Design method, system and device for wellbore anti-collision of cluster well group

Abstract

The application provides a cluster well group wellbore anti-collision design method, system and equipment, and belongs to the technical field of oil and gas development drilling. The wellbore anti-collision design method comprises the following steps: dividing a unit cell, and establishing a list of storage space nodes; determining a build-up point depth, and storing a wellhead and the build-up point node to a confirmed list; searching and judging whether all adjacent nodes around a current node are stored in a to-be-searched list, and calculating a generation value F of the adjacent node; through loop comparison of the size of the F value, a node of a preliminary design trajectory is obtained; and the output node trajectory is optimized, the node trajectory is optimized into a smooth curve, and output is performed. The application can provide a new trajectory design idea for a large platform cluster well group, simplifies an obstacle circumventing design process, reduces the risk of trajectory intersection and collision of the cluster well group from a design level, realizes intelligent searching for an optimal trajectory, improves design output efficiency, and reduces labor intensity.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wellbore anti-collision design, in particular to a cluster well group wellbore anti-collision design method, a cluster well group wellbore anti-collision design system, and a computer device and a computer readable storage medium for implementing the cluster well group wellbore anti-collision design method. BACKGROUND

[0002] In recent years, in order to realize low-cost and high-efficiency development of oil and gas resources and improve the centralized management capability of oil and gas wells, a large number of cluster well groups with single platform and multiple well numbers are adopted in Sichuan-Chongqing, Changqing and Tarim regions, and cluster well platforms are widely used for drilling of shale oil and gas, tight oil and gas and gas storage wells.

[0003] Due to small wellhead spacing, usually five to eight meters, large platform cluster well groups have a large number of wells, and wellbore trajectories are staggered and have complex spatial relationships. At present, professional trajectory design software for directional wells is developed for single well trajectory design, and a complete single wellbore trajectory is mostly formed by combining different profile types. Subsequent well design process includes anti-collision scanning and optimization of previously designed wells one by one until the trajectory design of the last well of the platform is completed. For multi-well trajectory design of large platform cluster well groups, the software cannot automatically optimize the designed trajectory while considering anti-collision. When the anti-collision distance does not meet the requirements in the subsequent well design process, the designed well trajectory may be adjusted, and the adjustment of the designed well trajectory will affect other designed wells, and the overall anti-collision scanning and optimization process is repeated, tedious, time-consuming and laborious. The widely used Navigator and SunnyPathing software in China are also designed for single well trajectory one by one and anti-collision scanning, and cannot meet the requirements of automatic anti-collision optimization in the trajectory design process. At the same time, the wellbore trajectory design process is subject to the technical level and experience of the operating personnel, and the anti-collision design and control degree is uneven, which affects the scientificity and operability of the trajectory design. Once an error occurs, it will bring greater difficulty and risk to the anti-collision operation.

[0004] Solving the anti-collision problem is the core to ensure the safety and efficiency of cluster well groups and infill wells. Anti-collision work runs through all links of well group pre-drilling preparation, engineering design and construction. In order to minimize the risk of wellbore collision and reduce the difficulty of drilling construction and the total cost of drilling, the drilling engineering design must be optimized as a whole.

[0005] At present, the design of wellbore anti-collision for large platform cluster wells is still lack of theoretical research. For example, the patent document with the invention name of wellbore trajectory control system based on process control and the publication number of CN108571287A discloses a technical method of controlling wellbore trajectory based on the directional deflecting characteristics of a steering tool. The method forms a technical method of controlling wellbore trajectory based on the directional deflecting characteristics of a steering tool by revealing the interaction and constraint relationship between the directional deflecting characteristics of the steering tool and the spatial flexure form of the wellbore trajectory. However, the method only considers the single well trajectory optimization design, and has little help for large platform cluster wells. The patent document with the invention name of a wellbore trajectory control method and the publication number of CN102425374A discloses a wellbore trajectory control method. The method includes wellbore trajectory design and wellbore trajectory control, and can meet the requirements of wellbore trajectory design and control of limiting the position and direction of the target point at the same time under multiple constraint conditions. However, the method does not consider the actual complex situation of large platform cluster wells, and cannot realize the best trajectory of large platform cluster well anti-collision safety requirements. The above two methods are considered from the aspect of single well trajectory optimization design, and have little help for the trajectory optimization design of large platform cluster well group. The current wellbore anti-collision calculation method mainly calculates the intersection probability through the actual drilling trajectory, and does not consider the anti-collision obstacle avoidance problem of adjacent wells in the design stage of large platform cluster well group. The current method is complicated in obstacle avoidance design process, and it is difficult to realize intelligent wellbore trajectory optimization design. The calculation of the shortest optimal path needs a lot of manual calculation. The solving method adopts the traditional optimization theory method, which does not meet the solving of the large well group cluster well anti-collision optimization model. SUMMARY

[0006] The present application aims to solve at least one of the above-mentioned deficiencies in the prior art. For example, the present application provides a cluster well group wellbore anti-collision design method to overcome the low efficiency of the prior art in the design and optimization of well trajectory for large platform cluster wells.

