Well track anti-collision scanning method and device, electronic equipment and storage medium

Abstract

The invention provides a borehole trajectory anti-collision scanning method and device, electronic equipment and a storage medium, and belongs to the technical field of borehole detection.The method comprises the steps that first inclinometry data and first borehole trajectory calculation data of a reference well and second inclinometry data and second borehole trajectory calculation data of a comparison well are obtained; inputting the first inclinometry data, the second inclinometry data, the first borehole trajectory calculation data and the second borehole trajectory calculation data into an improved cuckoo algorithm by taking the nearest spatial distance between the trajectory points of the reference well and the comparison well as an objective function to obtain the trajectory point with the smallest spatial distance between the reference well and the comparison well; wherein the improved cuckoo algorithm comprises the following steps: on the basis of an original cuckoo algorithm, adjusting an inertia weight and a step size control factor based on the number of iterations, and dynamically adjusting a parasitic nest elimination probability based on a fitness variance of a population. The technical problems that time and labor are wasted and convergence is poor in the prior art are effectively solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wellbore detection, in particular to a wellbore trajectory anti-collision scanning method and device, electronic equipment and storage medium. BACKGROUND

[0002] With the old oil field entering the later stage of production, many oil fields choose to increase the well spacing density by casing window sidetracking and other means to improve the recovery rate. Offshore oil and gas wells are often developed by changing the wellhead group from the well to improve the development efficiency due to the limitation of platform space. With the increase of the number of wellheads, the wellbore trajectory becomes more and more complex, and both of the above two means face the risk of collision of wellbore trajectory. The collision of wellbore trajectory will drill through the casing of adjacent well, which threatens the safety of downhole operation and even causes major safety accidents such as leakage and shutdown, resulting in huge economic losses. The wellbore trajectory anti-collision scanning is to prevent the collision from happening, to scan the reference well and its surrounding adjacent wells to obtain the nearest distance between the wells, and to make a collision risk warning in time so as to adjust the well structure and optimize the wellbore trajectory.

[0003] Therefore, in order to accurately obtain the nearest distance between adjacent wells, it is necessary to explore the technical principle of wellbore trajectory anti-collision scanning, which can provide help for subsequent method modeling and guidance for field construction.

[0004] Wellbore trajectory design is an important part of drilling engineering design. How to design a reasonable and economic wellbore trajectory has been a subject of research and exploration by experts in the field of oil and gas wells at home and abroad. It is found through investigation and analysis that most of the traditional methods are iterative methods for calculation, which not only consumes time and effort, but also has difficulty in convergence, and cannot meet the needs of current drilling engineering. SUMMARY

[0005] Therefore, it is necessary to provide a wellbore trajectory anti-collision scanning method, device, electronic equipment and storage medium to solve the technical problem of time-consuming and poor convergence of the prior art.

[0006] In order to solve the above technical problems, in a first aspect, the present application provides a wellbore trajectory anti-collision scanning method, comprising: obtaining first inclination data and first wellbore trajectory calculation data of a reference well and second inclination data and second wellbore trajectory calculation data of a comparison well; taking the nearest space distance between the trajectory points of the reference well and the comparison well as the objective function, inputting the first inclination data, the second inclination data, the first wellbore trajectory calculation data and the second wellbore trajectory calculation data into the improved cuckoo algorithm to obtain the trajectory point with the minimum space distance between the reference well and the comparison well, and completing the anti-collision scanning; The improved cuckoo algorithm comprises: On the basis of the original cuckoo algorithm, the inertia weight and the step length control factor are dynamically adjusted based on the current iteration number, and the parasitic nest elimination probability is dynamically adjusted based on the fitness variance of the population.

[0007] In some embodiments of the present application, before the first inclination data, the second inclination data, the first borehole trajectory calculation data and the second borehole trajectory calculation data are input into the improved cuckoo algorithm, further comprising: Converting the inclination data and borehole trajectory calculation data of the reference well and the comparison well to a preset same spatial coordinate system.

[0008] In some embodiments of the present application, the inertia weight of the improved cuckoo algorithm comprises:

[0009] In the formula, is the inertia weight at the tth iteration; is the maximum value of the inertia weight, is the minimum value of the inertia weight; is the maximum iteration number.

