A full-size drill-grinding-milling tool high-precision dynamic simulation analysis method based on an adaptive FEM-SPH coupling algorithm

Abstract

This invention relates to the technical field of simulation analysis methods for downhole tools in oil and gas fields, and discloses a high-precision dynamic simulation analysis method for full-size drilling and milling tools based on an adaptive FEM-SPH coupled algorithm. The method includes three processes: model establishment, model solving, and performance evaluation. The first process is model establishment, which involves obtaining the geometric model of the drilling and milling tool through model reconstruction technology, and establishing a high-precision dynamic simulation analysis model for the full-size drilling and milling tool based on a wear prediction model and the adaptive SPH-FEM coupled algorithm. The second process is model solving, which involves solving the model after successively changing the drilling pressure and rotational speed, and batch processing the simulation results using Python. The third process is performance evaluation, which evaluates the performance of the drilling and milling tool from three aspects: efficiency, safety, and lifespan. This invention improves simulation accuracy from three aspects: geometric modeling, wear simulation, and solution algorithm, and evaluates the performance of the drilling and milling tool from three aspects: efficiency, safety, and lifespan.

Description

Technical Field

[0001] This invention belongs to the technical field of simulation analysis methods for downhole tools in oil and gas fields, specifically a high-precision dynamic simulation analysis method for full-size drilling and milling tools based on an adaptive FEM-SPH coupling algorithm. Background Technology

[0002] Drilling and milling tools are core equipment for removing metal blockages from wellbore during well workover operations in oil and gas fields. Their performance directly determines the efficiency, safety, and economy of well workover operations. As well workover operations move towards deeper wells and more complex conditions, higher requirements are placed on the design precision and performance stability of drilling and milling tools. High-precision dynamic simulation analysis methods are key technologies for optimizing tool structures and controlling process parameters. They can effectively reduce physical experiment costs and shorten the research and development cycle, thus becoming a research hotspot in the industry.

[0003] Currently, the dynamic simulation analysis method for drilling and milling tools mainly relies on the finite element method (FEM). Some studies employ a coupling approach between smoothed particle hydrodynamics (SPH) and FEM to address the issues of mesh distortion and simulation interruption that easily occur in pure FEM simulations of large deformations. While existing simulation methods have made some progress, they still suffer from several insurmountable shortcomings in practical applications, failing to meet the demands of high-precision simulation of full-size drilling and milling tools. Specifically: First, insufficient modeling accuracy. Existing methods often employ simplified geometric modeling, failing to fully reproduce the core structures of full-size drilling and milling tools, such as irregular cutting edges and irregular curved surfaces, and lacking precise reconstruction based on the actual tool. This results in significant deviations between the simulation model and the actual tool, affecting the accuracy of the simulation results. Second, imperfect coupling algorithms. Existing SPH-FEM coupling methods often use fixed-threshold element transformation criteria, failing to adaptively correct based on actual drilling experiments. They cannot dynamically adjust transformation conditions according to distortion during the simulation process, leading to poor simulation stability and reliability. Third, inability to implement… The current wear simulation methods generally treat drilling and milling tools as rigid bodies, which cannot simulate the wear of these tools, resulting in significant errors between the simulated wear figures and actual conditions. Fourth, the research on process parameters is not systematic. Existing simulations mostly solve for single process parameters and small-scale working conditions, lacking systematic variable parameter analysis of key process parameters such as drilling pressure and rotational speed. Furthermore, they fail to achieve batch extraction, screening, and visualization of simulation data, resulting in low efficiency. Fifth, the performance evaluation system is incomplete. Existing evaluations mostly focus on single indicators such as tool working efficiency or cutting force, failing to construct a complete performance evaluation system from the three dimensions of efficiency, safety, and lifespan. This makes it impossible to comprehensively identify the performance shortcomings of drilling and milling tools under extreme working conditions, and it is difficult to provide accurate data support for the structural optimization of drilling and milling tools.

[0004] Therefore, developing a method that can solve the above-mentioned technical defects and achieve dynamic simulation analysis and performance evaluation of full-size drilling and milling tools with high simulation accuracy and comprehensive performance evaluation has become a technical problem that urgently needs to be solved by those skilled in the art, and it is also the starting point of this invention. Summary of the Invention

[0005] In view of the above situation and to overcome the shortcomings of the prior art, the present invention provides a high-precision dynamic simulation analysis method for full-size drilling and milling tools based on the adaptive FEM-SPH coupling algorithm, which effectively solves the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a high-precision dynamic simulation analysis method for full-size drilling and milling tools based on an adaptive FEM-SPH coupling algorithm, comprising the following steps: Step 1: Model Establishment. For drilling and milling tools commonly used in oil and gas field well workover operations, a geometric model of the drilling and milling tools is obtained through model reconstruction technology. A wear prediction model of the drilling and milling tools is constructed through drilling experiments. At the same time, the adaptive SPH-FEM coupling algorithm is corrected through drilling experiments. Based on the geometric model of the drilling and milling tools, a full-size high-precision dynamic simulation analysis model of the drilling and milling tools is established based on the wear prediction model of the drilling and milling tools and the adaptive SPH-FEM coupling algorithm. Step 2: Model Solving. For the high-precision dynamic simulation analysis model of the full-size drilling and milling tool established above, the model is solved by first changing the drilling pressure in the system, and the simulation results are processed in batches using Python. Then, the model is solved by changing the rotation speed in the system, and the simulation results are processed in batches using Python. Step 3: Performance Evaluation. This section mainly focuses on the simulation results generated by the high-precision dynamic simulation analysis model of the full-size drilling and milling tool. The performance evaluation of the drilling and milling tool is carried out from three aspects: efficiency, safety, and lifespan. Specifically, the specific work of breaking is used as the evaluation index of the working efficiency of the drilling and milling tool, the dynamic torque is used as the evaluation index of the working safety of the drilling and milling tool, and the wear amount is used as the evaluation index of the working life of the drilling and milling tool. In this way, the dynamic analysis and performance evaluation of the drilling and milling tool are completed.

[0007] Preferably, during the model establishment process, a model reconstruction technology combining laser scanning and point cloud data is used to obtain the geometric model of the drilling and milling tool, ensuring that the geometric model can accurately reproduce the core structure of the drilling and milling tool, such as irregular cutting edges, irregular curved surfaces, and grooves.