[0007] In order to achieve the above-mentioned purpose, the present application provides a cluster well group wellbore anti-collision design method, which comprises the following steps: S1, taking the wellhead of the target well as the center, the anti-collision area is gridded, and the coordinates (x i , y i , z iS2. Complete obstacle construction and store the obstacle area marker nodes in the confirmed list, and store the remaining grid nodes in the search list; S3. Determine the range of values ​​for well inclination, dogleg, and target azimuth; S4. Determine the depth of the start-up point, store the wellhead in the confirmed list, and set the node where the start-up point is located as the new trajectory node; S5. Starting from the start-up point, search and determine whether all adjacent nodes around the current node are stored in the search list. If not, skip the adjacent node. If yes, calculate the cost value F of the adjacent node; S6. Select the adjacent node with the smallest F value in step S5 as the new trajectory node and add it to the trajectory node list. Store the remaining adjacent nodes in the confirmed list; S7. Determine whether the new trajectory node is the target point. If not, continue to determine whether there are available continuous nodes in the search list. If yes, repeat step S6. If no, indicate that there is no solution and modify the depth of the build-up point. If yes, complete the search, output all trajectory nodes, and obtain the nodes of the preliminary design trajectory. S8. Starting from the wellhead node, check whether three adjacent trajectory nodes in the trajectory node list are collinear. If so, delete the middle trajectory node until all trajectory nodes are no longer collinear. S9. Using dogleg degree, well inclination, azimuth, and minimum length of the stable inclination segment as constraints, optimize the node trajectory in the trajectory node list into a smooth curve and output the optimized curve trajectory.

[0008] In an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention, the length of the unit grid in step S1 can be set to 0.5m to 1m.

[0009] In an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention, step S2 includes accumulating the anti-collision safety distance to the corresponding depth position of the adjacent well to complete the obstacle construction.

[0010] In an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention, the determination of the build-up point depth in step S4 may include calculating from the minimum build-up point depth. If there is no solution, the build-up point depth is increased by 5 to 20 m. The build-up point depth of the subsequent designed wells differs from the build-up point depth of the already designed wells by more than 20 m. The build-up point depth needs to be greater than the preset depth of the previous casing layer by 30 to 50 m.

[0011] In an exemplary embodiment of the wellbore anti-collision design method for cluster well groups of the present invention, the calculation method of the cost value F in step S5 can be as follows:

[0012] F = G + H

[0013] Where F is the total path cost of the current node; G is the cost used to move from the starting point to the current position, with D being the unit cost of movement along the coordinate axis and D being the unit cost of movement diagonally in the plane. The cost per unit movement when moving diagonally in space is H represents the theoretical minimum cost of moving from the current point to the target point along the coordinate axis without considering obstacles, and the cost per unit movement is D.

[0014] In an exemplary embodiment of the wellbore anti-collision design method of the cluster well group of the present invention, in step S8, it can be determined whether three adjacent trajectory nodes are collinear by whether the vector product of the original node and the trajectory node is 0. This includes setting the center coordinates of three consecutive trajectory nodes as (x0, y0, z0), (x1, y1, z1), and (x2, y2, z2), forming two vectors a(x1-x0, y1-y0, z1-z0) and b(x2-x0, y2-y0, z2-z0). If c = ab = |a||b|sinθ = 0, where a and b are vectors; c is the vector product; and θ is the angle between vectors a and b, then the three nodes are collinear; or there exists λ such that a = λb, then the three nodes are collinear.

[0015] In an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention, in step S9, the node trajectory can be optimized into a smooth curve using the circular arc optimization method.

[0016] Another aspect of the present invention provides a wellbore collision prevention design system for cluster well groups. The system includes a grid construction module, a confirmed list, a search list, a trajectory node list, a first parameter determination module, a second parameter determination module, a search module, a selection module, a target point judgment module, a collinearity judgment module, and a trajectory optimization module. The grid construction module is used to grid the collision prevention area with the target wellhead as the center, construct the collision prevention obstacle, and output the coordinates (x, y, y) of the center positions of all nodes. i y i z iThe confirmed list stores nodes confirmed as target points, obstacle zone markers, and nodes that have been searched but not selected as trajectory nodes. The search list stores nodes in the spatial grid that have not been marked or searched. Initially, the search list contains all nodes in the spatial grid. The trajectory node list stores wellhead nodes and nodes selected as new trajectory nodes during the search process. The search is completed when the last target point is added to the trajectory node list. The first parameter determination module determines the range of values ​​for well inclination, dogleg, and target azimuth. The second parameter determination module determines the depth of the build-up point. The search module is connected to the grid construction module and, starting from the build-up point, searches to determine whether all adjacent nodes around the current node are stored in the search list. If not, the adjacent node is skipped; otherwise, the cost value F of the adjacent node is calculated. The selection module is connected to the search module and selects the adjacent node with the smallest F value as the new trajectory node, storing the remaining adjacent nodes in the confirmed list. The target point judgment module is connected to the selection module. The system is connected to a block and includes a first judgment submodule and a second judgment submodule. The first judgment submodule is configured to determine whether a new trajectory node is a target point. If the determination is negative, the system proceeds to the second judgment submodule for further determination. If the determination is positive, the search is completed, a list of trajectory nodes is output, and the nodes of the preliminary design trajectory are obtained. The second judgment submodule is configured to determine whether the search list contains available continuous nodes. If it does, the system returns to the selection module to select a new trajectory node again. If it does not, the system indicates that there is no solution and returns to the second parameter determination module to modify the depth of the build-up point. The collinearity judgment module is connected to the first judgment submodule and is used to check whether three adjacent trajectory nodes in the trajectory node list are collinear, starting from the wellhead node. If they are collinear, the intermediate trajectory node is deleted until all trajectory nodes are no longer collinear. The trajectory optimization module is connected to both the collinearity judgment module and the first parameter determination module and is used to optimize the node trajectory into a smooth curve with constraints such as dogleg degree, well inclination, azimuth, and minimum length of the stable inclination segment, and output the optimized curve trajectory.

