Intelligent directional closed-loop regulation method and system for bent housing screw drill combination

Abstract

This invention discloses an intelligent directional closed-loop control method and system for a curved-shell screw drill string assembly. The method includes intelligent switching control of sliding / compound drilling modes and intelligent tool face control. The intelligent switching control of sliding / compound drilling modes uses a single drill string or column as the controlled object, intelligently designing the sliding / compound drilling length of the single drill string or column to be drilled and the switching scheme between the two, which is executed by an automated actuator to achieve intelligent switching between sliding / compound drilling. The intelligent tool face control includes changing the drill pressure control tool face and the wellhead rotary drill string control tool face. Before tool face control, the tool face control parameters are intelligently designed and executed by an automated actuator to achieve intelligent closed-loop control of the tool face. This invention can avoid the large amount of non-drilling time consumed by repeated adjustments, improving drilling efficiency.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development technology, and in particular to an intelligent directional closed-loop control method and system for a curved shell screw drill bit assembly. Background Technology

[0002] Currently, wellbore trajectory control drill string assemblies for directional and horizontal wells mainly fall into two categories: curved shell screw drill string assemblies and rotary steerable drill string assemblies. Curved shell screw drill string assemblies remain the most commonly used wellbore trajectory control drill string assemblies due to their economic efficiency and adaptability to harsh downhole environments such as high temperature and high pressure.

[0003] In the wellbore trajectory control process of curved-shell screw drill string assemblies, the build-up rate is difficult to predict accurately due to the influence of numerous parameters such as drill string structure, drilling engineering parameters, existing wellbore trajectory parameters, formation parameters, and drilling fluid properties. To ensure the wellbore trajectory extends along the predetermined path, during actual drilling, on-site personnel compare the wellbore trajectory design data with the actual wellbore trajectory data measured by MWD (Mechanical Method for Drilling), and then determine the wellbore trajectory control parameters such as drilling mode, bit pressure, and tool face angle for the next well section. However, due to the zero length of MWD, the wellbore trajectory measurement data has a lag, meaning that the formulation of wellbore trajectory control parameters is often in a "catching up" and "correcting" mode relative to the designed wellbore trajectory, affecting the accuracy and timeliness of wellbore trajectory control and placing high demands on the experience of on-site personnel.

[0004] In wellbore trajectory control using curved-shell screw drill string assemblies, tool face adjustments are very frequent. The accuracy of traditional tool face adjustments is affected by factors such as formation, wellbore trajectory, wellbore structure, drill string assembly, drilling fluid system, construction parameters, screw drill string anti-torsion angle, and operator experience. It is difficult to achieve the desired result in one step, and repeated adjustments consume a significant amount of non-normal drilling time, reducing drilling efficiency. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent directional closed-loop control method and system for curved shell screw drill string assembly, in order to solve the technical problems of how to reduce the dependence on the experience of construction personnel in the wellbore trajectory control process of curved shell screw drill string, improve the wellbore trajectory control accuracy of directional and horizontal wells, shorten the drilling cycle, and realize closed-loop control of wellbore trajectory.

[0006] This invention is achieved using the following technical solution: a method for intelligent directional closed-loop control of a curved shell screw drill bit assembly, comprising intelligent switching control of sliding / compound drilling modes and intelligent tool face control, wherein,

[0007] The intelligent switching control of sliding / compound drilling mode takes a single column or column as the controlled object, intelligently designs the sliding / compound drilling length of the single column or column to be drilled and the switching scheme between the two, and executes it by an automated actuator to realize intelligent switching between sliding / compound drilling.

[0008] The intelligent control of the tool face includes changing the tool face for controlling drilling pressure and the tool face for controlling the wellhead rotary drill string. Before the tool face is controlled, the tool face control parameters are intelligently designed and executed by an automated actuator to achieve intelligent closed-loop control of the tool face.

