A drilling trajectory autonomous decision-making method and system based on dynamic obstacle perception

Abstract

The application discloses a kind of based on dynamic obstacle perception's well trajectory autonomous decision-making method and system, in which the trajectory autonomous decision-making method includes: obtaining preset drilling trajectory;Real-time detection unknown obstacle to obtain obstacle parameter information;Based on the real-time position of drill bit and the target position of the target position apart from preset distance each corresponding drill bit attitude obtains obstacle tolerance zone;When the unknown obstacle interfering with preset drilling trajectory is detected, whether there is available path based on obstacle parameter information and the obstacle tolerance zone corresponding to current position is judged;There is available path, and preset drilling trajectory is updated based on available path;There is no available path, and target position and obstacle tolerance zone are updated by increasing preset distance, and the updated obstacle tolerance zone is returned to the step of judging whether there is available path again.The scheme can respond to small unknown obstacles on-line, automatically and quickly, and make local optimal decision, which significantly improves the real-time and efficiency of well trajectory decision-making.

Description

Technical Field

[0001] This invention relates to the field of geological drilling technology, specifically to drilling operation efficiency and intelligent optimization through autonomous decision-making on drilling trajectories. Background Technology

[0002] The heterogeneity and anisotropy of underground rock strata are extremely significant. During geological drilling, especially in oil and gas exploration and development, the drilling trajectory inevitably traverses various geological obstacles such as faults, folds, fracture zones, abrupt lithological interfaces, hard nodules, and abnormal pressure systems. These obstacles are randomly distributed in space, varying in shape and scale, ranging from regional faults extending for kilometers to flint nodules or tiny karst caves only a few meters in diameter, collectively posing a severe challenge to drilling operations.

[0003] In current technological practices, drilling trajectory planning heavily relies on geophysical data acquired before drilling, especially 3D seismic data. Engineers interpret the seismic data to construct geological models, thereby identifying large-scale geological obstacles that can be identified at seismic resolution, and designing a pre-planned drilling trajectory to avoid these known risks. However, when encountering unforeseen small obstacles during actual drilling, current decision-making processes typically require halting drilling operations. On-site engineers must compare and analyze real-time data with the geological model, manually assess the nature and risk of the obstacle, calculate multiple possible bypass paths, comprehensively evaluate and select the optimal new trajectory scheme, and then instruct the drilling rig to execute it.

[0004] In existing technological models, the entire process relies heavily on the experience and judgment of engineers, and is an offline, discontinuous decision-making loop. This decision-making process is lagging and lengthy, severely limiting operational efficiency. Furthermore, the computational complexity of obstacle avoidance path selection further increases decision-making time. The inefficiency is particularly pronounced when dealing with a massive number of randomly distributed small obstacles, failing to meet the real-time, continuous, and autonomous requirements of modern intelligent drilling. Summary of the Invention

[0005] This invention provides a method and system for autonomous decision-making on drilling trajectories based on dynamic obstacle perception. It addresses the contradiction between preset trajectories and the uncertainty of the underground environment, and solves the problems of decision lag, operation interruption, and low efficiency caused by the inability to respond to undetected small obstacles in real time and automatically in existing drilling trajectory planning and execution.

[0006] The technical solution is as follows:

[0007] In a first aspect, embodiments of the present invention provide an autonomous decision-making method for drilling trajectory based on dynamic obstacle perception, comprising the following steps:

[0008] Obtain the preset drilling trajectory planned based on known obstacles;

[0009] Drilling is performed along a preset drilling trajectory, and unknown obstacles in the direction of the drill bit's advance are detected in real time to obtain obstacle parameter information;

[0010] Based on the real-time position of the drill bit and the drill bit posture corresponding to the target position at a preset distance from the real-time position along the preset drilling trajectory, the obstacle tolerance zone corresponding to the real-time position is obtained. The obstacle tolerance zone represents the set of all paths from the real-time position with the corresponding drill bit posture to the target position with the corresponding drill bit posture and all satisfying the maximum dogleg constraint.

[0011] When an unknown obstacle interfering with the preset drilling trajectory is detected, the existence of a usable path is determined based on the obstacle parameter information and the obstacle tolerance zone corresponding to the current position.

[0012] If an available path exists, update the preset drilling trajectory between the current drill bit position and the corresponding target position based on the available path;

[0013] If no available path exists, increase the preset distance to update the target position and obstacle tolerance zone corresponding to the current position, and return to the step of determining whether an available path exists with the updated obstacle tolerance zone corresponding to the current position.

[0014] As a preferred embodiment, the step of obtaining the obstacle tolerance zone corresponding to the real-time position based on the drill bit's real-time position and the drill bit attitude corresponding to the target position at a preset distance from the real-time position along the preset drilling trajectory, further includes:

[0015] Obtain the stress conditions and safe upper limit of the drill pipe;

[0016] The obstacle tolerance zone is adjusted based on the stress conditions of the drill pipe and the upper limit of the stress safety.

[0017] As a preferred embodiment, updating the preset drilling trajectory between the current drill bit position and the corresponding target position based on the available path includes:

[0018] The comprehensive evaluation score corresponding to each available path is obtained based on multiple optimization objectives, and the available path with the highest comprehensive evaluation score is determined as the optimal path. The optimization objectives include path length, smoothness and deviation.

[0019] The preset drilling trajectory between the current position of the drill bit and the corresponding target position is updated based on the optimal path.

[0020] As a preferred embodiment, the step of obtaining the comprehensive evaluation score corresponding to each available path based on multiple optimization objectives, and determining the available path with the highest comprehensive evaluation score as the optimal path, further includes:

[0021] Obtain the drill pipe force increment corresponding to the optimal path. If the drill pipe force increment corresponding to the optimal path exceeds the preset increment threshold range, adjust the preset distance to update the target position and obstacle tolerance zone corresponding to the current position, and return to the step of determining whether there is a usable path with the updated obstacle tolerance zone corresponding to the current position.

[0022] As a preferred option, the trajectory autonomous decision-making method also includes:

[0023] Obtain the stress conditions and safe upper limit of the drill pipe;

[0024] The preset incremental threshold range is adjusted based on the stress condition of the drill pipe and the upper limit of the stress safety.

[0025] As a preferred embodiment, adjusting the preset incremental threshold range based on the drill pipe stress condition and the upper limit of stress safety includes:

[0026] Obtain the remaining drilling distance along the preset drilling trajectory from the real-time position;

[0027] The preset incremental threshold range is adjusted based on the remaining drilling distance along the preset drilling trajectory, the stress condition of the drill rod, and the upper limit of the stress safety based on the real-time position.