[0017] In another aspect, the present invention provides a computer device, the device comprising: a processor, a memory, and a computer program stored thereon, wherein when the computer program is executed by the processor, the cluster wellbore anti-collision design method described above is implemented.

[0018] In another aspect, the present invention provides a computer-readable storage medium that, when a computer program is executed by a processor, implements the cluster wellbore anti-collision design method as described above, thereby achieving anti-collision optimization design between the wellhead and the target point.

[0019] Compared with the prior art, the beneficial effects of the present invention may include at least one of the following:

[0020] (1) This invention proposes a wellbore anti-collision design method for cluster well groups, which solves the technical problems of limited wellbore space, high difficulty in anti-collision and obstacle bypass design, cumbersome manual design, and low drilling design output efficiency in large platform cluster well groups.

[0021] (2) This invention provides a design concept for the trajectory of a cluster well group on a large platform, which realizes intelligent search for the optimal trajectory, simplifies the obstacle avoidance design process, and reduces the risk of collision of cluster well group trajectories from the design level.

[0022] (3) This invention improves design output efficiency and reduces the labor intensity of personnel. Attached Figure Description

[0023] The above and other objects and / or features of the present invention will become clearer from the following description taken in conjunction with the accompanying drawings, in which:

[0024] Figure 1 A diagram illustrating the anti-collision barrier construction of an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention is shown.

[0025] Figure 2 A current trajectory node retrieval area map is shown as an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention.

[0026] Figure 3 The diagram shows a trajectory node path of an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention.

[0027] Figure 4 The diagram shows a feature point trajectory profile of deleting collinear trajectory nodes, representing an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention.

[0028] Figure 5 An optimized trajectory profile is shown as an exemplary embodiment of the wellbore anti-collision design method for cluster well groups according to the present invention.

[0029] Figure 6 A flowchart illustrating an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention is shown.

[0030] Figure 7 A calculation example of the collision avoidance space diagram of an exemplary embodiment of the cluster wellbore collision avoidance design method of the present invention is shown.

[0031] Figure 8 The diagram illustrates a scenario where the minimum cost node is unavailable in an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention.

[0032] Figure 9The diagram shows a trajectory node path of an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention.

[0033] Figure 10 A well inclination section restriction diagram is shown as an exemplary embodiment of the wellbore anti-collision design method for cluster well groups according to the present invention.

[0034] Figure 11 The diagram illustrates the target orientation limitation of an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention.

[0035] Figure 12 An optimized trajectory diagram of an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention is shown. Detailed Implementation

[0036] The following will describe in detail the cluster wellbore anti-collision design method, system and equipment of the present invention with reference to the accompanying drawings and specific embodiments.

[0037] Currently available drilling design software, both domestically and internationally, designs and performs anti-collision scanning for each individual well trajectory. Applying this software to large-scale cluster wells can lead to low process efficiency and inaccurate design results.

[0038] The current methods cannot meet the requirements for automated anti-collision optimization in the trajectory design process of large-scale cluster wells. Furthermore, wellbore trajectory design relies heavily on the technical skills and experience of the operators, resulting in inconsistent levels of anti-collision design and control, making it difficult to guarantee the scientific validity and operability of the trajectory design. Therefore, an automated method for cluster wellbore anti-collision design is urgently needed to solve these problems.

[0039] This invention provides a method for designing anti-collision features in large-platform cluster well groups. By gridding the anti-collision area, iteratively searching and judging, calculating the cost function, searching for the minimum cost trajectory from the wellhead to the target point, and optimizing the well trajectory with constraints such as dogleg degree, well inclination, azimuth, and minimum length of the stable inclination section, the method achieves optimized design for anti-collision features in cluster well groups.

[0040] To achieve the above objectives, the present invention provides a method for designing anti-collision features in cluster wellbore formations.

[0041] In an exemplary embodiment of the cluster wellbore anti-collision design method of the present invention, the anti-collision design method includes the following steps:

[0042] Step S1: Using the target wellhead as the center, mesh the anti-collision area and determine the center coordinates (x, y) of all nodes. i y i , z i ).