[0009] Furthermore, the intelligent switching control of the sliding / compound drilling mode includes the following steps:

[0010] S11: Based on the interval between two MWD trajectory measurements, group the data of adjacent wells and the drilled sections of the current well;

[0011] S12: Based on the data of each group, construct and train an intelligent prediction model for the build-up rate of the sliding / composite hybrid drilling section of the curved shell screw drill string;

[0012] S13: Use a trained intelligent prediction model for inclination rate to predict the inclination rate of a single section or column to be drilled.

[0013] S14: By adjusting the sliding drilling ratio data of the single section or column to be drilled, the optimal sliding drilling ratio of the single section or column to be drilled is obtained, and sliding drilling and compound drilling are carried out.

[0014] Further, step S12 specifically involves: using the longitudinal and transverse bending continuous beam method and the limit curvature method to calculate the drill bit lateral force and limit curvature under the sliding drilling and composite drilling modes of the curved shell screw drill bit, respectively, and combining the wellbore trajectory data and the sliding drilling ratio as input parameters of the GA-BP neural network, and using the actual curvature of the wellbore trajectory as the output parameter, fitting the relationship between the input parameters and the output parameters, and constructing and training an intelligent prediction model for the build-up rate of the sliding / composite hybrid drilling section of the curved shell screw drill bit.

[0015] Furthermore, step S13 specifically involves: after the intelligent prediction model for the build-up rate reaches the preset accuracy requirements, taking a single shaft or column as the control object, and using the designed wellbore trajectory data and sliding / composite drilling pressure as the basic parameters, the lateral force and ultimate curvature of the drill bit under the sliding drilling and composite drilling modes of the single shaft or column to be drilled are calculated using the longitudinal and transverse bending continuous beam method and the ultimate curvature method, respectively. Then, combined with the designed wellbore trajectory data, and through the preset sliding drilling ratio data of the single shaft or column, the trained intelligent prediction model for the build-up rate is used to predict the build-up rate of the single shaft or column to be drilled.

[0016] Furthermore, step S14 specifically involves: by adjusting the sliding drilling ratio data of the single section or column to be drilled, when the prediction result of the intelligent prediction model of the build-up rate is consistent with the curvature of the designed wellbore trajectory, the optimal sliding drilling ratio of the single section or column to be drilled is obtained. Subsequently, the single section or column to be drilled first undergoes sliding drilling, and after completing the designed sliding drilling footage, it is switched to composite drilling. The automated actuator acquires and automatically executes the sliding / composite drilling mode switching scheme of the single section or column to be drilled.

[0017] Furthermore, the intelligent control of the tool surface includes the following steps:

[0018] In the tool face adjustment mode when the drill bit is lifted from the bottom of the well, based on the set drilling pressure during normal sliding drilling after the tool face adjustment is completed, the tool face control is completed by obtaining the relationship between the anti-torsion angle and the drilling pressure or standpipe pressure difference, as well as the relationship between the wellhead drill string rotation angle and the change value of the downhole tool face.

[0019] In the tool face adjustment mode when the drill bit is in contact with the bottom of the well, the tool face is adjusted by obtaining the relationship between the reverse torsion angle and the drill pressure or standpipe pressure difference, and the relationship between the wellhead drill string rotation angle and the change value of the downhole tool face, based on the difference between the current drill pressure and the set drill pressure range during normal sliding drilling, as well as the relationship between the wellhead drill string rotation angle and the change value of the downhole tool face.

[0020] Furthermore, obtaining the relationship between the anti-torsion angle and the drilling pressure or riser pressure differential includes the following steps:

[0021] S21: Using the wellbore trajectory, well structure, drill string assembly, drilling fluid data, drilling pressure change value or stand pressure change value, and screw drill string anti-torsion angle change data after drilling pressure or stand pressure change, the relationship between the anti-torsion of the bent shell screw drill string and the drilling pressure change value or stand pressure change value is inverted using the drill string dynamics model.