[0028] As a preferred embodiment, the preset distance is greater than the maximum detection range of the drill bit and changes dynamically based on the stress condition of the drill rod and the upper limit of the stress safety limit.

[0029] As a preferred embodiment, increasing the preset distance to update the target position and obstacle tolerance zone corresponding to the current position includes:

[0030] The increment of the preset distance increases sequentially with each judgment result indicating that no available path exists.

[0031] As a preferred option, the trajectory autonomous decision-making method also includes:

[0032] The decision-making process is halted when the number of times the determination of whether a usable path exists for the same unknown obstacle exceeds a preset number, in order to await manual intervention.

[0033] Secondly, embodiments of the present invention provide an autonomous decision-making system for drilling trajectories based on dynamic obstacle perception, including a trajectory acquisition unit, an obstacle detection unit, a tolerance zone calculation unit, and a trajectory decision-making unit;

[0034] The trajectory acquisition unit acquires a preset drilling trajectory planned based on known obstacles;

[0035] The obstacle detection unit acquires obstacle parameter information of unknown obstacles in the direction of drill bit advance in real time during the drilling process along the preset drilling trajectory.

[0036] The tolerance zone calculation unit obtains the obstacle tolerance zone corresponding to the real-time position of the drill bit and the drill bit posture corresponding to the target position at a preset distance from the real-time position along the preset drilling trajectory. The obstacle tolerance zone represents the set of all paths from the real-time position with the corresponding drill bit posture to the target position with the corresponding drill bit posture and all satisfying the maximum dogleg constraint.

[0037] When the trajectory decision unit detects an unknown obstacle that interferes with the preset drilling trajectory, it determines whether there is a usable path based on the obstacle parameter information and the obstacle tolerance zone corresponding to the current position. If there is a usable path, it updates the preset drilling trajectory between the current position of the drill bit and the corresponding target position based on the usable path. If there is no usable path, it increases the preset distance to update the target position and obstacle tolerance zone corresponding to the current position, and then re-determines whether there is a usable path based on the updated obstacle tolerance zone corresponding to the current position.

[0038] Thirdly, embodiments of the present invention provide an electronic device, including a processor and a memory; the processor is connected to the memory; the memory is used to store executable program code; the processor reads the executable program code stored in the memory to run a program corresponding to the executable program code, so as to perform the steps described in the first aspect of the above embodiments.

[0039] Fourthly, embodiments of the present invention provide a computer storage medium storing a plurality of instructions adapted for loading by a processor and executing the steps described in the first aspect of the above embodiments.

[0040] The beneficial effects of the technical solutions provided by some embodiments of the present invention include at least the following:

[0041] This solution represents a fundamental shift from the traditional drilling model, which relies on static blueprints and manual intervention, to an intelligent model based on real-time perception, dynamic modeling, and autonomous optimization. By introducing an "obstacle tolerance zone," the physical constraints of drilling are transformed into a computer-processable and visualized three-dimensional safety corridor, providing a precise mathematical space for drill bit movement planning in unknown environments. Employing an incremental decision-making logic, using dynamic target points on a pre-defined trajectory as navigation objectives, and employing a gradient search strategy from near to far, it prioritizes local fine-tuning solutions that minimize disruption to the original plan when facing unknown obstacles. This decomposes the complex path planning problem into a series of "existence judgment" sub-problems performed within the "obstacle tolerance zone" corresponding to the target point, significantly simplifying computational complexity. Thus, while ensuring wellbore quality and equipment safety, it automates obstacle avoidance decisions with sub-second response times, significantly improving the continuity and efficiency of drilling operations and freeing engineers from frequent, low-risk micro-operations.

[0042] This solution corrects the tolerance zone through a real-time mechanical model, proactively preventing stuck drill and equipment overload, significantly improving the safety of decision-making, and enabling the size and shape of the obstacle tolerance zone to dynamically and accurately reflect the obstacle avoidance capability of the current downhole drilling tool.

[0043] This scheme comprehensively weighs path length, smoothness, and deviation, and introduces a reverse verification mechanism to ensure that the selected path is a globally better solution in terms of geometry and mechanics, thus achieving a balance between trajectory disturbance and safety margin.

[0044] This enables the incremental threshold range for judging the merits of a drilling path to be dynamically adjusted based on the remaining capacity of the equipment and subsequent drilling tasks, thus achieving intelligent resource planning throughout the entire wellbore cycle.

[0045] This solution enables the initial preset distance to dynamically change based on real-time mechanical conditions and predicted obstacles ahead, achieving forward-looking intelligent decision-making.

[0046] This scheme adopts an adaptive incremental strategy to intelligently accelerate the cyclic decision-making process, significantly reduce the number of invalid loops, improve decision-making efficiency, and at the same time avoid causing unnecessary excessive disturbance to the trajectory.

[0047] This solution establishes a human intervention mechanism, clarifies the system's capability boundaries, ensures ultimate safety in complex situations, achieves human-machine collaboration and controllable risks, and guarantees the safe and effective implementation of this solution in harsh industrial environments. Attached Figure Description

[0048] 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 drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a flowchart illustrating an autonomous decision-making method for drilling trajectory based on dynamic obstacle perception, provided in an embodiment of the present invention.

[0050] Figure 2 This is an additional flowchart illustrating an autonomous decision-making method for drilling trajectory based on dynamic obstacle perception provided in an embodiment of the present invention.

[0051] Figure 3 This is a schematic diagram illustrating the unfolded process of step 108A in an autonomous decision-making method for drilling trajectory based on dynamic obstacle perception provided in an embodiment of the present invention.

[0052] Figure 4 This is a schematic diagram of the structure of an autonomous decision-making system for drilling trajectory based on dynamic obstacle perception, provided in an embodiment of the present invention.

[0053] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0054] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0055] The terms "first," "second," "third," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0056] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the described elements without departing from the scope of the invention. Various processes or components may be appropriately omitted, substituted, or added to the various examples. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.

[0057] In the initial design phase of drilling projects, underground sensing data primarily relies on methods such as seismic exploration. The sparsity and low resolution of this data lead to uncertainties in the constructed underground models, which are far less precise than the high-precision environmental information obtained through direct measurements in surface engineering. Therefore, the pre-defined drilling trajectory generated based on low-precision seismic data can only ensure the avoidance of large geological obstacles that are identifiable on a macroscopic scale and have high certainty, such as regional large faults, salt deposits, and karst caves, thus ensuring the macroscopic accuracy of the wellbore trajectory. However, for numerous, randomly distributed, and small-scale obstacles—such as isolated nodules, micro-faults, and localized fracture zones—precise prediction before drilling is impossible; they must be detected through high-frequency, close-range detection during drilling.