[0043] Specifically, the length of the cell grid in step S1 is set to 0.5m to 1m. For example, the length of the cell grid can be set to 1m based on the maximum length of the drill bit.

[0044] Step S2: Complete the obstacle construction, and store the obstacle area marker nodes in the confirmed list, and store the remaining grid nodes in the search list.

[0045] Complete the obstacle construction and store the grid nodes of the obstacle area in the confirmed list, and store the grid nodes of the anti-collision area in the search list.

[0046] Figure 1 This is a diagram illustrating the construction of the anti-collision barrier according to the present invention. It should be noted that... Figure 1 In the diagram, A represents the wellhead, B represents the target point, the shaded area represents the obstacle area that belongs to the confirmed list, and the white area represents the collision avoidance area that belongs to the search list.

[0047] Specifically, step S2 may include accumulating the anti-collision safety distance to the corresponding depth position of the adjacent well to complete the barrier construction.

[0048] Step S3: Determine the range of values ​​for well inclination, dogleg, and target azimuth. Well inclination reflects the degree of wellbore inclination. When the well inclination is too large, problems such as drill string pressure, wellbore wear, difficulty in carrying rock, and difficulty in running casing will occur. Dogleg reflects the degree of wellbore curvature. The range of values ​​is determined by the directional drilling capability of the directional drilling tool and whether subsequent tools such as casing can be successfully run. Target azimuth limits the azimuth angle when hitting the target point and affects the degree of reservoir opening.

[0049] Step S4: Determine the depth of the kick-in point, save the wellhead to the confirmed list, and set the node where the kick-in point is located as a new trajectory node.

[0050] Specifically, determining the depth of the kick-in point in step S4 may include starting the calculation from the minimum kick-in point depth. If there is no solution, the kick-in point depth is increased by 5 to 20 meters. The kick-in point depth of subsequent designed wells differs from that of the designed wells by more than 20 meters. The kick-in point depth must be greater than the preset depth of the previous casing layer by 30 to 50 meters.

[0051] Step S5: Starting from the point of origin, search and determine whether all neighboring nodes around the current node are stored in the search list. If not, skip the neighboring node. If not, calculate the cost F of the neighboring node.

[0052] Figure 2 To retrieve the region map for the current trajectory node, it should be noted that... Figure 2 In the diagram, A represents the current trajectory node, the shaded area represents the previous node (in the confirmed list), and the white area represents the area to be searched (in the search list).

[0053] Specifically, the value F in S5 is calculated as follows:

[0054] F = G + H

[0055] Where F is the total path cost of the current node; G is the cost used to move from the starting point to the current position, with D being the unit cost of movement along the coordinate axis and D being the unit cost of movement diagonally in the plane. The cost per unit movement when moving diagonally in space is H represents the theoretical minimum cost of moving from the current point to the target point along the coordinate axis without considering obstacles, and the cost per unit movement is D.

[0056] Step S6: Select the neighboring node with the smallest F value from step S5 as the new trajectory node, and store the remaining neighboring nodes in the confirmed list.

[0057] Step S7: Determine whether the new trajectory node is a target point. If the determination is no, continue to determine whether there are available continuous nodes in the search list. If the determination is yes, repeat step S6. If the determination is no, indicate that there is no solution and modify the depth of the inclination point. If the determination is yes, complete the search, output all trajectory nodes, and obtain the nodes of the preliminary design trajectory.

[0058] Figure 3 The diagram shows the trajectory node path output after executing step S7. It should be noted that in Figure 3, A represents the wellhead, B represents the target point, C represents the build-up point, the black area represents the anti-collision obstacle zone, and the gray area represents the trajectory node path.

[0059] Step S8: Starting from the wellhead node, check whether the three adjacent trajectory nodes are collinear. If so, delete the intermediate trajectory node until all trajectory nodes are no longer collinear.

[0060] Figure 4 The diagram shows a profile of the feature point trajectory after removing intermediate trajectory nodes. It should be noted that... Figure 4 In the diagram, A represents the wellhead, B represents the target point, the black area represents the anti-collision obstacle zone, and the line segment represents the feature point trajectory before optimization.

[0061] Specifically, in step S8, it can be determined whether three adjacent trajectory nodes are collinear by checking if the vector product of the original node and the trajectory node is 0. This includes setting the center coordinates of three consecutive trajectory nodes as (x0, y0, z0), (x1, y1, z1), and (x2, y2, z2), forming two vectors a(x1-x0, y1-y0, z1-z0) and b(x2-x0, y2-y0, z2-z0). If c = ab = |a||b|sinθ = 0, where a and b are vectors, c is the vector product, and θ is the angle between vectors a and b, then the three nodes are collinear; or if there exists λ such that a = λb, then the three nodes are collinear.

[0062] Step S9: Using dogleg degree, well inclination, azimuth, and minimum length of stable inclination segment as constraints, optimize the node trajectory into a smooth curve and output the optimized curve trajectory.

[0063] Figure 5 The optimized feature point trajectory profile is shown. It should be noted that... Figure 5 In the diagram, A represents the wellhead, B represents the target point, the black area represents the anti-collision obstacle zone, and the curve represents the optimized feature point trajectory.