[0022] S22: Given the known changes in drill pressure or stand pressure, calculate the change in the anti-torsion angle of the bent shell screw drill bit using the drill string dynamics model, or, given the known change in the anti-torsion angle of the bent shell screw drill bit, inversely derive the change in drill pressure or stand pressure using the drill string dynamics model.

[0023] Furthermore, obtaining the relationship between the wellhead drill string rotation angle and the change value of the downhole tool face includes the following steps:

[0024] S31: Using the wellbore trajectory, well structure, drill string assembly, drilling fluid data, drilling pressure or hook load data during tool face adjustment, and top drive rotation angle and rotation speed data during tool face adjustment, the theoretical change value of the tool face is calculated by using the drill string dynamics model to change the tool face mode by rotating the drill string at the wellhead.

[0025] S32: Using the theoretical change value of the tool face and the parameters that cause the difference between the theoretical change value and the measured change value of the tool face as input parameters, and the measured change value of the tool face as output parameters, a GA-BP neural network is used to fit the relationship between the input parameters and the output parameters to construct and train an intelligent prediction model of the tool face under the known tool face control parameter conditions in the wellhead rotary drill string tool face adjustment mode.

[0026] S33: After the tool face intelligent prediction model reaches the accuracy requirements, the theoretical change value of the downhole tool face is calculated by preset the wellhead rotation angle and speed of the drill string and the drill string dynamics model. The trained tool face intelligent prediction model is then used to predict the change value of the downhole tool face.

[0027] S34: By adjusting the wellhead rotation angle and speed data, reasonable tool face control parameters are obtained when the prediction results of the tool face intelligent prediction model are within the allowable error range of the required tool face change value.

[0028] Furthermore, the intelligent control of the tool surface includes the following steps:

[0029] In the tool face adjustment mode when the drill bit is lifted from the bottom of the well, based on the set drilling pressure during normal sliding drilling after the tool face adjustment is completed, the anti-torsion angle of the screw drill string after bending the outer shell before the drill bit contacts the bottom of the well to reach the set drilling pressure during normal sliding drilling is calculated through steps S21~S22. The anti-torsion angle of the screw drill string is added to the target tool face and then subtracted from the current tool face to obtain the angle that the downhole tool face should rotate when the drill string is rotated at the wellhead to adjust the tool face. Then, the wellhead rotation angle and speed are calculated through steps S31~S34. The automated actuator executes the wellhead rotation angle and speed and lowers the drill string to reach and maintain the drilling pressure during normal sliding drilling, thus completing the tool face control in the drill bit lifting from the bottom of the well mode.

[0030] In the tool face adjustment mode when the drill bit contacts the bottom of the well, based on the difference between the current drilling pressure and the drilling pressure range set during normal sliding drilling, steps S21 to S22 determine whether the reverse torsion angle of the curved shell screw drill bit can be changed by changing the drilling pressure to make the tool face angle reach the target tool face. If the tool face can reach the target tool face by changing the drilling pressure, the drilling pressure change value is calculated and executed by the automated actuator. If the tool face cannot reach the target tool face by changing the drilling pressure, steps S31 to S34 calculate the wellhead rotation angle and rotation speed and hand them over to the automated actuator to complete the tool face control in the drill bit contacting the bottom of the well mode.

[0031] A smart directional closed-loop control system for a curved-shell screw drill bit assembly includes a dynamic measurement system, a monitoring system, an intelligent decision-making system, and an actuator.

[0032] The dynamic measurement system includes MWD, an integrated logging system, and a top drive spindle rotation positioning system. MWD is used to measure well inclination angle, azimuth angle, and the tool face angle of the screw drill under sliding drilling conditions. The integrated logging system is used to measure and record well depth, drill bit depth, drill pressure, rotation speed, standpipe pressure, and hook load in real time. The top drive spindle rotation positioning system is used to control and record the angle, speed, and direction of the top drive rotation.