[0058] Traditional drilling suffers from reliance on manual labor, slow response, and inefficient decision-making when encountering unforeseen minor obstacles, leading to frequent drilling interruptions and severely limiting operational efficiency. Therefore, this application is submitted.

[0059] Reference Figure 1 As shown, Figure 1A flowchart illustrating an autonomous drilling trajectory decision-making method based on dynamic obstacle perception, provided as an embodiment of the present invention, may include at least the following steps:

[0060] Step 102: Obtain the preset drilling trajectory planned based on known obstacles;

[0061] Step 104: Drill along the preset drilling trajectory and detect unknown obstacles in the direction of the drill bit's advance in real time to obtain obstacle parameter information;

[0062] Step 106: Based on the real-time position of the drill bit and the drill bit posture corresponding to the target position at a preset distance from the real-time position along the preset drilling trajectory, obtain the obstacle tolerance zone corresponding to the real-time position. The obstacle tolerance zone represents the set of all paths from the real-time position with the corresponding drill bit posture to the target position with the corresponding drill bit posture and all satisfying the maximum dogleg degree constraint.

[0063] Step 108: When an unknown obstacle interfering with the preset drilling trajectory is detected, determine whether there is a usable path based on the obstacle parameter information and the obstacle tolerance zone corresponding to the current position;

[0064] Step 108A: If an available path exists, update the preset drilling trajectory between the current drill bit position and the corresponding target position based on the available path;

[0065] Step 108B: If no available path exists, increase the preset distance to update the target position and obstacle tolerance zone corresponding to the current position, and return to step 108 to determine if a available path exists.

[0066] Illustratively, known obstacles are primarily obtained through regional surface exploration techniques used in the pre-drilling phase. The core technology is seismic exploration, which involves artificially generating seismic waves and receiving reflected waves from different subsurface rock interfaces. Computer processing and interpretation then construct a geological framework spanning several thousand meters underground. This technology yields large obstacles, including the axial sections of anticlines / synclines, salt domes or mud diapirs, unconformities, large buried hills, karst cave systems, and existing oil and gas reservoir boundaries. Their spatial location, basic shape, and scale provide a macroscopic, though relatively low-resolution, basis for drilling design. When planning the pre-set drilling trajectory based on this information, engineers adhere to the principle of "avoidance as the primary approach, controllable passage." For obstacles with extremely high risks, trajectory planning employs proactive avoidance strategies, ensuring a sufficient safe distance between the path and the obstacle from the initial design stage. For relatively stable obstacles that must be traversed, trajectory design carefully selects passage points and angles to keep risks within acceptable limits. The essence of the pre-set trajectory is a safe and efficient baseline based on macroscopic, prior information.

[0067] Real-time detection of unknown obstacles ahead of the drill bit primarily relies on logging-while-drilling (LOD) and measurement-while-drilling (MSD) technologies. By integrating sensors into the drill collar close to the drill bit, measurements are taken synchronously during drilling, and the data is transmitted to the surface in real time. LWD detection technologies mainly include LWD resistivity, LWD acoustic imaging, LWD gamma-ray imaging, and caliper measurement. Among these, azimuth resistivity imaging and deep azimuth resistivity techniques can detect high-resolution anisotropic variations in formation resistivity around the drill bit and even within tens of meters ahead. Furthermore, LWD seismic technology uses drill bit vibrations as a seismic source, enabling high-resolution predictions up to hundreds of meters ahead of the drill bit. These technologies identify microscopic geological bodies that are indistinguishable by seismic exploration, mainly including small faults, microfracture zones, interlayers, chert nodules, small cavities, and local abrupt changes in formation attitude—small obstacles in themselves. When these small obstacles are detected, the acquired obstacle parameter information is a multi-attribute dataset, including geometric information such as the obstacle's orientation, distance from the drill bit, apparent thickness or size, as well as rock mechanical properties used to determine the obstacle's physical properties. This obstacle parameter information provides data support for subsequent real-time decision-making.

[0068] Dogleg is a term in oil drilling engineering, referring to the angular change of the wellbore axis between two points in three-dimensional space. It is also known as the rate of change of total angle or wellbore curvature, comprehensively reflecting the changes in well inclination and azimuth. The maximum dogleg constraint quantitatively describes the degree of drastic change in the wellbore trajectory direction within a unit well section, with standard units such as degrees per 30 meters or degrees per 100 meters. During the drilling engineering design phase, engineers set a maximum dogleg limit that must be adhered to throughout the entire well section, based on factors such as the drill pipe's steel grade and specifications, the expected well depth, and formation characteristics.

[0069] Interpretive methods in drilling engineering transform the physical constraints (maximum dogleg) of drilling into a geometric model that can be processed and visualized by a computer. Based on differential geometry and numerical computation, the pre-defined trajectory and the target trajectory are first discretized in three-dimensional space. A local coordinate system (composed of tangent vector, normal vector, and binormal vector) is established at each discrete point on the trajectory using a Frenet frame, providing a reference frame to describe the possible directions of drill bit movement. The algorithm then transforms the maximum dogleg constraint into a continuous curvature model. Based on this, motion planning algorithms such as probabilistic route graphs and fast exploratory random trees are used to perform large-scale, guided random sampling from the vast state space spanned by the drill bit's attitude at the current and target positions, generating countless potential paths. For each generated path, its dogleg constraint is verified, and all qualified path points are recorded. The set of all qualified paths constitutes a continuous region in three-dimensional space, and the boundary of this region is the boundary of the obstacle tolerance zone. To make it more practical in engineering, this point cloud set can be wrapped and simplified using a 3D convex hull algorithm or an Alpha-Shape algorithm, ultimately generating a smooth 3D model for interferometry detection.

[0070] After obtaining obstacle parameter information and the calculated 3D model corresponding to the obstacle tolerance zone, the system first determines whether the obstacle's bounding box intersects with the preset drilling trajectory. If they do not intersect, the obstacle can be ignored, and the preset drilling trajectory does not need to be adjusted. If they intersect, the system further determines whether a usable path exists within the obstacle tolerance zone corresponding to the current position. When determining whether a usable path exists, if the obstacle completely blocks the entire tolerance zone, then a usable path certainly does not exist. However, a common situation is that the obstacle partially intersects with the tolerance zone, requiring verification of whether a continuous path exists from the starting point to the ending point, entirely within the tolerance zone, and without any interference with the obstacle model. If the obstacle divides the obstacle tolerance zone into several disconnected parts, and the starting and ending points are located in different isolated regions, then no usable path exists. Conversely, if the starting and ending points are still within the same connected region, then a usable path exists.