[0064] Specifically, in step S9, the circular arc optimization method can be used to optimize the node trajectory into a smooth curve.

[0065] Specifically, the circular arc optimization method includes the following steps:

[0066] Based on the above calculation process, a flowchart of the wellbore anti-collision design method for cluster well groups is shown below. Figure 6 As shown.

[0067] Another aspect of the present invention provides a wellbore anti-collision design system for cluster well groups.

[0068] In an exemplary embodiment of the wellbore anti-collision design system of the present invention, the wellbore anti-collision design system includes a grid construction module, a confirmed list, a search list, a trajectory node list, a first parameter determination module, a second parameter determination module, a search module, a selection module, a target point judgment module, a collinearity judgment module, and a trajectory optimization module.

[0069] The mesh construction module is used to mesh the anti-collision area with the target wellhead as the center, complete the construction of anti-collision barriers, and output the coordinates of the center positions of all nodes (x, y, y). i y i , z i ).

[0070] The confirmed list stores nodes that have been confirmed as target points, obstacle zone markers, and nodes that have been searched but not selected as trajectory nodes.

[0071] The search list stores nodes in the spatial grid that have not been marked or searched. Initially, the search list contains all nodes in the spatial grid.

[0072] The trajectory node list is used to store wellhead nodes and nodes selected as new trajectory nodes during the search process. The search is completed when the last target point is added to the trajectory node list.

[0073] The first parameter determination module is used to determine the range of values ​​for well inclination, dogleg, and target azimuth.

[0074] The second parameter determination module is used to determine the depth of the skew point.

[0075] The search module is connected to the mesh construction module. Starting from the deflection point, it searches and determines whether all neighboring nodes around the current node are stored in the search list. If not, the neighboring node is skipped; otherwise, the cost F of the neighboring node is calculated.

[0076] The selection module is connected to the search module and is used to select the neighboring node with the smallest F value as the new trajectory node, while the remaining neighboring nodes are stored in the confirmed list.

[0077] The target point judgment module is connected to the selection module and includes a first judgment submodule and a second judgment submodule. The first judgment submodule is configured to judge whether a new trajectory node is a target point. If the judgment is negative, the second judgment submodule is entered to complete further judgment. If the judgment is positive, the search is completed, the trajectory node list is output, and the nodes of the preliminary design trajectory are obtained.

[0078] The second judgment submodule is configured to determine whether the search list contains available continuous nodes. If yes, it returns to the selection module to select a new trajectory node again. If no, it prompts that there is no solution and returns to the second parameter determination module to modify the depth of the inclination point.

[0079] The collinearity judgment module is connected to the first judgment submodule. It is used to check whether three adjacent trajectory nodes in the trajectory node list are collinear, starting from the wellhead node. If so, the middle trajectory node is deleted until all trajectory nodes are no longer collinear.

[0080] The trajectory optimization module is connected to the collinearity judgment module and the first parameter determination module, respectively. It is used to optimize the node trajectory into a smooth curve with constraints such as dogleg degree, well inclination, azimuth and minimum length of stable inclination segment, and output the optimized curve trajectory.

[0081] The cluster wellbore anti-collision design method according to the present invention can be programmed into a computer program and the corresponding program code or instructions can be stored in a computer-readable storage medium. When the program code or instructions are executed by a processor, the processor performs the above-described cluster wellbore anti-collision design method. The processor and memory can be included in a computer device.

[0082] An exemplary embodiment of another aspect of the present invention also provides a computer-readable storage medium storing a computer program. The computer-readable storage medium stores a computer program that, when executed by a processor, causes the processor to execute the cluster wellbore anti-collision design method according to the present invention. The computer-readable recording medium is any data storage device capable of storing data readable by a computer system. Examples of computer-readable recording media include: read-only memory, random access memory, read-only optical disk, magnetic tape, floppy disk, optical data storage device, and carrier waves (such as data transmission via the Internet through wired or wireless transmission paths).

[0083] An exemplary embodiment of another aspect of the present invention also provides a computer device. The computer device includes a processor and a memory. The memory stores a computer program. The computer program is executed by the processor, causing the processor to execute the computer program of the cluster wellbore anti-collision design method according to the present invention.

[0084] To better understand the present invention, the following description, in conjunction with the accompanying drawings and examples, further clarifies the content of the present invention, but the content of the present invention is not limited to the following embodiments.

[0085] Step 1: Using the target wellhead as the center, divide the anti-collision space into a grid of cells. The cell length can be set from 0.5m to 1m. In this embodiment, the cell length is set to 1m.

[0086] Establish a confirmed list and a searchable list to store spatial nodes, limiting the range of values ​​for well inclination, dogleg angle, and target azimuth. Input the wellhead, elevation, and trajectory information of adjacent wells, accumulate the collision avoidance safety distance to the corresponding depth position of adjacent wells, complete obstacle construction, and add the completed obstacle construction cells to the confirmed list. Determine the center coordinates (x, y, y) of all nodes based on their positions in coordinate space. i y i z i To keep the calculation process simple and clear, let the wellhead coordinates (starting point) be (0,0,0) and the target coordinates (end point) be (1,5,-5), with a search cost D = 1.