[0033] The monitoring system includes a well inclination monitoring module, an azimuth monitoring module, and a tool face monitoring module. The well inclination monitoring module and the azimuth monitoring module are used to compare the actual drilling data with the designed wellbore trajectory; the tool face monitoring module is used to monitor the tool face in real time during tool face adjustment and sliding drilling.

[0034] The intelligent decision-making system is used to intelligently set wellbore trajectory control parameters;

[0035] The actuator is used to execute the trajectory control parameters set by the intelligent decision-making system.

[0036] The beneficial effects of this invention are as follows:

[0037] (1) Before drilling a single section or column, the sliding drilling ratio and the switching scheme between sliding / composite drilling have been formulated based on the intelligent prediction model of the build-up rate of the sliding / composite drilling section and the design of the wellbore trajectory, which reduces the negative impact on the accuracy of wellbore trajectory control caused by the lag in wellbore trajectory measurement data due to the zero length of MWD.

[0038] (2) Before the tool face is adjusted, the tool face control parameters have been formulated based on the drill string dynamics model and the tool face intelligent prediction model. The tool face can be quickly and accurately adjusted to the target position, avoiding the large amount of non-drilling time consumed by repeated adjustments and improving drilling efficiency.

[0039] (3) The intelligent directional closed-loop control method of the curved shell screw drill bit combination is based on artificial intelligence methods and automated drilling equipment to realize closed-loop control of wellbore trajectory, which reduces the dependence on the experience of construction personnel in the wellbore trajectory control process. Attached Figure Description

[0040] 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 the structures shown in these drawings without creative effort.

[0041] Figure 1 This is a system block diagram of the present invention;

[0042] Figure 2Flowchart for intelligent switching control of sliding / combined drilling modes;

[0043] Figure 3 Flowchart for calculating the anti-torsion angle of screw drill bits;

[0044] Figure 4 Flowchart for calculating the rotation angle and speed of the wellhead drill string in the tool face adjustment mode for rotating drill string at the wellhead. Implementation

[0045] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0046] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0047] The following detailed description of some embodiments of the present invention is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other. Example

[0048] See Figure 1 A smart directional closed-loop control system for a curved-shell screw drill assembly includes a dynamic measurement system, a monitoring system, an intelligent decision-making system, and an actuator. The dynamic measurement system comprises three parts: a dynamic measurement method (MWD), a comprehensive logging system, and a top drive spindle rotation positioning system. The MWD primarily measures the well inclination angle, azimuth angle, and the tool face angle of the screw drill in sliding drilling conditions. The well inclination angle and azimuth angle are measured at a single point, similar to traditional MWD methods, while the tool face angle of the screw drill in sliding drilling conditions is measured continuously. The comprehensive logging system measures and records data such as well depth, drill bit depth, drill pressure, rotation speed, standpipe pressure, and hook load in real time. The top drive spindle rotation positioning system controls and records the rotation angle, speed, and direction of the top drive, eliminating the need for manual wellhead calibration of the drill string angle during tool face adjustment and enabling rapid and accurate rotation of the top drive to any angle.

[0049] The monitoring system mainly consists of three parts: a well inclination monitoring module, an azimuth monitoring module, and a tool face monitoring module. After each well inclination and azimuth data measurement, the data is transmitted to the monitoring system. The well inclination and azimuth monitoring modules compare the actual drilling data with the designed wellbore trajectory. When the trajectory deviation exceeds the threshold, the monitoring system will prompt the intelligent decision-making system to make corresponding decisions to adjust the wellbore trajectory control parameters. The tool face monitoring module monitors the tool face in real time during tool face adjustment and during sliding drilling. During tool face adjustment, it monitors whether the tool face is adjusted in place, and during sliding drilling, it monitors whether the tool face angle exceeds the threshold and prompts the intelligent decision-making system to make corresponding decisions.

