 2 and N, and repeat the above steps. If p is not less than N-1, then calculate the evaluation value of the current scheme and complete the perturbation of the current scheme.

8. The convergence method for the source travel path according to claim 1, characterized in that, Calculating and comparing the pre-change and post-change assessment values ​​includes: Calculate the evaluation values ​​of the three line segments before the change, and sum them to obtain the evaluation value before the change; Calculate the evaluation values ​​of the three line segments after the change, and sum them to obtain the evaluation value after the change; The three line segments before the change are from position p-1 to position p, from position p to position p+1, and from position q-1 to position q, respectively. The three line segments after the change are from position p-1 to position p+1, from position q-1 to position p, and from position p to position q, respectively.

9. The convergence method for the source travel path according to claim 1, characterized in that, Determining whether to accept the change based on the evaluation difference, the random probability value, and the current acceptable inverse evaluation value includes: A random probability value greater than 0 and less than 1 is randomly generated, and the evaluated value is compared with the current acceptable inverse evaluated value. If the evaluated value is greater than the current acceptable reverse evaluated value, then no change is accepted; If the evaluated value is not greater than the current acceptable reverse evaluated value, but is greater than 1 / 4 of the current acceptable reverse evaluated value, then a decision is made on whether to accept the change based on the random probability value and the current acceptable reverse evaluated value. If the assessed value is not greater than 1 / 4 of the currently acceptable reverse assessed value, then the change is accepted.

10. The method for converging the source travel path according to claim 9, characterized in that, Determining whether to accept the change based on the random probability value and the current acceptable inverse evaluation value includes: If the evaluated value is not greater than the current acceptable inverse evaluated value, but is greater than 1 / 2 of the current acceptable inverse evaluated value, then it is further determined whether the random probability value is less than the function value of the current acceptable inverse evaluated value, wherein the function value is obtained by adding 1 to the current acceptable inverse evaluated value, taking the logarithm, subtracting 1 from the logarithm, and then dividing by 2. If the random probability value is less than the function value of the currently acceptable inverse evaluation value, then the change is accepted; If the random probability value is not less than the function value of the current acceptable inverse evaluation value, then no change is accepted; If the evaluated value is not greater than 1 / 2 of the current acceptable inverse evaluated value, but greater than 1 / 4 of the current acceptable inverse evaluated value, then it is further determined whether the random probability value is less than the current acceptable inverse evaluated value. If the random probability value is less than the current acceptable inverse evaluation value, then the change is accepted; If the random probability value is not less than the current acceptable inverse evaluation value, then no change is accepted.

11. The convergence method for the source travel path according to claim 1, characterized in that, Using the current subpopulation as the new current parent population and repeating the previous step, multiple schemes that meet preset conditions are obtained, resulting in multiple sets of convergence path schemes for controllable seismic source travel paths, including: Find the minimum evaluation value of the current subpopulation and its corresponding solution, and repeat the previous step; If the number of times the same solution appears exceeds a preset number, then stop repeating the previous step and output the solution. If the current temperature is lower than the preset temperature, stop repeating the previous step and output the solution. The output scheme is used as the convergence path scheme for multiple controllable seismic source travel paths.

12. A convergence device for the trajectory of an earthquake source, characterized in that, include: The initial module is configured to read the original path scheme containing multiple sets of earthquake source travel paths, and generate multiple derived path schemes based on the original path schemes using a random perturbation generation method, and use all the derived path schemes as the current parent population. The convergence module is configured to generate a subpopulation based on the current parent population using roulette wheel and simulated annealing methods, perturb each scheme in the subpopulation, and obtain the minimum evaluation value of the current subpopulation and its corresponding scheme. as well as The output module is configured to use the current subpopulation as the new current parent population and repeat the steps in the convergence module to obtain multiple schemes that meet preset conditions, thereby obtaining multiple sets of convergence path schemes for controllable seismic source travel paths. The initial module is also configured to: copy from the original path scheme D0 to Di; set the current position p to 2; randomly generate a random number q between 2 and N-1; if the current position p is not equal to the random number q, swap the node sequence value Vp of position p and the node sequence value Vq of position q, and determine whether p is less than N-1; if p is less than N-1, increment p by 1 and repeat the previous step; if p is not less than N-1, generate a derived path scheme and calculate the evaluation value of the current scheme. The convergence module is further configured to: randomly select several schemes from the parent population, calculate their distribution probabilities based on the evaluation values ​​of the several schemes, randomly generate a probability value, select the corresponding scheme based on the probability value and the distribution probability, and copy it to generate a sub-scheme; determine whether the number of generated sub-schemes reaches a preset number; if the number of generated sub-schemes does not reach the preset number, repeat the above steps; if the number of generated sub-schemes reaches the preset number, use the generated sub-scheme as a sub-population; set the current position p to 2, calculate the current acceptable inverse evaluation value; randomly generate a random number q between 2 and N; if the current position p is not equal to the random number q, then calculate... Calculate and compare the pre-change and post-change evaluation values; if the pre-change evaluation value is not less than the post-change evaluation value, subtract the pre-change evaluation value from the post-change evaluation value to obtain the evaluation difference, and determine whether to accept the change based on the evaluation difference, the random probability value, and the current acceptable inverse evaluation value; if the change is accepted, delete the value corresponding to position p from the queue and insert it into position q; determine whether p is less than N-1, if p is less than N-1, increment p by 1, return to the randomly generated random number q between 2 and N, and repeat the above steps; if p is not less than N-1, calculate the evaluation value of the current scheme and complete the perturbation of the current scheme.

13. A computer device, characterized in that, include: At least one processor; as well as A memory storing computer instructions executable on the processor, which, when executed by the processor, implement the steps of the method according to any one of claims 1-11.

14. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-11.

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