[0087] Figure 7 The example collision avoidance space diagram of this exemplary embodiment is shown. It should be noted that, Figure 7In the diagram, A represents the wellhead, B represents the target point, C represents the previous trajectory node, D represents the current node, the black part represents nodes that have already been searched, the mesh part represents the anti-collision obstacle zone, and the numbers 1 to 6 represent adjacent nodes waiting to be searched.

[0088] This invention uses collision avoidance safety distance for calculation, and the trajectory design does not need to consider the influence of measurement error ellipsoid, and uses spatial straight line segments for trajectory search.

[0089] Step 2: Calculate the F value of the current spatial node using the cost function, select the point with the smaller F value as the new trajectory node, and add the remaining nodes to the confirmed list.

[0090] The specific calculation process for the F-value is as follows:

[0091] The value of F at the starting point is: F = G + H = 0 + [|1 - 0| + |5 - 0| + |(-5) - 0|] = 11

[0092] The current node's value F is: F = [1 + 2√2] + [|1 - 0| + |5 - 2| + |(-5) - (-3)|] = 7 + 2√2

[0093] Calculate the F-values ​​of the current node's neighboring nodes:

[0094] Node 1 and Node 6: The previous trajectory node was searched and is now in the retrieved list;

[0095] Node 2: F = [3 + √2] + [|1 - 0| + |5 - 3| + |(-5) - (-2)|] = 9 + √2 ≈ 10.4;

[0096] Node 3: F = [2 + 2√2] + [|1 - 0| + |5 - 3| + |(-5) - (-3)|] = 7 + 2√2 ≈ 9.8;

[0097] Node 4: F = [1 + 3√2] + [|1 - 0| + |5 - 3| + |(-5) - (-4)|] = 5 + 3√2 ≈ 9.2;

[0098] Node 5: F = [2 + 2√2] + [|1 - 0| + |5 - 2| + |(-5) - (-4)|] = 7 + 2√2 ≈ 9.8.

[0099] Step 3: Determine whether the calculated F value is the minimum value. If yes, keep the node as a trajectory node and move the node from the search list to the confirmed list. If no, put the node into the confirmed list.

[0100] Calculations revealed that node 4 had the lowest computational cost, so node 4 was selected as the new trajectory node, and all neighboring nodes were added to the confirmed list, thus completing the current node search.

[0101] If node 4 becomes unavailable, and the costs of nodes 3 and 5 are the same, to ensure the final curve is the optimal curve, the costs of all neighbors of nodes 3 and 5 are calculated, and the node with the lowest cost is selected to guide the selection of the current node. Since all neighbors of node 5 are in the confirmed list, and neighbor costs cannot be compared, node 3 is selected as the new trajectory node.

[0102] Figure 8 The diagram illustrates the case where the minimum cost node is unavailable in this exemplary embodiment. It should be noted that... Figure 8 In the diagram, A represents the current node, the black part represents nodes that have been searched, the gray part represents nodes that are unavailable, and the numbers 1 to 5 represent nodes to be judged.

[0103] Step 4: Determine if the new trajectory node is a target point. If not, continue to determine if there are available continuous nodes in the search list. If yes, repeat step 2. If no, indicate that there is no solution and introduce a manual strategy to modify the depth of the tilting point. If yes, complete the search, output all trajectory nodes, and obtain the nodes of the preliminary designed trajectory.

[0104] Figure 9 The diagram shows the trajectory node path output after retrieval using this exemplary embodiment. It should be noted that... Figure 9 In the diagram, A represents the wellhead, B represents the target point, and the black area represents the trajectory node.

[0105] Step 5: Optimize the output trajectory curve using the circular arc optimization method, transforming the node trajectory into a smooth curve and then outputting it.

[0106] Specifically, the calculation steps of the circular arc optimization method include:

[0107] ① Perform circular arc fitting on the nodes of continuous non-collinear trajectories, and let the center coordinates of the corresponding node squares be M.

[0108] ② All trajectory nodes should ideally lie on a single plane, and the plane equation can be expressed as:

[0109] ax + by + cz = 1 (1)

[0110] Its corresponding matrix form is:

[0111] MA = L1 (2)

[0112]

[0113] Where A is the coefficient matrix:

[0114] A = (a, b, c) T (4)

[0115] L1 is a constant matrix:

[0116] L1 = (1, 1, ..., 1) T (5)

[0117] ③ Calculate the normal vector of the fitted plane using the least squares method:

[0118]

[0119] ④ Since the perpendicular bisector of the line connecting any two points on the arc passes through the center of the circle, then:

[0120]

[0121] Vector of the line connecting any two points on an arc:

[0122]

[0123] The vector of the line connecting the center of the circle and its midpoint is:

[0124]

[0125] Summarized as follows:

[0126]

[0127] Introduction,

[0128]

[0129] C=(x 圆 y 圆 , z 圆 ) T (12)

[0130]

[0131] Combining equations (11), (12), and (13), we obtain:

[0132] BC = L2 (14)

[0133] The unknown is x 圆 y 圆 z 圆 There are 3 terms, resulting in a total of n-1 equations. Since these are overdetermined equations, the transformation to well-determined equations is as follows:

[0134] B T BC = B T L2 (15)

[0135] And the center of the circle lies within the pre-defined plane:

[0136]

[0137] Combining equations (15) and (16), we get:

[0138]

[0139] The coordinates of the center of the circle are obtained:

[0140]

[0141] Obtain the radius of the corresponding circle:

[0142]

[0143] And the corresponding curvature:

[0144]

[0145] ⑤ Introduce constraints, including dogleg limitation, well inclination limitation, and target orientation limitation.