[0008] Preferably, the geometric model of the drilling and milling tool is obtained using a model reconstruction technique combining laser scanning and point cloud data, including the following steps: The surface of the full-size drilling and milling tools commonly used in oil and gas field well workover is pre-treated by cleaning to remove impurities such as oil, rust, and dust from the tool surface. The drilling and milling tools are then fixed on the laser scanning worktable using a suitable clamp. Adjust the laser scanner parameters and use multi-angle, all-round scanning to collect three-dimensional coordinate data of the surface of the drilling and milling tool to generate raw point cloud data; Post-processing of point cloud data, such as filtering, registration, and segmentation, is performed to remove noise points, redundant points, and outliers, and multi-view point cloud data is fused to form a complete global point cloud. By fitting point clouds, reconstructing surfaces, and stitching and fusion, a smooth surface that closely matches the point cloud data is generated. At the same time, geometric information is supplemented for areas where point cloud data is missing due to scanning limitations, ensuring the continuity and integrity of the reconstructed surface. Finally, a three-dimensional geometric model of the drilling and milling tool that perfectly matches the actual size and shape of the tool is constructed.

[0009] Preferably, during the model establishment process, drilling experiments of drilling and milling tools are carried out using a drilling and milling tool drilling experiment system to construct a wear prediction model for drilling and milling tools.

[0010] Preferably, the drilling and milling tool drilling test system consists of a drilling and milling tool, a test system top plate, a synchronous belt, a synchronous pulley, a three-phase asynchronous motor, a test system column, a tensioning mechanism, a drill rod support, a test system crossbeam, a chuck support, a four-jaw chuck, a test system base, a waste liquid collection tray, a drill rod coupling, a torque sensor, a planetary gear reducer, a chuck guide rail, an electric cylinder support, an electric cylinder, metal blockage, and a pressure sensor. The experimental system top plate is positioned above the drilling and milling tool drilling experimental system. Four experimental system columns are positioned below the top plate. Tensioning mechanisms are located on the left, right, and rear sides of the columns via fastening bolts. The upper ends of the columns are fixedly connected to the lower ends of the top plate and the upper ends of the base via fastening bolts. A three-phase asynchronous motor is mounted on the lower end of the top plate via fastening bolts. The output shaft of the three-phase asynchronous motor is coaxially fixedly connected to the driving pulley of the synchronous belt pulley via a key. The driving and driven pulleys of the synchronous belt pulley are connected by a synchronous belt for belt drive. The driven pulley of the synchronous belt pulley is coaxially fixedly connected to the input shaft of the planetary gear reducer via a key. The planetary gear reducer is mounted on the lower end of the top plate via fastening bolts. The output shaft of the planetary gear reducer is coaxially fixedly connected to the input shaft of the torque sensor via a drill rod coupling. The input shaft of the torque sensor is coaxially fixedly connected to the drilling and milling tool connector via a drill rod coupling. The drilling and milling tool connector is fixedly connected to the drilling and milling tool via threads. The drilling and milling tool connector is coaxially fitted with the center hole of the experimental system beam. The experimental system beam is fixedly connected to the experimental system column via fastening bolts. A four-jaw chuck is arranged below the drilling and milling tool. The chuck above the four-jaw chuck is used to clamp metal blockages. A waste liquid collection tray is arranged below the four-jaw chuck. The lower end of the waste liquid collection tray is fixedly connected to the chuck bracket base plate by welding. The chuck bracket has an L-shaped structure. The base plate and side plate of the chuck bracket are fixedly connected by welding. The side plate of the chuck bracket reciprocates linearly along the side plate of the chuck guide rail. The base plate of the chuck guide rail is fixedly connected to the experimental system base via fastening bolts. A pressure sensor is arranged below the chuck bracket. The lower end face of the chuck bracket base plate contacts the upper end face of the pressure sensor. The lower end face of the pressure sensor is fixedly connected to the upper end face of the electric cylinder piston rod via threads. The side end face of the electric cylinder is fixedly connected to the side plate of the electric cylinder bracket via fastening bolts. The top plate of the electric cylinder bracket is fixedly connected to the experimental system base via fastening bolts.

[0011] Preferably, the method for constructing a wear prediction model for drilling and milling tools by conducting drilling experiments using a drilling and milling tool drilling experiment system during the model establishment process includes the following steps: First, connect the drilling and milling tool to the drilling and milling tool connector with threads. Clamp the metal blockage with a four-jaw chuck. At the same time, start the electric cylinder. The piston rod of the electric cylinder begins to push the four-jaw chuck and the metal blockage upward. When the metal blockage comes into contact with the drilling and milling tool, the pressure sensor collects and displays the drilling pressure. The drilling pressure of the drilling and milling tool can be changed by adjusting the displacement of the piston rod of the electric cylinder. Then start the three-phase asynchronous motor, and the drilling and milling tool will start to rotate and drill and grind the metal blockage. The speed of the drilling and milling tool can be changed by adjusting the speed of the three-phase asynchronous motor. After the drilling and milling tool has been drilling continuously for minutes, the piston rod of the electric cylinder moves downward and returns to the initial position, the three-phase asynchronous motor is turned off and the drilling and milling tool is removed, and the experimental torque of the drilling and milling tool is extracted through the torque sensor. The wear volume of drilling and milling tools is characterized by laser confocal microscopy and three-dimensional imaging technology, and a wear prediction model of drilling and milling tools is constructed based on the wear volume. Based on the wear prediction model of drilling and milling tools, an ABAQUS secondary development program was written in Python and incorporated with the geometric model of the drilling and milling tools to simulate the wear of the tools.