[0071] For example, a random sampling algorithm can be used to densely generate a large number of random paths connecting the start and end points within the tolerance zone, and quickly detect whether each path intersects with the obstacle model. Finding even one non-intersecting path proves the existence of a usable path. One usable path is selected to replace the trajectory segment between the current position and the corresponding target position in the preset drilling trajectory, resulting in an updated preset drilling trajectory, and drilling operations continue. Because the judgment process and the path planning process are performed simultaneously, the usable replacement path can be obtained simultaneously with the determination of its existence.

[0072] This solution achieves a significant leap in decision-making efficiency. Unlike traditional techniques that, upon encountering an obstacle, require replanning the entire path from the current position within a vast search space and sifting through numerous entry points, this solution uses points on the trajectory corresponding to a preset distance as definitive entry points, greatly simplifying the decision-making logic. This makes the objective very clear when encountering obstacles, eliminating the need to repeatedly search for the optimal entry point. It simply requires quickly determining whether a dogleg-degree obstacle avoidance path exists under the currently set target constraints. This goal-driven approach concentrates computational resources on solving a smaller-scale feasibility problem, thereby enabling rapid path generation and judgment.

[0073] This approach also avoids significant disruption to the preset drilling trajectory caused by obstacle avoidance maneuvers. It prioritizes near-range obstacle avoidance around target locations determined by a preset distance, quickly returning to the preset drilling trajectory. When no feasible path is determined, the preset distance is gradually increased to generate a new entry point, and a rapid reassessment is performed. This gradient search strategy, which expands the decision-making field of view in exchange for a larger solution space, avoids excessive disruption to the preset drilling trajectory, controllingly sacrificing local efficiency to increase the likelihood of task success. As the preset distance increases, the target location becomes farther from the current location. With increased allowable path length, while maintaining the same upper limit on curvature, the total directional change achievable by the drill bit increases, and its turning process becomes smoother. In drilling operations, a larger target distance allows the drill bit to bypass obstacles with smoother and safer curves, thereby improving the reliability and success rate of autonomous obstacle avoidance. The gradient search strategy also avoids unnecessary consumption of computational resources, reducing decision-making time from minutes in traditional methods to seconds, ensuring the continuity of drilling operations.

[0074] It is easy to understand that the obstacle tolerance zone can be updated in real time at the current location, or it can be updated after an unknown obstacle is detected. By introducing real-time updates to the obstacle tolerance zone, a precise and safe drilling corridor can be continuously maintained under the premise of controllable computational load. Once an unknown obstacle blocking the preset drilling trajectory is detected, judgment and decision-making can be made immediately based on the obstacle tolerance zone at the real-time location, which can further reduce the decision-making response time, thereby improving the continuity and efficiency of drilling operations.

[0075] In addition, since the preset drilling trajectory is usually a smooth curve, the current position and target position do not change much at different times during the drilling operation along the preset drilling trajectory. The obstacle tolerance zone can be updated by predictive optimization algorithm (such as incremental update based on the tolerance zone at the previous time), which can further reduce the computational pressure and simplify the real-time update of the obstacle tolerance zone.

[0076] It should be noted that this solution does not aim for completely unmanned, black-box operation, but rather optimizes trajectories for avoiding unknown obstacles under controllable risk conditions. It can autonomously and quickly handle a large number of routine, low-risk emergencies, thereby freeing engineers from frequent micro-management.

[0077] It is easy to understand that when the drilling operation determines that the obstacle encountered is beyond the scope of a small area or that the required trajectory adjustment is too large, or other complex situations, the automatic decision-making can be actively paused through the division of permissions, triggering manual intervention, and returning the decision-making power to the engineer to make important decisions such as whether to retreat to a safe point for sidetracking or to manually adjust the trajectory.

[0078] The current application scenarios for this solution primarily target operating conditions with controllable risks, such as drilling operations in conventional horizontal wells with relatively homogeneous lithology, stable formation pressure, and simple wellbore structures. These geological environments are highly predictable, and the probability of complex downhole conditions is relatively low, providing favorable practical conditions for granting autonomous trajectory decision-making authority. In the future, with further development of drilling exploration technology and the gradual improvement of detection distance and accuracy, it will also be possible to implement this solution in more complex operating conditions, achieving autonomous trajectory decision-making.

[0079] In one embodiment of the present invention, such as Figure 2 As shown, Figure 2 This is an additional flowchart illustrating an autonomous decision-making method for drilling trajectory based on dynamic obstacle perception provided in an embodiment of the present invention.

[0080] Step 106: Based on the real-time position of the drill bit and the drill bit attitude corresponding to the target position at a preset distance from the real-time position along the preset drilling trajectory, obtain the obstacle tolerance zone corresponding to the real-time position. This step further includes:

[0081] Step 1062: Obtain the stress condition and safe upper limit of the drill pipe.

[0082] Step 1064: Adjust the obstacle tolerance zone based on the stress condition of the drill pipe and the upper limit of the stress safety.

[0083] To illustrate, the forces acting on the drill pipe include the torque required to rotate it and the frictional resistance that must be overcome to move it. As the drill pipe moves through the well, friction occurs. Since dynamic friction is typically less than the maximum static friction, as the drill pipe rotates continuously, the contact between the drill pipe and the wellbore changes from static to dynamic friction, significantly reducing the overall resistance to dragging the drill pipe. The rotation of the drill pipe is powered by the top drive or rotary table, and this rotational power is transmitted throughout the entire drill pipe, including the curved sections. Sufficient torque is required for the drill pipe to rotate, and the curved sections generate additional rotational resistance. The more curved the wellbore, the larger the contact area and normal pressure between the drill pipe and the wellbore, leading to a sharp increase in the torque required to rotate the drill pipe and the friction during tripping in and out of the well. Torque exceeding the capacity of the top drive or rotary table will prevent further rotation; excessive friction will prevent the pressure on the drill bit from being effectively transmitted, reducing the rate of drilling; it will also cause difficulties in tripping in and out of the well, increasing the risk of stuck pipe. Therefore, during the drilling engineering design phase, engineers will set corresponding upper limits for stress safety based on factors such as the steel grade and specifications of the drill pipe, the expected well depth, and formation characteristics.