[0010] In some embodiments of the present application, the step length control factor of the improved cuckoo algorithm comprises:

[0011] In the formula, is the step length control factor at the tth iteration; is the initial step length control factor; is the maximum iteration number.

[0012] In some embodiments of the present application, the parasitic nest elimination probability of the improved cuckoo algorithm comprises:

[0013] In the formula, is the fitness variance of the population; n is the number of individuals in the population; is the fitness value of the ith individual; is the average fitness of the population; is the dynamic discovery probability at the tth iteration.

[0014] In some embodiments of the present application, the first inclination data, the second inclination data, the first borehole trajectory calculation data and the second borehole trajectory calculation data are input into the improved cuckoo algorithm to obtain the trajectory point with the minimum spatial distance between the reference well and the comparison well, comprising: Step one, setting initial parameters of the cuckoo search algorithm, wherein the initial parameters include: population size, inertia weight range, maximum iteration number and initial step control factor.

[0015] Step two, randomly generating a plurality of first trajectory points on the reference well and the comparison well respectively, while calculating the target function value corresponding to the matching of a plurality of first trajectory points on the two wells, and taking the first trajectory point corresponding to the minimum value as the current solution; Step three, based on the currently generated points, generating a plurality of second trajectory points on the reference well and the comparison well respectively through Levy flight, and iteratively calculating the second target function value corresponding to the matching of a plurality of second trajectory points on the two wells; Step four, if the second target function value is smaller than the current solution, replacing the current solution with the second trajectory point corresponding to the second target function value; Step five, judging whether the current iteration number t reaches the maximum iteration number . Step six, if t max , the next round of iteration is continued until the termination condition is met; Step seven, if t=T max , the algorithm is terminated and the search result is output.

[0016] In some embodiments of the present application, before entering step five, further comprising: Randomly changing the replaced current solution based on the parasitic nest elimination probability.

[0017] In a second aspect, the present application also provides a wellbore trajectory anti-collision scanning device, comprising: A data acquisition module for acquiring first inclination data and first wellbore trajectory calculation data of a reference well, and second inclination data and second wellbore trajectory calculation data of a comparison well; An anti-collision scanning module for taking the minimum spatial distance between the trajectory points of the reference well and the comparison well as the target function, inputting the first inclination data, the second inclination data, the first wellbore trajectory calculation data and the second wellbore trajectory calculation data into the improved cuckoo search algorithm, obtaining the trajectory point with the minimum spatial distance between the reference well and the comparison well, and completing the anti-collision scanning.

[0018] In a third aspect, the present application also provides an electronic device, comprising: A memory for storing a program; A processor coupled with the memory for executing the program stored in the memory to implement the steps of the wellbore trajectory anti-collision scanning method in any one of the above methods.

[0019] In a fourth aspect, the present application further provides a storage medium comprising: for storing computer-readable programs or instructions, which are executed by a processor to implement the steps of the well trajectory anti-collision scanning method according to any one of the above method embodiments.

[0020] The well trajectory anti-collision scanning method provided by the present application is based on the obtained detailed well trajectory calculation data to establish a well trajectory nearest distance objective function, and the model is integrated into the cuckoo algorithm to search for the minimum distance between adjacent wells, thereby completing the anti-collision scanning. Moreover, the traditional cuckoo algorithm is improved, and the non-linear inertia weight, dynamic step control factor and dynamic discovery probability are introduced to optimize the algorithm parameters, thereby enhancing the search accuracy and accelerating the convergence process of the algorithm. The technical problems of time-consuming and labor-consuming and poor convergence of the prior art are effectively solved. BRIEF DESCRIPTION OF DRAWINGS In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. 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 creative labor.

[0021] Figure 1 A flowchart of an embodiment of the well trajectory anti-collision scanning method provided by the present application; Figure 2 A well trajectory nearest distance scanning schematic diagram provided by the present application; Figure 3 A flowchart of an embodiment of step S103 in the method; Figure 1 A flowchart of an embodiment of step S103 in the method; Figure 4 A structural schematic diagram of an embodiment of the well trajectory anti-collision scanning device provided by the present application; Figure 5 A structural schematic diagram of an embodiment of the electronic device provided by the present application. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings of the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0023] In the description of the embodiments of the application, unless otherwise specified, the meaning of "multiple" is two or more than two. The association relationship of the associated objects is described, which means that there can be three relationships, for example: A and / or B, which can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone.