[0012] Preferably, during the model establishment process, drilling experiments of drilling and milling tools are conducted using a drilling and milling tool drilling experiment system to correct the adaptive SPH-FEM coupling algorithm. The steps include: First, drilling experiments of drilling and milling tools were carried out using a drilling and milling tool drilling experiment system, and the experimental torque of the drilling and milling tools was extracted using a torque sensor. Then, based on the geometric model of the drilling and milling tool obtained by the model reconstruction technology, and the wear prediction model of the drilling and milling tool constructed by the drilling experiment, a simulation model of the drilling and milling tool is established and the model is solved. Based on the equivalent plastic strain criterion, the distorted FEM elements of the metal plug are automatically converted into SPH particles of the metal plug. The simulation torque of the drilling and milling tool is extracted through the simulation model of the drilling and milling tool, with the goal of making the average value of the experimental torque and the simulation torque of the drilling and milling tool equal. The equivalent plastic strain value of the metal plug distorted FEM element is determined by the reverse calculation method, so as to obtain the critical condition for the automatic transformation of the metal plug distorted FEM element into metal plug SPH particles, and then the adaptive SPH-FEM coupling algorithm correction is completed.

[0013] Preferably, in the model solving process, for the high-precision dynamic simulation analysis model of the full-size drilling and milling tool established during the model building process, the steps include: First, the system changes the drilling pressure, with an adjustment range of 5-25kN and a step size of 5kN. The drilling pressure is set sequentially to 5kN, 10kN, 15kN, 20kN, and 25kN. For each drilling pressure condition, the simulation software is started to solve the model. The solution time is 10 minutes. Each condition is solved 3 times, and the average of the 3 simulation results is taken as the valid data for that condition. Meanwhile, Python processing scripts were written to extract simulation data under various working conditions using the PyANSYS library, and the data was filtered, fitted and visualized to obtain reports of key parameters under different drilling pressure conditions. Then, keeping the drilling pressure constant at 10kN, the system changes the rotation speed, with the speed adjustment range being 50-250r / min and the step size being 50r / min. The rotation speed is set sequentially to 50r / min, 100r / min, 150r / min, 200r / min, and 250r / min. For each speed condition, the simulation software was started to solve the model. The solution time was 10 minutes. Each condition was solved 3 times, and the average of the 3 simulation results was taken as the valid data for that condition. Simultaneously, Python processing scripts were written to extract simulation data under various operating conditions using the PyANSYS library, and the data was filtered, fitted, and visualized to obtain reports of key parameters under different speed operating conditions.

[0014] Preferably, in the performance evaluation process, the drilling and milling tool is evaluated in terms of efficiency, safety, and lifespan based on the simulation data obtained during model solving. The steps include: First, the work efficiency is evaluated using the specific energy required for breaking the blockage as an evaluation index. The work done by the external force of the drilling and milling tool during the drilling process is obtained through a high-precision dynamic simulation analysis model of the full-size drilling and milling tool. At the same time, the volume of the metal blockage before and after drilling is obtained through the same model. The volume reduction of the metal blockage is obtained by subtracting the volume of the metal blockage after drilling from the volume before drilling. The specific energy required for breaking the blockage is obtained by dividing the work done by the external force of the drilling and milling tool by the volume reduction of the metal blockage. This is the energy required to break a unit volume of metal blockage. A high specific energy required for breaking the blockage reflects low work efficiency. Therefore, the specific energy required for breaking the blockage is used as an evaluation index to evaluate the work efficiency of the drilling and milling tool. Then, the dynamic torque is used as the evaluation index for work safety evaluation. The dynamic torque curve of the drilling and milling tool during the drilling process is obtained through a high-precision dynamic simulation analysis model of the full-size drilling and milling tool. The peak value, average value and fluctuation range of the dynamic torque are obtained based on the dynamic torque curve of the drilling and milling tool. The larger the peak value, average value and fluctuation range of the dynamic torque of the drilling and milling tool, the worse the work safety of the drilling and milling tool. Therefore, the peak value, average value and fluctuation range of the dynamic torque of the drilling and milling tool are comprehensively considered to carry out the work safety evaluation of the drilling and milling tool. Finally, the working life of the drilling and milling tool is evaluated using wear as the evaluation index. The volume of the drilling and milling tool before and after drilling is obtained through a high-precision dynamic simulation analysis model of the full-size drilling and milling tool. The wear of the drilling and milling tool is obtained by subtracting the volume of the drilling and milling tool after drilling from the volume before drilling. A large wear of the drilling and milling tool reflects a short working life. Therefore, the working life of the drilling and milling tool is evaluated using wear as the evaluation index.

[0015] Preferably, the simulation data for each working condition is extracted from the PyANSYS library, and the simulation data includes crushing specific work, dynamic torque, and wear amount.

[0016] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention provides a high-precision dynamic simulation analysis method for full-size drilling and milling tools based on an adaptive FEM-SPH coupling algorithm, achieving high simulation accuracy. The method improves simulation accuracy from three aspects: geometric modeling, wear simulation, and solution algorithm. Specifically, it employs laser scanning combined with point cloud data model reconstruction technology to obtain the geometric model of the drilling and milling tool, ensuring that the geometric model accurately reproduces the core structures of the tool, such as irregular cutting edges, irregular curved surfaces, and grooves. Drilling experiments are conducted using a drilling and milling tool drilling experiment system to construct a wear prediction model for the tool. An ABAQUS secondary development program is written in Python and incorporated into the geometric model of the drilling and milling tool to simulate the wear amount. Finally, drilling experiments are conducted using the drilling and milling tool drilling experiment system to correct the adaptive SPH-FEM coupling algorithm, further improving the accuracy of the dynamic analysis model for full-size drilling and milling tools.

[0017] 2. This invention provides a high-precision dynamic simulation analysis method for full-size drilling and milling tools based on an adaptive FEM-SPH coupling algorithm, offering comprehensive performance evaluation. Through a high-precision dynamic simulation analysis model of full-size drilling and milling tools, the breaking specific work, dynamic torque, and wear amount of the tools are obtained. Breaking specific work is used as the evaluation index for the working efficiency of the drilling and milling tools, dynamic torque as the evaluation index for the working safety of the tools, and wear amount as the evaluation index for the working life of the tools. The performance of the drilling and milling tools is evaluated from three aspects: efficiency, safety, and lifespan. Attached Figure Description

[0018] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0019] In the attached diagram: Figure 1 The flowchart of a high-precision dynamic simulation analysis method for full-size drilling and milling tools based on an adaptive FEM-SPH coupling algorithm is provided for this invention.

[0020] Figure 2 This is a geometric model diagram of the full-size drilling and milling tool in this invention.