[0084] Interpretive methods can be used to simulate the actual stress on the drill pipe downhole by constructing real-time friction and torque models. Various parameter data are input into the model, such as real-time wellbore trajectory parameters from measurements while drilling (well depth, inclination angle, azimuth angle), drill pipe parameters (size, weight, stiffness, joint position, etc.), drilling fluid performance parameters (density, rheology), drilling rig equipment parameters (hook load, top drive torque, drilling pressure, rotational speed), and friction coefficient. The model solves the mechanical equilibrium equations based on methods such as finite element analysis, thereby calculating the torque distribution, friction distribution, and stress distribution along the entire drill pipe. For example, the torque model is: Surface torque = Wellhead torque + (Frictional torque between drill string and wellbore) + (Drilling fluid viscous torque); Friction model: Hook load = Drill string suspended weight + (Friction between drilling tools and wellbore) (Drilling fluid buoyancy).

[0085] For example, a tolerance zone scaling factor S (0 < S < 1) can be defined based on the upper limit of the force safety and the current stress condition of the drill pipe. The larger S is, the closer the corrected obstacle tolerance zone is to the original size; the smaller S is, the tighter the corrected obstacle tolerance zone is, in order to avoid further deterioration of the mechanical state. For example, S = scaling control coefficient * (maximum safe torque of the top drive - current actual torque) / maximum safe torque of the top drive, where the current actual torque corresponds to the stress condition of the drill pipe, and the maximum safe torque of the top drive corresponds to the upper limit of the force safety.

[0086] It's easy to understand that changing the size of the obstacle tolerance zone essentially involves sorting all paths that satisfy the dogleg constraint according to the magnitude of their increased friction or torque, and then filtering them out in descending order based on the tolerance zone scaling factor S. The region formed by the set of remaining paths in three-dimensional space is then used as the corrected obstacle tolerance zone. For example, if S=0.8, then the top 20% of paths are filtered out in descending order.

[0087] This embodiment combines the size of the obstacle tolerance zone with the stress conditions of the drill pipe to achieve adaptive obstacle tolerance, so that the size and shape of the obstacle tolerance zone can dynamically and accurately reflect the obstacle avoidance capability of the current downhole drilling tool.

[0088] In one embodiment of the present invention, such as Figure 3 As shown, Figure 3 This is a schematic diagram illustrating the unfolded process of step 108A in an autonomous decision-making method for drilling trajectory based on dynamic obstacle perception provided in an embodiment of the present invention.

[0089] Step 108A, update the preset drilling trajectory between the current drill bit position and the corresponding target position based on the available path, including:

[0090] Step 108A2: Based on multiple optimization objectives, obtain the comprehensive evaluation score corresponding to each available path, and determine the available path with the highest comprehensive evaluation score as the optimal path. The optimization objectives include path length, smoothness and deviation.

[0091] Step 108A4: Update the preset drilling trajectory between the current position of the drill bit and the corresponding target position based on the optimal path.

[0092] Interpretive, based on obstacle parameter information and the obstacle tolerance zone corresponding to the current position, all available paths that meet the requirements are obtained, and multi-objective optimization evaluation is performed on all available paths that meet the requirements. Based on the comprehensive evaluation score, the optimal path is selected from all available paths to update the preset drilling trajectory segment between the current position and the corresponding target position.

[0093] For example, the optimization objectives of a multi-objective optimization evaluation may include, but are not limited to: the total path length; path smoothness, usually measured by the average dogleg score; and path deviation, which is the degree to which the path deviates from the preset drilling trajectory before the update, usually quantified by the size of the area formed between the two paths. After determining the optimization objectives, a cost function is used to calculate the comprehensive evaluation score, such as: Total Cost = W1 × Path Length + W2 × Path Smoothness + W3 × Path Deviation, where W1, W2, and W3 are weighting coefficients that engineers can set according to the importance they place on different optimization objectives.

[0094] This embodiment selects the optimal path from multiple available paths through multi-objective optimization evaluation, rather than blindly selecting one. This approach can minimize the difficulty of the drill pipe passing through while taking into account decision-making efficiency, and also leave room for subsequent obstacle avoidance decisions.

[0095] In one embodiment of the present invention, step 108A2 involves obtaining the comprehensive evaluation score corresponding to each available path based on multiple optimization objectives, and determining the available path with the highest comprehensive evaluation score as the optimal path. This step further includes:

[0096] Obtain the drill pipe force increment corresponding to the optimal path. If the drill pipe force increment corresponding to the optimal path exceeds the preset increment threshold range, adjust the preset distance to update the target position and obstacle tolerance zone corresponding to the current position, and return to the step of determining whether there is a usable path with the updated obstacle tolerance zone corresponding to the current position.

[0097] Explanatoryly, this embodiment, after obtaining the optimal path and before updating the preset drilling trajectory, also uses the optimal path to reverse-verify the rationality of the target position. The optimal path only represents the best solution among all solutions between the current position and the corresponding target position. However, theoretically, as long as the target position is at any position after a certain critical distance from the current position, a corresponding optimal path can be obtained. However, the closer the target position is to the critical position corresponding to that critical distance, the lower the trajectory disturbance caused by updating the preset drilling trajectory with the optimal path is because the adjusted preset drilling trajectory segment is relatively short. But at the same time, the maximum dogleg degree of the optimal path is also relatively large, and the increase in drill pipe force caused by the optimal path will be greater. Conversely, the farther the target position is from the critical position corresponding to that critical distance, the smaller the maximum dogleg degree of the optimal path is, and the smaller the increase in drill pipe force caused by the optimal path is. However, the trajectory disturbance caused by updating the preset drilling trajectory with the optimal path is greater because the adjusted preset drilling trajectory segment is relatively longer. Therefore, it is necessary to adjust unreasonable target positions to achieve a relative balance between the degree of trajectory disturbance and the increase in drill pipe force. This embodiment uses the increase in drill pipe force resulting from the optimal path to reverse-verify the rationality of the target location.

[0098] Specifically, the optimal path can be transformed into a series of dense, discrete nodes. These nodes form a series of short, straight path units, creating an approximate path for the computer to efficiently calculate the mechanical relationships of each tiny path unit. Then, based on the drill pipe's physical parameters and mechanical models such as the large deformation beam-column theory, the drill pipe's shape within the discretized approximate path space is calculated, along with the corresponding contact points and support forces. In this embodiment, the change in torque required to rotate the drill pipe and the change in frictional resistance required to move the drill pipe are used as the increment of force on the drill pipe. For each contact point, Coulomb's law of friction is applied: frictional resistance = contact normal force × friction coefficient, where the friction coefficient characterizes various factors such as drilling fluid lubricity, rock formation properties, and casing condition. The torque is calculated by summing all frictional torques. When the drill pipe rotates, each point in contact with the wellbore generates a frictional torque that opposes rotation. This torque is transmitted upwards and accumulated from each contact point, ultimately resulting in the increased driving torque.