[0024] The descriptions of "first", "second", etc. involved in the embodiments of the application are only for the purpose of description, and cannot be understood as indicating or implying the relative importance of the indicated technical features or implicitly indicating the number of the indicated technical features. Therefore, the technical features limited by "first" and "second" can be explicitly or implicitly included at least one of the features.

[0025] In this paper, the reference to "embodiments" means that the specific features, structures or properties described in conjunction with the embodiments can be included in at least one embodiment of the application. The appearance of this phrase in the specification does not necessarily mean the same embodiment, nor is it an independent or alternative embodiment to other embodiments. The skilled person in the art explicitly and implicitly understands that the embodiments described herein can be combined with other embodiments.

[0026] The application provides a wellbore trajectory anti-collision scanning method, device, electronic equipment and storage medium, which are described below.

[0027] Figure 1 An embodiment flowchart of the wellbore trajectory anti-collision scanning method provided by the application is shown in Figure 1 The wellbore trajectory anti-collision scanning method comprises: S101, obtaining first inclination data and first wellbore trajectory calculation data of a reference well and second inclination data and second wellbore trajectory calculation data of a comparison well.

[0028] S102, converting the inclination data and the wellbore trajectory calculation data of the reference well and the comparison well to a preset same spatial coordinate system.

[0029] S103, taking the spatial distance between the trajectory points of the reference well and the comparison well as the objective function, inputting the first inclination data, the second inclination data, the first wellbore trajectory calculation data and the second wellbore trajectory calculation data into the improved cuckoo algorithm, obtaining the trajectory point with the minimum spatial distance between the reference well and the comparison well, and completing the anti-collision scanning.

[0030] Figure 2 The wellbore trajectory nearest distance scanning schematic diagram in the embodiment of the application is shown in The nearest distance scanning is also called spherical distance scanning, the reference well is recorded as L 1, and the comparison well is recorded as L 2, L1i For L 1, a point on L 2j For L 2, a point on the reference well L 1, a point on L 1i As a reference point, and with point L 1i As the center of the circle, a spherical surface with a radius of p With the change of the radius p , a point L 2 can be obtained on the comparison well which is tangent to the spherical surface L 2j , L 1i The coordinate vectors of L 2j and r 1i and r 2j , the unit tangent vector of the well trajectory at point L 1i is t 1i Then: (1) Where the unit tangent vector of t 1i is: (2) Combining the above two equations (1) and (2), we get: (3) In equation (3), N 1i , N 2j are the north coordinates of the points on the reference well and the comparison well, respectively, m; E 1i , E 2j are the east coordinates of the points on the reference well and the comparison well, respectively, m; D 1i , D 2j are the vertical depths of the points on the reference well and the comparison well, respectively, m.

[0031] The nearest distance of the point on the reference well to the comparison well needs to satisfy the above equation (3).

[0032] Further, the present application takes the shortest distance in two-point space as the objective function: (4) In equation (4):N 1i , N 2j respectively represent the north coordinates of points on the reference well and the comparison well, m; E 1i , E 2j respectively represent the east coordinates of points on the reference well and the comparison well, m; D 1i , D 2j respectively represent the vertical depths of points on the reference well and the comparison well, m.

[0033] The improved cuckoo algorithm comprises: on the basis of the original cuckoo algorithm, dynamically adjusting the inertia weight and the step length control factor based on the current iteration number, and dynamically adjusting the parasitic nest elimination probability based on the fitness variance of the population.

[0034] Specifically, in some embodiments of the present application, the inertia weight of the improved cuckoo algorithm comprises: (5) In formula (5), is the inertia weight at the tth iteration; is the maximum value of the inertia weight, is the minimum value of the inertia weight; is the maximum iteration number.

[0035] In some embodiments of the present application, the step length control factor of the improved cuckoo algorithm comprises: (6) In formula (6), is the step length control factor at the tth iteration; is the initial step length control factor; is the maximum iteration number.

[0036] In some embodiments of the present application, the parasitic nest elimination probability of the improved cuckoo algorithm comprises: (7) In formula (7), is the fitness variance of the population; n is the number of individuals in the population; is the fitness value of the ith individual; is the average fitness of the population; is the dynamic discovery probability at the tth iteration.