[0021] Figure 3 This is a schematic diagram of the overall design of the drilling and milling tool drilling experimental system in this invention.

[0022] Figure 4This is a partial structural diagram of the drilling and milling tool drilling experimental system of the present invention.

[0023] Figure 5 This is a high-precision dynamic simulation analysis model diagram of the full-size drilling and milling tool in this invention.

[0024] Figure 6 This is a schematic diagram of the adaptive FEM-SPH coupling algorithm in this invention.

[0025] In the diagram: 1. Drilling and milling tool; 2. Point cloud data; 3. Experimental system top plate; 4. Synchronous belt; 5. Synchronous pulley; 6. Three-phase asynchronous motor; 7. Experimental system column; 8. Tensioning mechanism; 9. Drill rod support; 10. Experimental system crossbeam; 11. Chuck support; 12. Four-jaw chuck; 13. Experimental system base; 14. Waste liquid collection tray; 15. Drill rod coupling; 16. Torque sensor; 17. Planetary gear reducer; 18. Chuck guide rail; 19. Electric cylinder support; 20. Electric cylinder; 21. Metal blockage; 22. Metal blockage FEM unit; 23. Metal blockage distortion FEM unit; 24. Metal blockage SPH particles; 25. Pressure sensor. Detailed Implementation

[0026] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0027] like Figure 1-6As shown, this invention provides a high-precision dynamic simulation analysis method for full-size drilling and milling tools based on an adaptive FEM-SPH coupling algorithm. The method includes three processes: model building, model solving, and performance evaluation. The specific process is as follows: The first process is model building. For drilling and milling tools commonly used in oil and gas field well workover operations, a geometric model of the tool is obtained through model reconstruction technology. A wear prediction model for the tool is constructed through drilling experiments. Simultaneously, the adaptive SPH-FEM coupling algorithm is corrected through drilling experiments. Based on the geometric model of the tool, a high-precision dynamic simulation analysis model for full-size drilling and milling tools is established based on the wear prediction model and the adaptive SPH-FEM coupling algorithm. The second process is model solving. For the high-precision dynamic simulation analysis model of the full-size drilling and milling tool established above, the model is first solved after the drilling pressure is changed, and the simulation results are processed in batches using Python. Then, the model is solved after the rotation speed is changed, and the simulation results are processed in batches using Python. The third process is performance evaluation. This part mainly focuses on the simulation results generated by the high-precision dynamic simulation analysis model of the full-size drilling and milling tool, and evaluates the performance of the drilling and milling tool 1 from three aspects: efficiency, safety, and lifespan. The specific work of crushing is used as the evaluation index of the working efficiency of the drilling and milling tool 1, the dynamic torque is used as the evaluation index of the working safety of the drilling and milling tool 1, and the wear amount is used as the evaluation index of the working life of the drilling and milling tool 1. Thus, the dynamic analysis and performance evaluation of the drilling and milling tool are completed.

[0028] During the model establishment process, a model reconstruction technique combining laser scanning and point cloud data is used to obtain the geometric model of the drilling and milling tool. Specifically, this includes: pre-treating the surface of a full-size drilling and milling tool 1 commonly used in oil and gas field well workover to remove oil, rust, dust, and other impurities; fixing the drilling and milling tool 1 onto the laser scanning worktable using an adapter fixture; adjusting the laser scanner parameters, including laser wavelength, scanning accuracy, scanning speed, and point cloud density; acquiring three-dimensional coordinate data of the surface of the drilling and milling tool 1 using multi-angle and omnidirectional scanning methods to generate original point cloud data 2; and further processing the point cloud data 2. Post-processing steps such as line filtering, registration, and segmentation are performed to remove noise, redundant, and outlier points. Multi-view point cloud data 2 is then fused to form a complete global point cloud. Through point cloud fitting, surface reconstruction, and stitching fusion, a smooth surface that closely matches point cloud data 2 is generated. At the same time, geometric information is supplemented for areas missing in point cloud data 2 due to scanning limitations to ensure the continuity and integrity of the reconstructed surface. Finally, a three-dimensional geometric model of the drilling and milling tool 1 is constructed that perfectly matches the actual size and shape of the tool, ensuring that the geometric model can accurately reproduce the core structures of the drilling and milling tool 1, such as irregular cutting edges, irregular curved surfaces, and grooves.

[0029] Specifically, during the model establishment process, drilling experiments of drilling and milling tool 1 are conducted through a drilling and milling tool drilling experiment system to construct a wear prediction model for drilling and milling tool 1. The specific process is as follows: The drilling and milling tool drilling experiment system mainly consists of drilling and milling tool 1, experimental system top plate 3, synchronous belt 4, synchronous pulley 5, three-phase asynchronous motor 6, experimental system column 7, tensioning mechanism 8, drill rod support 9, experimental system crossbeam 10, chuck support 11, four-jaw chuck 12, experimental system base 13, waste liquid collection tray 14, drill rod coupling 15, torque sensor 16, planetary gear reducer 17, chuck guide rail 18, electric cylinder support 19, electric cylinder 20, metal blockage 21, and pressure sensor 25. The experimental system top plate 3 is positioned above the drilling and milling tool drilling experimental system. Four experimental system columns 7 are positioned below the top plate 3. Tensioning mechanisms 8 are respectively positioned on the left, right, and rear sides of the experimental system columns 7 using fastening bolts. The upper ends of the experimental system columns 7 are fixedly connected to the lower ends of the experimental system top plate 3 using fastening bolts, and the lower ends of the experimental system columns 7 are fixedly connected to the upper ends of the experimental system base 13 using fastening bolts. A three-phase asynchronous motor 6 is mounted on the lower end of the experimental system top plate 3 using fastening bolts. The output shaft of the three-phase asynchronous motor 6 is connected to the synchronous pulley 5. The driving pulley is coaxially fixedly connected via a key. The driving pulley and driven pulley of the synchronous belt pulley 5 are belt driven by the synchronous belt 4. The driven pulley of the synchronous belt pulley 5 is coaxially fixedly connected to the input shaft of the planetary gear reducer 17 via a key. The planetary gear reducer 17 is mounted on the lower end of the top plate 3 of the experimental system by fastening bolts. The output shaft of the planetary gear reducer 17 is coaxially fixedly connected to the input shaft of the torque sensor 16 via a drill rod coupling 15. The input shaft of the torque sensor 16 is coaxially fixedly connected to the drilling and milling tool joint via the drill rod coupling 15. The drilling and milling tool joint is coaxially fixedly connected to the drilling and milling tool joint. Tool 1 is fixedly connected by threads. The drill and milling tool connector is coaxially fitted with the center hole of the experimental system beam 10. The experimental system beam 10 is fixedly connected to the experimental system column 7 by fastening bolts. A four-jaw chuck 12 is arranged below the drill and milling tool 1. The chuck above the four-jaw chuck 12 is used to clamp the metal blockage 21. A waste liquid collection tray 14 is arranged below the four-jaw chuck 12. The lower end of the waste liquid collection tray 14 is fixedly connected to the base plate of the chuck bracket 11 by welding. The chuck bracket 11 has an L-shaped structure. The base plate and side plates of the chuck bracket 11 are fixedly connected by welding. The side plate of the frame 11 reciprocates linearly along the side plate of the chuck guide rail 18. The bottom plate of the chuck guide rail 18 is fixedly connected to the experimental system base 13 by fastening bolts. A pressure sensor 25 is arranged below the chuck support 11. The lower end face of the bottom plate of the chuck support 11 contacts the upper end face of the pressure sensor 25. The lower end face of the pressure sensor 25 is fixedly connected to the upper end face of the piston rod of the electric cylinder 20 by threads. The side end face of the electric cylinder 20 is fixedly connected to the side plate of the electric cylinder support 19 by fastening bolts. The top plate of the electric cylinder support 19 is fixedly connected to the experimental system base 13 by fastening bolts.