[0050] The intelligent decision-making system is the core of the entire intelligent directional closed-loop control method for the curved shell screw drill assembly. It is responsible for the intelligent setting of wellbore trajectory control parameters. The intelligent decision-making system stores historical data such as the trajectory and trajectory control parameters of adjacent wells and the drilled sections of the current well, as well as an artificial intelligence model trained on the above data. Each time it receives the latest measured wellbore trajectory data such as well inclination and azimuth, the intelligent decision-making system will update the trajectory data in the system, predict the build-up rate and wellbore trajectory of the well section between the current trajectory measurement and the next trajectory measurement, and inversely deduce the drilling length of the two modes of sliding drilling and composite drilling and the switching scheme between the two based on the prediction results. Before each toolface adjustment, the intelligent decision-making system, based on the given target toolface, uses the artificial intelligence model in the system to inversely deduce the wellhead drill string rotation angle and rotation speed, the required drilling pressure, and other toolface control parameters.

[0051] The actuator mainly consists of a top drive, a winch, and a top drive spindle rotary positioning system, executing the trajectory control parameters set by the intelligent decision-making system. By controlling whether the top drive rotates, the drilling mode (sliding drilling or combined drilling) can be determined; by controlling the output speed of the top drive, the drill string speed can be controlled. By controlling the rotation of the winch, the raising and lowering of the drill string and whether the drill bit contacts the bottom of the well can be controlled; by controlling the speed of the winch, the drilling pressure can be maintained at the drilling pressure value given by the intelligent decision-making system. The top drive spindle rotary positioning system can automatically rotate the top of the drill string to the required angle at a given speed during tool face adjustment.

[0052] A method for intelligent directional closed-loop control of a curved-shell screw drill string assembly is disclosed. During wellbore trajectory control, a dynamic measurement system measures various parameters in real time and transmits the measurement data to a monitoring system. The monitoring system monitors whether various trajectory control commands are correctly executed and transmits the results to an intelligent decision-making system. The intelligent decision-making system is responsible for formulating and adjusting various trajectory control commands and issuing control and adjustment commands to the actuators. The actuators are responsible for executing the various commands formulated by the intelligent decision-making system, and the execution results are measured by the dynamic measurement system. This forms a complete intelligent directional closed-loop control system for the curved-shell screw drill string assembly.

[0053] See Figures 2 to 4 A method for intelligent directional closed-loop control of a curved shell screw drill assembly includes an intelligent switching control method for sliding / compound drilling modes and an intelligent tool face control method, specifically including the following steps:

[0054] First, before drilling a certain drill string assembly, collect the wellbore trajectory and well structure data of the adjacent wells and the drilled sections of this well, as well as the drill string assemblies, comprehensive logging data, tool face control parameters, and tool face data of the drilled sections of the same formation in the adjacent wells and the same formation in this well.

[0055] Second, taking a single section or column as the control object, intelligently design the sliding / combined drilling length of the single section or column to be drilled and the switching scheme between the two, such as... Figure 2 As shown, the main steps include:

[0056] S11: Based on the interval between two MWD trajectory measurements, group the data of adjacent wells and the drilled sections of the current well;

[0057] S12: Using the longitudinal and transverse bending continuous beam method, the lateral force of the sliding drilling bit and the lateral force of the composite drilling bit in each group of data is calculated separately. Then, the limit curvature method is used to calculate the limit curvature of the sliding drilling bit and the limit curvature of the composite drilling bit in each group of data. The lateral force of the sliding drilling bit, the limit curvature of the sliding drilling bit, the lateral force of the composite drilling bit, and the limit curvature of the composite drilling bit in each group of data are combined with the bit factors, formation factors, and sliding drilling ratio as input parameters of the GA-BP neural network. The actual curvature of the wellbore trajectory is used as the output parameter. The relationship between the input parameters and the output parameters is fitted to construct and train an intelligent prediction model for the build-up rate of the sliding / composite hybrid drilling section of the curved shell screw drill tool.