[0037] Compared with the prior art, the wellbore trajectory anti-collision scanning method provided by the application establishes a wellbore trajectory nearest distance objective function based on the obtained detailed wellbore trajectory calculation data, integrates a model into a cuckoo algorithm, and searches for the minimum distance between adjacent wells by using the algorithm, thereby completing the anti-collision scanning. Moreover, the traditional cuckoo algorithm is improved, a nonlinear inertia weight, a dynamic step control factor and a dynamic discovery probability are introduced to optimize the algorithm parameters, and the search accuracy and accelerated convergence process of the algorithm are strengthened. The technical problems of time-consuming and laborious and poor convergence of the prior art are effectively solved.

[0038] As Figure 3 In some embodiments of the application, step S103 comprises: S301, setting initial parameters of the cuckoo search algorithm.

[0039] The initial parameters include: population size , inertia weight range , maximum iteration number , initial step control factor .

[0040] S302, randomly generating a plurality of first trajectory points on the reference well and the comparison well respectively, simultaneously calculating the corresponding objective function values after matching a plurality of first trajectory points on the two wells, and taking the first trajectory point corresponding to the minimum value as the current solution.

[0041] Specifically, on L 1 and L 2, a plurality of points n and are randomly generated, and a total of 2 points are obtained. Each point is a three-dimensional vector, represented as n and , and all points on the two wells are paired and the corresponding objective function values are calculated, totaling 2 , and then the point corresponding to the minimum value is selected from the n 2 values as the current solution n .

[0042] S303, based on the first trajectory points, generating a plurality of second trajectory points on the reference well and the comparison well respectively by Levy flight, and iteratively calculating the corresponding second objective function values after matching a plurality of second trajectory points on the two wells.

[0043] Specifically, for each current solution , a new solution is generated by inertia weight dynamic adjustment Levy flight. The formula is:​ (8) In formula (8), is a random step length subject to a Levy distribution.

[0044] The probability density function of the Levy distribution has a heavy-tail property, so that the algorithm can search in a large range during the search process and avoid falling into a local optimum.

[0045] First, two random variables subject to a normal distribution are generated by the following formula and . Wherein: ; Levy flight step length s is ; is the inertia weight at the t th iteration, and its mathematical expression is: ; It should be noted that the inertia weight will change dynamically with the number of iterations t . A high inertia weight at the beginning of iteration can enhance the global search ability, and a low inertia weight at the later iteration can enhance the local fine search ability.

[0046] is a dynamic step scaling factor, and its expression is: ; The calculation formula of each dimension of the new solution is: ; Wherein, is the s th dimension of the Levy flight step length j .

[0047] S304, if the second target function value is less than the current solution, the second trajectory point corresponding to the second target function value is used to replace the current solution.

[0048] Specifically, according to the specific optimization problem, a fitness function is defined to evaluate the pros and cons of the new solution. In the minimization function problem, the fitness function is the target function itself. The fitness value of the new solution If the fitness value corresponding to the new solution is smaller than the fitness value of the current solution (in the minimization problem), the new solution is better.

[0049] The fitness values of the new solution and the current solution are compared. If If so, replace the current solution with the new solution, i.e. This step simulates the behavior of the cuckoo when it is looking for a better nest (solution). Only when the newly found nest is better, the cuckoo will choose it.

[0050] S305, randomly change the current solution after replacement based on the parasitic nest elimination probability.

[0051] It should be noted that the traditional fixed probability Pa may eliminate potential high-quality solutions too early in the early iterations, and it is difficult to escape from local optimality in the later iterations. Replace the fixed probability Pa with the dynamically discovered probability Pa(t), and randomly select a part of the solution for random change, simulating the process of the host bird discovering the eggs of the foreign bird and discarding them. For each selected solution , adjust the parasitic nest elimination probability adaptively:

[0052] This step enables the algorithm to jump out of the local optimal solution to a certain extent and increase the diversity of the search.

[0053] S306, judge whether the current iteration number t reaches the maximum iteration number T .

[0054] S307, if t < T max , continue the next round of iteration until the termination condition is met; if t = T max , the algorithm terminates and outputs the search result.