[0030] The drilling experiment of the milling and grinding tool is as follows: First, the milling and grinding tool 1 is fixedly connected to the milling and grinding tool connector by threads. The metal blockage 21 is clamped by the four-jaw chuck 12. At the same time, the electric cylinder 20 is started. The piston rod of the electric cylinder 20 begins to push the four-jaw chuck 12 and the metal blockage 21 upward. When the metal blockage 21 contacts the milling and grinding tool 1, the pressure sensor 25 collects and displays the drilling pressure. The drilling pressure of the milling and grinding tool 1 can be changed by adjusting the displacement of the piston rod of the electric cylinder 20. Then, the three-phase asynchronous motor 6 is started, and the milling and grinding tool 1 begins to rotate and drill the metal blockage 21. The drilling pressure of the milling and grinding tool 1 can be changed by adjusting the three-phase asynchronous motor 6. The rotational speed of the asynchronous motor 6 can change the rotational speed of the drilling and milling tool 1. After the drilling and milling tool 1 has been drilling continuously for 10 minutes, the piston rod of the electric cylinder 20 moves downward and returns to the initial position, the three-phase asynchronous motor 6 is turned off and the drilling and milling tool 1 is removed. The wear volume of the drilling and milling tool 1 is characterized by laser confocal microscopy and three-dimensional imaging technology. Based on the wear volume, a wear prediction model of the drilling and milling tool 1 is constructed. According to the wear prediction model of the drilling and milling tool 1, an ABAQUS secondary development program is written based on Python language and the geometric model of the drilling and milling tool is added to realize the simulation function of the wear amount of the drilling and milling tool 1.

[0031] Specifically, during the model establishment process, drilling experiments of drilling and milling tool 1 were conducted using a drilling and milling tool drilling experiment system to correct the adaptive SPH-FEM coupling algorithm. The specific process is as follows: First, drilling and milling tool 1 is fixedly connected to the drilling and milling tool connector via threads. The metal blockage 21 is clamped by a four-jaw chuck 12. Simultaneously, the electric cylinder 20 is activated. The piston rod of the electric cylinder 20 begins to push the four-jaw chuck 12 and the metal blockage 21 upward. When the metal blockage 21 contacts the drilling and milling tool 1, the pressure sensor 25 collects data. The drilling pressure is displayed and adjusted by changing the displacement of the piston rod of the electric cylinder 20. Then, the three-phase asynchronous motor 6 is started, and the drilling tool 1 begins to rotate and drill the metal blockage 21. The rotation speed of the drilling tool 1 can be changed by adjusting the speed of the three-phase asynchronous motor 6. After the drilling tool 1 drills continuously for 10 minutes, the piston rod of the electric cylinder 20 moves downward and returns to the initial position. The three-phase asynchronous motor 6 is turned off and the drilling tool 1 is removed. The experimental torque of the drilling tool 1 is extracted by the torque sensor 16. Simultaneously, based on the geometric model of the drilling and milling tool obtained through model reconstruction technology, and the wear prediction model of the drilling and milling tool constructed from drilling experiments, a simulation model of the drilling and milling tool is established. The model is then solved using a modified adaptive SPH-FEM coupling algorithm. The modification process of the adaptive SPH-FEM coupling algorithm is as follows: During the drilling process, the drilling and milling tool 1 generates a cutting force on the metal plug 21. When the metal plug 21 is subjected to this cutting force, the metal plug FEM element 22 undergoes mesh element distortion, resulting in distorted metal plug FEM element 23, which causes the simulation to report an error and terminate. Therefore, based on the equivalent plastic strain criterion, the distorted metal blockage FEM element 23 is automatically transformed into metal blockage SPH particles 24, thereby ensuring the simulation continues and simulating the generation and movement of debris. The simulation torque of the drilling and milling tool 1 is extracted through the drilling and milling tool simulation model. With the goal of equalizing the average value of the experimental torque and the simulation torque of the drilling and milling tool 1, the equivalent plastic strain value of the FEM element being transformed into SPH particles is determined by the back-reasoning method. Thus, the critical condition for the distorted metal blockage FEM element 23 to be automatically transformed into metal blockage SPH particles 24 is obtained, thereby completing the adaptive SPH-FEM coupling algorithm correction.