[0099] The explanatory, preset incremental threshold range includes an upper and lower threshold, set by engineers based on experience. If the drill pipe force increment corresponding to the optimal path is within the incremental threshold range, the optimal path is acceptable; conversely, if the drill pipe force increment corresponding to the optimal path is outside the incremental threshold range, the optimal path is unacceptable, and the preset distance needs to be adjusted to update the target position corresponding to the current position. Specifically, when the drill pipe force increment corresponding to the optimal path is greater than the upper threshold, the preset distance should be increased to move the target position further away from the current position; conversely, when the drill pipe force increment corresponding to the optimal path is less than the lower threshold, the preset distance should be decreased to move the target position closer to the current position. The magnitude of the increase or decrease in the preset distance can be determined by the magnitude of the increase or decrease from the upper or lower threshold. After adjusting the preset distance to obtain the new target position, the determination of whether a usable path exists is performed again.

[0100] In another embodiment of the present invention, the rationality of the target location can also be verified by the maximum value of the dogfighting degree of the optimal path. The maximum value of the dogfighting degree corresponding to the optimal path is obtained; if the maximum value of the dogfighting degree corresponding to the optimal path exceeds a preset dogfighting degree threshold range, a preset distance is adjusted to update the target location and obstacle tolerance zone corresponding to the current location, and the updated obstacle tolerance zone corresponding to the current location is returned to the step of determining whether a usable path exists.

[0101] In one embodiment of the present invention, the trajectory autonomous decision-making method further includes:

[0102] Obtain the stress conditions and safe upper limit of the drill pipe;

[0103] The preset incremental threshold range is adjusted based on the stress condition of the drill pipe and the upper limit of the stress safety.

[0104] Explanatoryly, this embodiment introduces a dynamic interval algorithm. Real-time simulations of friction and torque are performed to reflect the stress on the drill pipe. The current mechanical state of the drill pipe is then assessed based on the stress conditions and the upper limit of the safe stress range. Finally, the upper and lower limits of the preset incremental threshold interval are dynamically adjusted according to the current mechanical state. This rationally plans and allocates the obstacle avoidance potential of the entire drilling task, improving the level of intelligent autonomous decision-making.

[0105] For example, if the preset incremental threshold range is (20, 50), in N·m, and the upper limit of the force safety is torque Q0, and at a certain moment the drill pipe is under torque Q1, then (Q0-Q1) / Q0 represents the margin ratio of the current mechanical state. Based on this margin ratio, the preset incremental threshold range is dynamically adjusted through step-wise or linear adjustments. For instance, if the margin ratio is greater than the first step value of 0.66, the incremental threshold range is increased to (30, 60); if the margin ratio is less than the second step value of 0.33, the incremental threshold range is decreased to (10, 40).

[0106] In one embodiment of the present invention, adjusting a preset incremental threshold range based on the stress condition of the drill pipe and the upper limit of the stress safety includes:

[0107] Obtain the remaining drilling distance along the preset drilling trajectory from the real-time position;

[0108] The preset incremental threshold range is adjusted based on the remaining drilling distance along the preset drilling trajectory, the stress condition of the drill pipe, and the upper limit of the stress safety.

[0109] Explained in this embodiment, the drilling progress along the preset drilling trajectory is further incorporated into a dynamic interval algorithm to dynamically adjust the upper and lower limits of the preset incremental threshold interval. The dynamic adjustment of the incremental threshold interval is assisted in optimizing the drilling progress along the preset drilling trajectory. The less progress is made, the lower the incremental threshold interval is adjusted to reserve more tolerance for subsequent, heavier drilling tasks; conversely, the more progress is made, the higher the incremental threshold interval is adjusted to avoid applying overly stringent criteria for judging the rationality of target positions to the remaining limited drilling tasks. This rationally plans and allocates the obstacle avoidance potential of the entire drilling task, improving the intelligence level of autonomous decision-making.

[0110] For example, for every 1% of the drilling progress completed, both the upper and lower thresholds of the incremental threshold range increase by 0.1.

[0111] In another embodiment of the invention, the number of obstacles encountered in the remaining drilling distance can be predicted based on the completed drilling distance and the number of obstacles encountered on the completed drilling trajectory. This predicted number of obstacles encountered in the remaining drilling distance is then used as the basis for adjusting a preset incremental threshold range. For example, the fewer the predicted number of obstacles, the larger the upper and lower thresholds; conversely, the more predicted number of obstacles, the smaller the upper and lower thresholds. This further matches a more reasonable judgment standard (i.e., the incremental threshold range) to the rationality assessment of each target location, rationally plans and allocates the obstacle avoidance potential of the entire drilling task, and improves the intelligence level of autonomous decision-making.

[0112] In one embodiment of the present invention, the preset distance is greater than the maximum detection range of the drill bit, and dynamically changes based on the stress condition of the drill rod and the upper limit of the stress safety limit.

[0113] Interpretive analysis can be performed through real-time friction and torque simulation to continuously calculate and understand the current stress state of the downhole drilling tool. If the current mechanical state is healthy (e.g., torque and friction are well below the safe stress limit), a moderate or slightly smaller initial preset distance is preferred. This is because even if the path requires some curvature, there is sufficient mechanical capacity to safely complete the obstacle avoidance, achieving the goal of successful obstacle avoidance with minimal trajectory disturbance. Conversely, if the mechanical margin is already low, a relatively large initial preset distance should be chosen to reserve enough space for generating a path with better friction and smoother flow. This avoids situations where the selected available path, although geometrically feasible, is mechanically infeasible or high-risk due to an excessively short distance. Therefore, the corresponding initial preset distance is different for each obstacle avoidance decision and increases as the mechanical margin decreases.

[0114] This embodiment dynamically optimizes the preset distance based on the real-time stress state of the drill pipe during drilling operations, ensuring the availability of the obstacle tolerance zone for continuous maintenance, thereby avoiding unnecessary cycles of judgment and improving the intelligence level and practical effect of the solution.