[0146] The dogleg value is equal to the curvature of the corresponding well section, thus limiting the dogleg of the build-up section.

[0147] K≤k max , where k max This represents the maximum degree of sycophancy.

[0148] According to the formula for the coordinates of the center of the circle in equation (18), let the coordinates of the center O be (x... 圆 y 圆 , z 圆 The last point M of the inclined section is (x m y m , z m Then we get:

[0149]

[0150] It can be seen that the vertical upward unit vector is (0, 0, 1).

[0151] The dot product is:

[0152]

[0153] Substituting the coordinates, we get:

[0154]

[0155] Solving equation (22) yields:

[0156]

[0157] The final well inclination angle is obtained as follows:

[0158]

[0159] Among them, the well inclination angle θ should be between 0 and θ max between.

[0160] Figure 10 The diagram shows the well inclination section constraint, where θ represents the well inclination angle; α represents the complementary angle of the well inclination angle; ρ represents the radius of curvature of the corresponding well section; y represents the vertical coordinate axis; and x represents the horizontal coordinate axis.

[0161] Since the orientation is a vector on a horizontal plane, only the orientation angle limitation within a two-dimensional plane is considered.

[0162] Let the unit vector of true north in the plane be The target point coordinates are T(a, b), and the center coordinates of the node preceding the target point are P. n-1 (x n-1 y n-1 ).

[0163] The vector is then:

[0164]

[0165] vector unit vector of true north The dot product is represented as:

[0166]

[0167] Substitute coordinates to calculate:

[0168]

[0169] Solving for:

[0170]

[0171] The target azimuth angle δ should be calculated to satisfy δ0+2≤δ≤δ0+2, where δ0 is the preset target azimuth angle.

[0172] Figure 11 The target entry azimuth constraint diagram is shown, where δ represents the target entry azimuth angle; δ0 represents the preset target entry azimuth angle; Represents the unit vector in the due north direction; T represents the target point with coordinates (a, b); P n-1 This represents the node preceding the target point, with coordinates (x...). n-1 y n-1 ).

[0173] ⑥ Optimize and iterate.

[0174] If the preliminary calculation results cannot meet the requirements for dogleg degree, well inclination, and target orientation, then jump to step ② iterate M=M' and recalculate until the requirements are met. At the same time, output the collinear feature point trajectory segment (vertical well segment) and the optimized circular arc segment (inclination segment), which is the final trajectory. If there is no solution (it is impossible to optimize a curve that meets the requirements for dogleg degree, well inclination, and target orientation), then jump to step four again.

[0175] Where M' is:

[0176]

[0177] when When k decreases, δ increases. When k increases, δ decreases.

[0178] Figure 12 The optimized trajectory diagram is shown. It should be noted that... Figure 12 In the diagram, A represents the wellhead, B represents the target point, the black part represents the trajectory node, and the curved part represents the optimized trajectory.

[0179] Although the present invention has been described above in conjunction with exemplary embodiments and accompanying drawings, those skilled in the art should understand that various modifications can be made to the above embodiments without departing from the spirit and scope of the claims.

Claims

1. A method for designing anti-collision features in cluster wellbore configurations, characterized in that: The wellbore anti-collision design method includes the following steps: S1. Using the target wellhead as the center, grid the anti-collision area and determine the center coordinates (x, y) of all nodes. i y i , z i ); S2. Complete obstacle construction, and store the obstacle area marker nodes in the confirmed list, and store the remaining grid nodes in the search list; S3. Determine the range of values ​​for well inclination, dogleg, and target azimuth; S4. Determine the depth of the kick-in point, save the wellhead to the confirmed list, and set the node where the kick-in point is located as the new trajectory node; S5. Starting from the point of inclination, search and determine whether all neighboring nodes around the current node are stored in the search list. If not, skip the neighboring node. If yes, calculate the cost F of the neighboring node. S6. Select the neighboring node with the smallest F value in step S5 as the new trajectory node and put the node into the trajectory node list. Store the remaining neighboring nodes in the confirmed list. S7. Determine if the new trajectory node is a target point. If not, continue to determine if there are available continuous nodes in the search list. If yes, repeat step S6. If no, indicate no solution and modify the depth of the incline point. If yes, complete the search, output all trajectory nodes, and obtain the nodes of the preliminary design trajectory. S8. Starting from the wellhead node, check whether three adjacent trajectory nodes in the trajectory node list are collinear. If so, delete the middle trajectory node until all trajectory nodes are no longer collinear. S9. Using dogleg degree, well inclination, azimuth and minimum length of stable inclination segment as constraints, optimize the node trajectory in the trajectory node list into a smooth curve and output the optimized curve trajectory. The length of the unit grid in step S1 is set to 0.5m to 1m; The determination of the kick-in point depth in step S4 includes calculating from the minimum kick-in point depth. If there is no solution, the kick-in point depth is increased by 5 to 20 m. The kick-in point depth of subsequent designed wells differs from that of the designed wells by more than 20 m. The kick-in point depth must be greater than the preset depth of the previous casing layer by 30 to 50 m.