[0032] In the model solving process, for the full-size drilling and milling tool high-precision dynamic simulation analysis model established during model building, the drilling pressure is first changed systematically. The drilling pressure adjustment range is 5-25kN, with a step size of 5kN. The drilling pressure is set sequentially to 5kN, 10kN, 15kN, 20kN, and 25kN. Under each drilling pressure condition, the simulation software is started to solve the model. The solution time is 10 minutes. Each condition is repeated 3 times, and the average of the 3 simulation results is taken as the valid data under that condition. At the same time, a Python processing script is written to extract the simulation data (breaking specific power, dynamic torque, wear) under each condition through the PyANSYS library. The data is then filtered, fitted, and visualized to obtain reports of key parameters under different drilling pressure conditions. Then, keeping the drilling pressure constant at 10kN, the system changes the rotation speed, with an adjustment range of 50-250 r / min and a step size of 50 r / min. The rotation speed is set sequentially to 50 r / min, 100 r / min, 150 r / min, 200 r / min, and 250 r / min. Under each rotation speed condition, the simulation software is started to solve the model, with a solution time of 10 minutes. Each condition is solved three times, and the average of the three simulation results is taken as the effective data under that condition. At the same time, a Python processing script is written to extract the simulation data (breaking specific power, dynamic torque, and wear) under each condition through the PyANSYS library. The data is then filtered, fitted, and visualized to obtain reports of key parameters under different rotation speed conditions.

[0033] In the performance evaluation process, based on the simulation data obtained during the model solving process, the performance of the drilling and milling tool 1 is evaluated from three aspects: efficiency, safety, and lifespan. The specific evaluation process is as follows: First, the working efficiency is evaluated using the specific energy of breaking the metal blockage as the evaluation index. The external force work done by the drilling and milling tool 1 during the drilling process is obtained through the high-precision dynamic simulation analysis model of the full-size drilling and milling tool. At the same time, the volume of the metal blockage 21 before and after drilling is obtained through the high-precision dynamic simulation analysis model of the full-size drilling and milling tool. The volume reduction of the metal blockage 21 is obtained by subtracting the volume of the metal blockage 21 after drilling from the volume before drilling. The specific energy of breaking the metal blockage 21 is obtained by dividing the external force work done by the drilling and milling tool 1 by the volume reduction of the metal blockage 21. That is, the energy required to break a unit volume of metal blockage 21. A large specific energy of breaking the metal blockage 1 reflects low working efficiency of the drilling and milling tool 1. Therefore, the working efficiency of the drilling and milling tool 1 is evaluated using the specific energy of breaking the metal blockage 21 as the evaluation index. Then, dynamic torque is used as the evaluation index for work safety assessment. The dynamic torque curve of drilling and milling tool 1 during the drilling process is obtained through a high-precision dynamic simulation analysis model of the full-size drilling and milling tool. The peak value, average value and fluctuation range of dynamic torque are obtained based on the dynamic torque curve of drilling and milling tool 1. A large peak value, average value and fluctuation range of dynamic torque of drilling and milling tool 1 reflects poor work safety of drilling and milling tool 1. Therefore, the work safety assessment of drilling and milling tool 1 is carried out by comprehensively considering the peak value, average value and fluctuation range of dynamic torque of drilling and milling tool 1. Finally, wear amount is used as the evaluation index for work life assessment. The volume of drilling and milling tool 1 before drilling and after drilling are obtained through a high-precision dynamic simulation analysis model of the full-size drilling and milling tool. The wear amount of drilling and milling tool 1 is obtained by subtracting the volume of drilling and milling tool 1 after drilling from the volume of drilling and milling tool 1 before drilling. A large wear amount of drilling and milling tool 1 reflects a short work life of drilling and milling tool 1. Therefore, the work life assessment of drilling and milling tool 1 is carried out using wear amount as the evaluation index. Based on the above evaluation results, the performance of the drilling and milling tool 1 was evaluated from three aspects: efficiency, safety, and lifespan. At the same time, the performance shortcomings of the drilling and milling tool 1 under extreme working conditions (high drilling pressure, high speed) can be quickly identified, providing accurate data support for the structural optimization of the drilling and milling tool 1.

[0034] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0035] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A high-precision dynamic simulation analysis method for full-size drilling and milling tools based on an adaptive FEM-SPH coupling algorithm, characterized by the following steps: include: Step 1: Model establishment. For the drilling and milling tools commonly used in oil and gas field well workover operations (1), the geometric model of the drilling and milling tools is obtained through model reconstruction technology. The wear prediction model of the drilling and milling tools is constructed through drilling experiments. At the same time, the adaptive SPH-FEM coupling algorithm is corrected through drilling experiments. Based on the geometric model of the drilling and milling tools, a full-size high-precision dynamic simulation analysis model of the drilling and milling tools is established based on the wear prediction model of the drilling and milling tools and the adaptive SPH-FEM coupling algorithm. Step 2: Model Solving. For the high-precision dynamic simulation analysis model of the full-size drilling and milling tool established above, the model is solved by first changing the drilling pressure in the system, and the simulation results are processed in batches using Python. Then, the model is solved by changing the rotation speed in the system, and the simulation results are processed in batches using Python. Step 3: Performance Evaluation. This section mainly focuses on the simulation results generated by the high-precision dynamic simulation analysis model of the full-size drilling and milling tool. The performance evaluation of the drilling and milling tool (1) is carried out from three aspects: efficiency, safety and life. Among them, the specific work of breaking is used as the evaluation index of the working efficiency of the drilling and milling tool (1), the dynamic torque is used as the evaluation index of the working safety of the drilling and milling tool (1), and the wear amount is used as the evaluation index of the working life of the drilling and milling tool (1). In this way, the dynamic analysis and performance evaluation of the drilling and milling tool are completed.

2. The high-precision dynamic simulation analysis method for full-size drilling and milling tools based on the adaptive FEM-SPH coupling algorithm according to claim 1, characterized in that: During the model establishment process, a model reconstruction technology combining laser scanning and point cloud data is used to obtain the geometric model of the drilling and milling tool, ensuring that the geometric model can accurately restore the core structure of the drilling and milling tool (1), such as irregular cutting edges, irregular curved surfaces, and grooves.