[0115] Furthermore, predictive functionality can be incorporated, dynamically optimizing the preset distance based on predictions of the geological environment ahead. This involves predicting the probability of encountering unknown obstacles based on the number and frequency of such encounters in the application scenario. If the predicted probability of an obstacle is low, a relatively small initial preset distance can be used for the obstacle avoidance decision, prioritizing a smooth trajectory. Conversely, if the predicted probability of an obstacle is high, the initial preset distance should be appropriately increased.

[0116] In one embodiment of the present invention, increasing the preset distance to update the target position and obstacle tolerance zone corresponding to the current position includes:

[0117] The increment of the preset distance increases sequentially with each judgment result indicating that no available path exists.

[0118] Interpretively, because the size, shape, and location of unknown obstacles are all unknown, it is difficult to accurately control the increment of the preset distance when the judgment result is that no usable path exists each time. On the one hand, if the increment is set too small, it may lead to repeated small increases in the preset distance without finding a usable path, resulting in a long period of ineffective loops. On the other hand, if the increment is set too large, although it can quickly find a usable path to complete the obstacle avoidance decision and greatly reduce the number of loops, it is likely to cause the target position to be too far away, causing the decision to excessively disturb the original preset drilling trajectory.

[0119] This embodiment uses a preset distance increment to match the unknown obstacles being dealt with. This not only significantly reduces the number of loops and ensures the efficiency of autonomous decision-making, but also shortens the disturbance length of the original preset drilling trajectory when a usable path is found.

[0120] The preferred increment method is that each subsequent increment is double the previous increment. For example, for any unknown obstacle requiring a decision, if the first judgment results in no available path, the preset distance is increased by a fixed increment of 5m; if the second judgment also results in no available path, the preset distance is increased again by double the fixed increment of 5m, i.e., 10m; the third time by 15m, and so on. For the next unknown obstacle requiring a decision, the initial preset distance increment is reset to a fixed increment of 5m.

[0121] In one embodiment of the present invention, the trajectory autonomous decision-making method further includes:

[0122] The decision-making process is halted when the number of times the determination of whether a usable path exists for the same unknown obstacle exceeds a preset number, in order to await manual intervention.

[0123] Explanatoryly, by increasing the limit on the number of iterations, complex obstacles are identified, and obstacle avoidance decisions are stopped and delegated to human intervention, achieving autonomous decision-making for emergency avoidance and authority allocation. This leverages the advantages of automation technology in rapid response and precise execution while ensuring proper management of overall risks and anomalies, laying the foundation for a highly autonomous intelligent drilling system. This guarantees the safe and effective implementation of this solution in harsh industrial environments.

[0124] The foregoing has described specific embodiments of the invention. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than those shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0125] Please refer to the following. Figure 4 , Figure 4 The diagram shows a schematic of the structure of an autonomous decision-making system for drilling trajectory based on dynamic obstacle perception, provided by an embodiment of the present invention.

[0126] The trajectory autonomous decision-making system 200 includes a trajectory acquisition unit 201, an obstacle detection unit 202, a tolerance zone calculation unit 203, and a trajectory decision-making unit 204;

[0127] The trajectory acquisition unit 201 acquires a preset drilling trajectory planned based on known obstacles;

[0128] The obstacle detection unit 202 acquires obstacle parameter information of unknown obstacles in the direction of drill bit advance in real time during the drilling process along the preset drilling trajectory.

[0129] The tolerance zone calculation unit 203 obtains the obstacle tolerance zone corresponding to the real-time position of the drill bit and the drill bit posture corresponding to the target position at a preset distance from the real-time position along the preset drilling trajectory. The obstacle tolerance zone represents the set of all paths from the real-time position with the corresponding drill bit posture to the target position with the corresponding drill bit posture and all satisfy the maximum dogleg constraint.

[0130] When the trajectory decision unit 204 detects an unknown obstacle that interferes with the preset drilling trajectory, it determines whether there is a usable path based on the obstacle parameter information and the obstacle tolerance zone corresponding to the current position. If there is a usable path, it updates the preset drilling trajectory between the current position of the drill bit and the corresponding target position based on the usable path. If there is no usable path, it increases the preset distance to update the target position and obstacle tolerance zone corresponding to the current position, and re-determines whether there is a usable path based on the updated obstacle tolerance zone corresponding to the current position.

[0131] The various embodiments in this invention are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the trajectory autonomous decision-making system embodiment is basically similar to the trajectory autonomous decision-making method embodiment, so the description is relatively simple; relevant parts can be referred to the description of the trajectory autonomous decision-making method embodiment.

[0132] Please see Figure 5 The diagram shown is a structural schematic of an electronic device provided by an embodiment of the present invention.

[0133] like Figure 5 As shown, the electronic device 500 may include at least one processor 501, at least one network interface 504, a user interface 503, a memory 505, and at least one communication bus 502.

[0134] The communication bus 502 can be used to realize the connection and communication of the above components.

[0135] The user interface 503 may include buttons, and the optional user interface may also include a standard wired interface or a wireless interface.

[0136] The network interface 504 may include, but is not limited to, Bluetooth modules, NFC modules, Wi-Fi modules, etc.

[0137] The processor 501 may include one or more processing cores. The processor 501 connects to various parts within the electronic device 500 using various interfaces and lines. It executes various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 505, and by calling data stored in the memory 505. Optionally, the processor 501 may be implemented using at least one hardware form of DSP, FPGA, or PLC. The processor 501 may integrate one or more of the following: CPU, GPU, and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content to be displayed on the screen; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 501 and may be implemented as a separate chip.

[0138] The memory 505 may include RAM or ROM. Optionally, the memory 505 may include a non-transitory computer-readable medium. The memory 505 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 505 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 505 may also be at least one storage device located remotely from the aforementioned processor 501. As a computer storage medium, the memory 505 may include an operating system, a network communication module, a user interface module, and a trajectory autonomous decision-making application. The processor 501 may be used to call the trajectory autonomous decision-making application stored in the memory 505 and execute the steps of the trajectory autonomous decision-making method mentioned in the foregoing embodiments.

[0139] This invention also provides a computer-readable storage medium storing instructions that, when executed on a computer or processor, cause the computer or processor to perform one or more steps in the above-described trajectory autonomous decision-making method embodiments. If the constituent modules of the above-described electronic device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0140] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., Digital Versatile Discs (DVDs)), or semiconductor media (e.g., Solid State Disks (SSDs)).

[0141] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks. Unless otherwise specified, the technical features of this embodiment and its implementation can be combined arbitrarily.