[0055] Specifically, after each iteration, check whether the current iteration number t is equal to the maximum iteration number T max . If t = T max , the algorithm terminates and outputs the optimal solution. The optimal solution is the solution with the best fitness value in the entire iteration process. If t < T max , increase the iteration number t by 1 (t = t + 1), and then return to the iteration process to continue the next round of iteration until the termination condition is met.

[0056] In summary, the present application firstly unifies the inclination data of the reference well and the adjacent well to the same spatial coordinate system, and establishes a mathematical model with the minimum spatial distance between the trajectory points of the two wells as the objective function. The traditional cuckoo algorithm is innovatively improved, and nonlinear inertia weight, dynamic step control factor and dynamic discovery probability are introduced. The nonlinear inertia weight is dynamically adjusted according to the number of iterations, which enhances the global search ability in the early search stage and strengthens the local fine search in the later stage, effectively balancing the search strategy of the algorithm; the dynamic step control factor makes the Levy flight step more adaptive and can better explore the search space; the dynamic discovery probability avoids eliminating potential high-quality solutions too early in the early stage of iteration by adaptively adjusting the parasitic nest elimination probability, and can effectively jump out of the local optimal solution in the later stage, improving the search diversity of the algorithm. The advantage lies in that the algorithm structure is simple and robust, can quickly identify the collision risk, and provides a reliable basis for optimizing the well trajectory design and adjusting the drilling scheme, which has important engineering application value for ensuring the safety of downhole operation and reducing the risk of accidents.

[0057] As Figure 4 In a second aspect, the present application further provides a well trajectory anti-collision scanning device 40, comprising: A data acquisition module 410 is configured to acquire the first inclination data and the first well trajectory calculation data of the reference well, and the second inclination data and the second well trajectory calculation data of the comparison well; An anti-collision scanning module 420 is configured to take the minimum spatial distance between the trajectory points of the reference well and the comparison well as the objective function, input the first inclination data, the second inclination data, the first well trajectory calculation data and the second well trajectory calculation data into the improved cuckoo algorithm, obtain the trajectory points with the minimum spatial distance between the reference well and the comparison well, and complete the anti-collision scanning.

[0058] As Figure 5 In a third aspect, the present application further provides an electronic device 50, comprising: A storage 510 is configured to store programs; A processor 520 is coupled to the storage 510 and is configured to execute the programs stored in the storage 510 to implement the steps of the well trajectory anti-collision scanning method in any one of the above method embodiments.

[0059] It should be understood that, in addition to the above functions, the processor 520 can also implement other functions when executing the magnetic resonance image optimization program in the storage 510, which can be specifically understood with reference to the description of the corresponding method embodiments.

[0060] Further, the type of the electronic device 50 referred to in the embodiments of the present application is not specifically limited, and the electronic device 70 can be a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop, or the like. Exemplary embodiments of the portable electronic device include, but are not limited to, a portable electronic device running an IOS, an android, a microsoft, or other operating system. The portable electronic device described above can also be other portable electronic devices, such as a laptop having a touch-sensitive surface (e.g., a touch panel), and the like. It should also be understood that in some other embodiments of the present application, the electronic device 50 can also not be a portable electronic device, but a desktop computer having a touch-sensitive surface (e.g., a touch panel).

[0061] In a fourth aspect, the present application also provides a storage medium comprising: a computer readable program or instructions for storing, which, when executed by a processor, can implement the steps of the well trajectory anti-collision scanning method in any one of the above method items Those skilled in the art can understand that all or part of the processes of the above-mentioned embodiments can be completed by a computer program instructing relevant hardware (such as a processor, a controller, etc.) to complete. The computer program can be stored in a computer readable storage medium. The computer readable storage medium includes a magnetic disk, an optical disk, a read-only memory, a random access memory, and the like.

[0062] The well trajectory anti-collision scanning method, device, electronic device, and storage medium provided by the present application are described in detail above. The principles and implementation manners of the present application are described by applying specific examples in this paper. The above description of the embodiments is only used to help understand the method of the present application and its core idea. Meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation manner and application range can be changed. In summary, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A wellbore trajectory anti-collision scanning method, characterized in that: include: Acquiring first inclination survey data and first wellbore trajectory calculation data of the reference well and second inclination survey data and second wellbore trajectory calculation data of the comparison well; Taking the shortest spatial distance between the trajectory points of the reference well and the comparison well as the objective function, the first inclination survey data, the second inclination survey data, the first wellbore trajectory calculation data, and the second wellbore trajectory calculation data are input into the improved cuckoo algorithm to obtain the trajectory point with the smallest spatial distance between the reference well and the comparison well, thereby completing the anti-collision scan; The improved cuckoo algorithm includes: Based on the original cuckoo algorithm, the inertia weight and step size control factor are dynamically adjusted according to the current number of iterations, and the probability of parasitic nest elimination is dynamically adjusted based on the fitness variance of the population.