3. The high-precision dynamic simulation analysis method for full-size drilling and milling tools based on the adaptive FEM-SPH coupling algorithm according to claim 2, characterized in that: The geometric model of a drilling and milling tool is obtained using a model reconstruction technique that combines laser scanning with point cloud data, including the following steps: The surface of the full-size drilling and milling tool (1) commonly used in oil and gas field well repair is pre-treated by cleaning to remove oil, rust, dust and other impurities from the tool surface. The drilling and milling tool (1) is fixed on the laser scanning worktable using an adapter clamp. Adjust the parameters of the laser scanner and use multi-angle and all-round scanning to collect three-dimensional coordinate data of the surface of the drilling and milling tool (1) to generate original point cloud data (2); The point cloud data (2) is processed by filtering, registration, segmentation and other post-processing to remove noise points, redundant points and abnormal points, and the multi-view point cloud data (2) is fused to form a complete global point cloud; By fitting point clouds, reconstructing curved surfaces and splicing and fusion, a smooth curved surface that closely matches the point cloud data (2) is generated. At the same time, geometric information is supplemented for the missing areas of point cloud data (2) caused by scanning limitations, ensuring the continuity and integrity of the reconstructed curved surface. Finally, a three-dimensional geometric model of the drilling and milling tool (1) that is completely matched with the actual size and shape of the drilling and milling tool (1) is constructed.

4. The high-precision dynamic simulation analysis method for full-size drilling and milling tools based on the adaptive FEM-SPH coupling algorithm according to claim 3, characterized in that: During the model establishment process, drilling experiments of drilling and milling tools (1) were carried out through a drilling and milling tool drilling experiment system to construct a wear prediction model for drilling and milling tools (1).

5. A high-precision dynamic simulation analysis method for full-size drilling and milling tools based on an adaptive FEM-SPH coupling algorithm as described in claim 4, characterized in that: The drilling and milling tool drilling test system consists of a drilling and milling tool (1), a test system top plate (3), a synchronous belt (4), a synchronous pulley (5), a three-phase asynchronous motor (6), a test system column (7), a tensioning mechanism (8), a drill rod support (9), a test system crossbeam (10), a chuck support (11), a four-jaw chuck (12), a test system base (13), a waste liquid collection tray (14), a drill rod coupling (15), a torque sensor (16), a planetary gear reducer (17), a chuck guide rail (18), an electric cylinder support (19), an electric cylinder (20), a metal blockage (21), and a pressure sensor (25). The experimental system top plate (3) is arranged above the drilling and milling tool drilling experimental system. Four experimental system columns (7) are arranged below the top plate (3). Tensioning mechanisms (8) are respectively arranged on the left, right, and rear sides of the experimental system columns (7) via fastening bolts. The upper end of the experimental system columns (7) is fixedly connected to the lower end of the experimental system top plate (3) via fastening bolts. The lower end of the experimental system columns (7) is fixedly connected to the upper end of the experimental system base (13) via fastening bolts. A three-phase asynchronous motor (6) is installed at the lower end of the experimental system top plate (3) via fastening bolts. The output shaft of the three-phase asynchronous motor (6) is connected to the synchronous pulley (5). The driving pulley is coaxially fixedly connected by a key. The driving pulley and driven pulley of the synchronous belt pulley (5) are belt driven by the synchronous belt (4). The driven pulley of the synchronous belt pulley (5) is coaxially fixedly connected to the input shaft of the planetary gear reducer (17) by a key. The planetary gear reducer (17) is installed on the lower end of the top plate (3) of the experimental system by fastening bolts. The output shaft of the planetary gear reducer (17) is coaxially fixedly connected to the input shaft of the torque sensor (16) by a drill rod coupling (15). The input shaft of the torque sensor (16) is coaxially fixedly connected to the drill milling tool joint by a drill rod coupling (15). The drill milling tool joint and the drill milling tool (17) are coaxially fixedly connected to the drill milling tool (16). The drilling and milling tool connector is coaxially fitted with the center hole of the experimental system beam (10) through a threaded connection. The experimental system beam (10) and the experimental system column (7) are fixedly connected by fastening bolts. A four-jaw chuck (12) is arranged below the drilling and milling tool (1). The chuck above the four-jaw chuck (12) is used to clamp the metal blockage (21). A waste liquid collection tray (14) is arranged below the four-jaw chuck (12). The lower end of the waste liquid collection tray (14) is fixedly connected to the bottom plate of the chuck bracket (11) by welding. The chuck bracket (11) has an L-shaped structure. The bottom plate and side plate of the chuck bracket (11) are fixedly connected by welding. The side plate of 11) moves back and forth linearly along the side plate of the chuck guide rail (18). The bottom plate of the chuck guide rail (18) is fixedly connected to the experimental system base (13) by fastening bolts. The pressure sensor (25) is arranged below the chuck bracket (11). The lower end face of the bottom plate of the chuck bracket (11) contacts the upper end face of the pressure sensor (25). The lower end face of the pressure sensor (25) is fixedly connected to the upper end face of the piston rod of the electric cylinder (20) by threads. The side end face of the electric cylinder (20) is fixedly connected to the side plate of the electric cylinder bracket (19) by fastening bolts. The top plate of the electric cylinder bracket (19) is fixedly connected to the experimental system base (13) by fastening bolts.

6. The high-precision dynamic simulation analysis method for full-size drilling and milling tools based on the adaptive FEM-SPH coupling algorithm according to claim 5, characterized in that: The method for constructing a wear prediction model for the drilling and milling tool (1) by conducting drilling experiments using a drilling and milling tool drilling experiment system during the model establishment process includes the following steps: First, the drilling and milling tool (1) is fixedly connected to the drilling and milling tool connector by thread. The metal blockage (21) is clamped by the four-jaw chuck (12). At the same time, the electric cylinder (20) is started. The piston rod of the electric cylinder (20) begins to push the four-jaw chuck (12) and the metal blockage (21) upward. When the metal blockage (21) contacts the drilling and milling tool (1), the pressure sensor (25) collects and displays the drilling pressure. The drilling pressure of the drilling and milling tool (1) can be changed by adjusting the displacement of the piston rod of the electric cylinder (20). Then start the three-phase asynchronous motor (6), and the drilling and milling tool (1) starts to rotate and drill and grind the metal blockage (21). The speed of the drilling and milling tool (1) can be changed by adjusting the speed of the three-phase asynchronous motor (6). After the drilling and milling tool (1) drills continuously for 10 minutes, the piston rod of the electric cylinder (20) moves downward and returns to the initial position, the three-phase asynchronous motor (6) is turned off and the drilling and milling tool (1) is removed. The experimental torque of the drilling and milling tool (1) is extracted by the torque sensor (16). The wear volume of the drilling and milling tool was characterized by laser confocal microscopy and three-dimensional imaging technology, and a wear prediction model of the drilling and milling tool (1) was constructed based on the wear volume. Based on the wear prediction model of the drilling and milling tool (1), an ABAQUS secondary development program was written in Python and the geometric model of the drilling and milling tool was added to realize the simulation of the wear amount of the drilling and milling tool.