[0142] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A drilling trajectory autonomous decision-making method based on dynamic obstacle perception, characterized in that, Includes the following steps: Obtain the preset drilling trajectory planned based on known obstacles; Drilling is performed along a preset drilling trajectory, and unknown obstacles in the direction of the drill bit's advance are detected in real time to obtain obstacle parameter information; Based on the real-time position of the drill bit and the drill bit posture corresponding to the target position at a preset distance from the real-time position along the preset drilling trajectory, the obstacle tolerance zone corresponding to the real-time position is obtained. The obstacle tolerance zone represents the set of all paths from the real-time position with the corresponding drill bit posture to the target position with the corresponding drill bit posture and all satisfying the maximum dogleg constraint. Obtain the stress conditions and safe upper limit of the drill pipe; Based on the stress conditions of the drill pipe and the upper limit of the stress safety, the obstacle tolerance zone is modified: the tolerance zone scaling factor is calculated according to the upper limit of the stress safety and the stress conditions of the drill pipe; All paths in the obstacle tolerance zone are sorted according to the magnitude of their respective increases in friction or torque. Some paths are then filtered out in descending order based on the tolerance zone scaling factor. The area formed by the set of remaining paths in three-dimensional space is used as the corrected obstacle tolerance zone. The larger the tolerance zone scaling factor, the closer the corrected obstacle tolerance zone is to the original size. The smaller the tolerance zone scaling factor, the more compact the corrected obstacle tolerance zone is. When an unknown obstacle interfering with the preset drilling trajectory is detected, the existence of a usable path is determined based on the obstacle parameter information and the obstacle tolerance zone corresponding to the current position. If an available path exists, update the preset drilling trajectory between the current drill bit position and the corresponding target position based on the available path; If no available path exists, increase the preset distance to update the target position and obstacle tolerance zone corresponding to the current position, and return to the step of determining whether an available path exists with the updated obstacle tolerance zone corresponding to the current position.

2. The drilling trajectory autonomous decision-making method based on dynamic obstacle perception according to claim 1, characterized in that, The step of updating the preset drilling trajectory between the current drill bit position and the corresponding target position based on the available path includes: The comprehensive evaluation score corresponding to each available path is obtained based on multiple optimization objectives, and the available path with the highest comprehensive evaluation score is determined as the optimal path. The optimization objectives include path length, smoothness and deviation. The preset drilling trajectory between the current position of the drill bit and the corresponding target position is updated based on the optimal path.

3. The drilling trajectory autonomous decision-making method based on dynamic obstacle perception according to claim 2, characterized in that, The process involves obtaining a comprehensive evaluation score for each available path based on multiple optimization objectives, and determining the available path with the highest comprehensive evaluation score as the optimal path. This is followed by: Obtain the drill pipe force increment corresponding to the optimal path. If the drill pipe force increment corresponding to the optimal path exceeds the preset increment threshold range, adjust the preset distance to update the target position and obstacle tolerance zone corresponding to the current position, and return to the step of determining whether there is a usable path with the updated obstacle tolerance zone corresponding to the current position.

4. The drilling trajectory autonomous decision-making method based on dynamic obstacle perception according to claim 3, characterized in that, Also includes: Obtain the stress conditions and safe upper limit of the drill pipe; The preset incremental threshold range is adjusted based on the stress condition of the drill pipe and the upper limit of the stress safety.

5. The drilling trajectory autonomous decision-making method based on dynamic obstacle perception according to claim 4, characterized in that, The adjustment of the preset incremental threshold range based on the drill pipe stress condition and the upper limit of stress safety includes: Obtain the remaining drilling distance along the preset drilling trajectory from the real-time position; The preset incremental threshold range is adjusted based on the remaining drilling distance along the preset drilling trajectory, the stress condition of the drill rod, and the upper limit of the stress safety based on the real-time position.

6. The drilling trajectory autonomous decision-making method based on dynamic obstacle perception according to claim 1, characterized in that, The preset distance is greater than the maximum detection range of the drill bit and changes dynamically based on the stress on the drill rod and the upper limit of the stress safety.

7. The drilling trajectory autonomous decision-making method based on dynamic obstacle perception according to claim 1, characterized in that, The step of increasing the preset distance to update the target position and obstacle tolerance zone corresponding to the current position includes: The increment of the preset distance increases sequentially with each judgment result indicating that no available path exists.

8. The drilling trajectory autonomous decision-making method based on dynamic obstacle perception according to claim 1, characterized in that, Also includes: The decision-making process is halted when the number of times the determination of whether a usable path exists for the same unknown obstacle exceeds a preset number, in order to await manual intervention.

9. A drilling trajectory autonomous decision-making system based on dynamic obstacle perception, characterized in that, It includes a trajectory acquisition unit, an obstacle detection unit, a tolerance zone calculation unit, and a trajectory decision unit; The trajectory acquisition unit acquires a preset drilling trajectory planned based on known obstacles; The obstacle detection unit acquires obstacle parameter information of unknown obstacles in the direction of drill bit advance in real time during the drilling process along the preset drilling trajectory. The tolerance zone calculation unit obtains the obstacle tolerance zone corresponding to the real-time position of the drill bit and the drill bit posture corresponding to the target position at a preset distance from the real-time position along the preset drilling trajectory. The obstacle tolerance zone represents the set of all paths from the real-time position with the corresponding drill bit posture to the target position with the corresponding drill bit posture and all satisfying the maximum dogleg constraint; and obtains the stress condition of the drill pipe and the upper limit of the stress safety. Based on the stress conditions of the drill pipe and the upper limit of the stress safety, the obstacle tolerance zone is modified: the tolerance zone scaling factor is calculated according to the upper limit of the stress safety and the stress conditions of the drill pipe; All paths in the obstacle tolerance zone are sorted according to the magnitude of their respective increases in friction or torque. Some paths are then filtered out in descending order based on the tolerance zone scaling factor. The area formed by the set of remaining paths in three-dimensional space is used as the corrected obstacle tolerance zone. The larger the tolerance zone scaling factor, the closer the corrected obstacle tolerance zone is to the original size. The smaller the tolerance zone scaling factor, the more compact the corrected obstacle tolerance zone is. When the trajectory decision unit detects an unknown obstacle that interferes with the preset drilling trajectory, it determines whether there is a usable path based on the obstacle parameter information and the obstacle tolerance zone corresponding to the current position. If an available path exists, update the preset drilling trajectory between the current drill bit position and the corresponding target position based on the available path; If no available path exists, increase the preset distance to update the target position and obstacle tolerance zone corresponding to the current position, and then re-determine whether there is an available path based on the updated obstacle tolerance zone corresponding to the current position.

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