2. The wellbore trajectory anti-collision scanning method according to claim 1, characterized in that: Before inputting the first inclination measurement data, the second inclination measurement data, the first wellbore trajectory calculation data, and the second wellbore trajectory calculation data into the improved cuckoo algorithm, the method further includes: The inclination survey data and wellbore trajectory calculation data of the reference well and the inclination survey data and wellbore trajectory calculation data of the comparison well are converted into a preset same space coordinate system.

3. The wellbore trajectory anti-collision scanning method according to claim 1, characterized in that: The inertia weights of the improved cuckoo algorithm include: Where, is the inertia weight at the tth iteration; is the maximum value of the inertia weight, is the minimum value of the inertia weight; is the maximum number of iterations.

4. The wellbore trajectory anti-collision scanning method according to claim 1, characterized in that: The step size control factors of the improved cuckoo algorithm include: Where, is the step size control factor at the tth iteration; is the initial step size control factor; is the maximum number of iterations.

5. The wellbore trajectory anti-collision scanning method according to claim 1, characterized in that: The parasitic nest elimination probability of the improved cuckoo algorithm includes: Where, is the population fitness variance; n is the number of individuals in the population; is the fitness value of the i-th individual; is the average fitness of the population; is the dynamic discovery probability at the tth iteration.

6. The wellbore trajectory anti-collision scanning method according to claim 1, characterized in that: The step of inputting the first inclination measurement data, the second inclination measurement data, the first wellbore trajectory calculation data, and the second wellbore trajectory calculation data into the improved cuckoo algorithm to obtain a trajectory point with the minimum spatial distance between the reference well and the comparison well comprises: Step 1: setting the initial parameters of the cuckoo search algorithm, wherein the initial parameters include: population size, inertia weight range, maximum number of iterations, and initial step size control factor; Step 2: randomly generate a number of first trajectory points on the reference well and the comparison well, and calculate the corresponding objective function values ​​after matching the first trajectory points on the two wells, and take the first trajectory point corresponding to the minimum value as the current solution; Step 3: Based on the first trajectory point, generate several second trajectory points on the reference well and the comparison well through Levy flight, and traverse and calculate the second objective function value corresponding to the mutual matching between the several second trajectory points on the two wells; Step 4: If the second objective function value is less than the current solution, the current solution is replaced by the second trajectory point corresponding to the second objective function value; Step 5: Determine whether the current number of iterations t reaches the maximum number of iterations ; Step 6: If t <T max , continue to the next round of iteration until the termination condition is met; Step 7: If t=T max , the algorithm terminates and outputs the search results.

7. The wellbore trajectory anti-collision scanning method according to claim 6, characterized in that: Before entering step 5, it also includes: The current solution after replacement is randomly changed based on the probability of parasitic nest elimination.

8. A wellbore trajectory anti-collision scanning device, characterized in that: include: A data acquisition module, configured to acquire first inclination measurement data and first wellbore trajectory calculation data of a reference well and second inclination measurement data and second wellbore trajectory calculation data of a comparison well; The anti-collision scanning module is used to input the first inclination measurement data, the second inclination measurement data, the first wellbore trajectory calculation data, and the second wellbore trajectory calculation data into the improved cuckoo algorithm, using the shortest spatial distance between the trajectory points of the reference well and the comparison well as the objective function, to obtain the trajectory point with the smallest spatial distance between the reference well and the comparison well, thereby completing the anti-collision scanning.

9. An electronic device, characterized in that: include: Memory, used to store programs; A processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps of the wellbore trajectory anti-collision scanning method described in any one of claims 1 to 7.

10. A storage medium, characterized in that: include: Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps of the wellbore trajectory anti-collision scanning method described in any one of claims 1 to 7.

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