7. A high-precision dynamic simulation analysis method for full-size drilling and milling tools based on an adaptive FEM-SPH coupling algorithm as described in claim 6, characterized in that: During the model establishment process, drilling experiments of drilling and milling tools are conducted using a drilling and milling tool drilling experiment system to correct the adaptive SPH-FEM coupling algorithm. The steps include: First, a drilling experiment of the drilling and milling tool (1) was carried out using a drilling and milling tool (1) drilling experiment system, and the experimental torque of the drilling and milling tool (1) was extracted by a torque sensor (16). Then, based on the geometric model of the drilling and milling tool obtained by the model reconstruction technology, and the wear prediction model of the drilling and milling tool (1) constructed by the drilling experiment, a simulation model of the drilling and milling tool is established and the model is solved. According to the equivalent plastic strain criterion, the distorted FEM element (23) of the metal plug is automatically converted into metal plug SPH particles (24). The simulation torque of the drilling and milling tool is extracted through the simulation model of the drilling and milling tool, with the goal of making the average value of the experimental torque and the simulation torque of the drilling and milling tool equal. The equivalent plastic strain value of the metal plug distorted FEM element (23) transformed into S metal plug SPH particle (24) is determined by the reverse calculation method, thereby obtaining the critical condition for the automatic transformation of the metal plug distorted FEM element (23) into metal plug SPH particle (24), and then completing the adaptive SPH-FEM coupling algorithm correction.

8. The high-precision dynamic simulation analysis method for full-size drilling and milling tools based on the adaptive FEM-SPH coupling algorithm according to claim 7, characterized in that: The model solving process, for the high-precision dynamic simulation analysis model of the full-size drilling and milling tool established during the model building process, includes the following steps: First, the system changes the drilling pressure, with an adjustment range of 5-25kN and a step size of 5kN. The drilling pressure is set sequentially to 5kN, 10kN, 15kN, 20kN, and 25kN. For each drilling pressure condition, the simulation software is started to solve the model. The solution time is 10 minutes. Each condition is solved 3 times, and the average of the 3 simulation results is taken as the valid data for that condition. Meanwhile, Python processing scripts were written to extract simulation data under various working conditions using the PyANSYS library, and the data was filtered, fitted and visualized to obtain reports of key parameters under different drilling pressure conditions. Then, keeping the drilling pressure constant at 10kN, the system changes the rotation speed, with the speed adjustment range being 50-250r / min and the step size being 50r / min. The rotation speed is set sequentially to 50r / min, 100r / min, 150r / min, 200r / min, and 250r / min. For each speed condition, the simulation software was started to solve the model. The solution time was 10 minutes. Each condition was solved 3 times, and the average of the 3 simulation results was taken as the valid data for that condition. Simultaneously, Python processing scripts were written to extract simulation data under various operating conditions using the PyANSYS library, and the data was filtered, fitted, and visualized to obtain reports of key parameters under different speed operating conditions.

9. A high-precision dynamic simulation analysis method for full-size drilling and milling tools based on an adaptive FEM-SPH coupling algorithm as described in claim 5, characterized in that: In the performance evaluation process, the performance of the drilling and milling tool (1) is evaluated from three aspects: efficiency, safety, and lifespan, based on the simulation data obtained during the model solving process. The steps include: First, the work efficiency is evaluated using the specific energy of breaking as the evaluation index. The work done by the external force of the drilling and milling tool (1) during the drilling process is obtained through the high-precision dynamic simulation analysis model of the full-size drilling and milling tool. At the same time, the volume of the metal blockage (21) before and after drilling is obtained through the high-precision dynamic simulation analysis model of the full-size drilling and milling tool. The volume reduction of the metal blockage (21) is obtained by subtracting the volume of the metal blockage (21) after drilling from the volume before drilling. The specific energy of breaking the drilling and milling tool (1) is obtained by dividing the work done by the external force of the drilling and milling tool (1) by the volume reduction of the metal blockage (21). That is, the energy required to break a unit volume of metal blockage (21). A large specific energy of breaking the drilling and milling tool (1) reflects a low work efficiency of the drilling and milling tool (1). Therefore, the work efficiency of the drilling and milling tool (1) is evaluated using the specific energy of breaking as the evaluation index. Then, the dynamic torque is used as the evaluation index to conduct a work safety evaluation. The dynamic torque curve of the drilling and milling tool (1) during the drilling process is obtained through the full-size high-precision dynamic simulation analysis model of the drilling and milling tool (1). The peak value, average value and fluctuation range of the dynamic torque are obtained based on the dynamic torque curve of the drilling and milling tool (1). The large peak value, average value and fluctuation range of the dynamic torque of the drilling and milling tool (1) reflect the poor work safety of the drilling and milling tool (1). Then, the peak value, average value and fluctuation range of the dynamic torque of the drilling and milling tool (1) are comprehensively considered to carry out the work safety evaluation of the drilling and milling tool (1). Finally, the working life is evaluated using wear as the evaluation index. The volume of the drilling and milling tool (1) before drilling and after drilling is obtained by a full-size high-precision dynamic simulation analysis model. The wear of the drilling and milling tool (1) is obtained by subtracting the volume of the drilling and milling tool (1) after drilling from the volume before drilling. A large wear of the drilling and milling tool (1) reflects a short working life. Therefore, the working life of the drilling and milling tool (1) is evaluated using wear as the evaluation index.

10. A high-precision dynamic simulation analysis method for full-size drilling and milling tools based on an adaptive FEM-SPH coupling algorithm as described in claim 9, characterized in that: The simulation data for each working condition is extracted from the PyANSYS library. The simulation data includes crushing specific work, dynamic torque, and wear.

Images