2. The wellbore anti-collision design method for cluster well groups according to claim 1, characterized in that, Step S2 includes accumulating the anti-collision safety distance to the corresponding depth position of the adjacent well to complete the obstacle construction.

3. The wellbore anti-collision design method for cluster well groups according to claim 1, characterized in that, The calculation method for the cost F in step S5 is as follows: F = G + H Where F is the total path cost of the current node; G is the cost used to move from the starting point to the current position, with D being the unit cost of movement along the coordinate axis and D being the unit cost of movement diagonally in the plane. The cost per unit movement when moving diagonally in space is H represents the theoretical minimum cost of moving from the current point to the target point along the coordinate axis without considering obstacles, and the cost per unit movement is D.

4. The wellbore anti-collision design method for cluster well groups according to claim 1, characterized in that, In step S8, the collinearity of three adjacent trajectory nodes is determined by whether the vector product of the original node and the trajectory node is 0. This includes setting the center coordinates of three consecutive trajectory nodes as (x0, y0, z0), (x1, y1, z1), and (x2, y2, z2), forming two vectors a(x1-x0, y1-y0, z1-z0) and b(x2-x0, y2-y0, z2-z0). If c = ab = |a||b|sinθ = 0, where a and b are vectors, c is the vector product, and θ is the angle between vectors a and b, then the three nodes are collinear; or if there exists λ such that a = λb, then the three nodes are collinear.

5. The wellbore anti-collision design method for cluster well groups according to claim 1, characterized in that, In step S9, the node trajectory is optimized into a smooth curve using the circular arc optimization method.

6. A wellbore anti-collision design system for cluster well groups, characterized in that, The system is used to implement the wellbore anti-collision design method for cluster well groups as described in any one of claims 1 to 5, and includes a grid construction module, a confirmed list, a search list, a trajectory node list, a first parameter determination module, a second parameter determination module, a search module, a selection module, a target point judgment module, a collinearity judgment module, and a trajectory optimization module, wherein, The mesh construction module is used to mesh the anti-collision area with the target wellhead as the center, complete the construction of anti-collision barriers, and output the coordinates of the center positions of all nodes (x, y, y). i y i , z i ); The confirmed list stores nodes that have been confirmed as target points, obstacle zone markers, and nodes that have been searched but not selected as trajectory nodes. The search list stores nodes in the spatial grid that have not been marked or searched. Initially, the search list contains all nodes in the spatial grid. The trajectory node list is used to store wellhead nodes and nodes selected as new trajectory nodes during the search process. The search is completed when the last target point is added to the trajectory node list. The first parameter determination module is used to determine the range of values ​​for well inclination, dogleg, and target azimuth. The second parameter determination module is used to determine the depth of the inclined point; The search module is connected to the mesh building module. It is used to start from the tilting point and search to determine whether all neighboring nodes around the current node are stored in the search list. If not, the neighboring node is skipped. If not, the cost value F of the neighboring node is calculated. The selection module is connected to the search module and is used to select the neighboring node with the smallest F value as the new trajectory node, while the remaining neighboring nodes are stored in the confirmed list. The target point judgment module is connected to the selection module and includes a first judgment submodule and a second judgment submodule. The first judgment submodule is configured to judge whether a new trajectory node is a target point. If the judgment is negative, it enters the second judgment submodule to complete further judgment. If the judgment is positive, it completes the search, outputs a list of trajectory nodes, and obtains the nodes of the preliminary design trajectory. The second judgment submodule is configured to determine whether the search list contains available continuous nodes. If yes, it returns to the selection module to select a new trajectory node again. If no, it prompts that there is no solution and returns to the second parameter determination module to modify the depth of the slope. The collinearity judgment module is connected to the first judgment submodule. It is used to check whether three adjacent trajectory nodes in the trajectory node list are collinear, starting from the wellhead node. If so, the middle trajectory node is deleted until all trajectory nodes are no longer collinear. The trajectory optimization module is connected to the collinearity judgment module and the first parameter determination module, respectively. It is used to optimize the node trajectory into a smooth curve with constraints such as dogleg degree, well inclination, azimuth and minimum length of stable inclination segment, and output the optimized curve trajectory.

7. A computer device, characterized in that, The device includes: processor; The memory stores a computer program that, when executed by a processor, implements the wellbore anti-collision design method for cluster well groups as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the wellbore anti-collision design method for cluster well groups as described in any one of claims 1 to 5.

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