[0058] S13: After the intelligent prediction model for the build-up rate reaches the accuracy requirements, a single shaft or column is used as the control object. The designed wellbore trajectory data and sliding / composite drilling pressure are used as the basic parameters. The longitudinal and transverse bending continuous beam method and the limit curvature method are used to calculate the drill bit lateral force and limit curvature under the sliding drilling and composite drilling modes of the single shaft or column to be drilled, respectively. Then, combined with drill bit factors, formation factors and the designed wellbore trajectory curvature, the trained intelligent prediction model for the build-up rate of the single shaft or column is used to predict the build-up rate of the single shaft or column to be drilled by using the preset sliding drilling ratio data of the single shaft or column.

[0059] S14: By adjusting the sliding drilling ratio data of the single section or column to be drilled, when the prediction result of the intelligent prediction model of the build-up rate is consistent with the curvature of the designed wellbore trajectory, the optimal sliding drilling ratio of the single section or column to be drilled is obtained. After that, in order to reduce the frequency of tool face control, the single section or column to be drilled first undergoes sliding drilling, and after completing the designed sliding drilling footage, it is switched to composite drilling.

[0060] Third, the intelligent design tool allows for parameter adjustment, such as... Figure 3 , Figure 4 As shown, the intelligent design of tool face adjustment parameters mainly includes the following steps:

[0061] S2: Obtain the relationship between the reverse twist angle and the drilling pressure or riser pressure differential;

[0062] S21: Using the wellbore trajectory, well structure, drill string assembly, drilling fluid data, drilling pressure change value or stand pressure change value, and screw drill string anti-torsion angle change data after drilling pressure or stand pressure change, the relationship between the anti-torsion of the bent shell screw drill string and the drilling pressure change value or stand pressure change value is inverted using the drill string dynamics model.

[0063] S22: Given the known changes in drilling pressure or stand pressure, calculate the change in the anti-torsion angle of the bent shell screw drill bit using the drill string dynamics model, or, given the known changes in the anti-torsion angle of the bent shell screw drill bit, inversely derive the change in drilling pressure or stand pressure using the drill string dynamics model.

[0064] S3: Obtain the relationship between the wellhead drill string rotation angle and the change value of the downhole tool face;

[0065] S31: Using the wellbore trajectory, well structure, drill string assembly, drilling fluid data, drilling pressure or hook load data during tool face adjustment, and top drive rotation angle and rotation speed data during tool face adjustment, the theoretical change value of the tool face is calculated by using the drill string dynamics model to change the tool face mode by rotating the drill string at the wellhead.

[0066] S32: Using the theoretical change value of the tool face and the parameters that cause the difference between the theoretical change value and the measured change value of the tool face as input parameters, and the measured change value of the tool face as output parameters, a GA-BP neural network is used to fit the relationship between the input parameters and the output parameters to construct and train an intelligent prediction model of the tool face under the known tool face control parameter conditions in the wellhead rotary drill string tool face adjustment mode.

[0067] S33: After the tool face intelligent prediction model reaches the accuracy requirements, the theoretical change value of the downhole tool face is calculated by preset the wellhead rotation angle and speed of the drill string and the drill string dynamics model. The trained tool face intelligent prediction model is then used to predict the change value of the downhole tool face.

[0068] S34: By adjusting the wellhead rotation angle and speed data, reasonable tool face control parameters are obtained when the prediction results of the tool face intelligent prediction model are within the allowable error range of the required tool face change value.

[0069] S4: In the tool face adjustment mode when the drill bit is lifted from the bottom of the well, based on the set drilling pressure during normal sliding drilling after the tool face adjustment is completed, the anti-torsion angle of the screw drill string after bending the outer shell before the drill bit contacts the bottom of the well to reach the set drilling pressure during normal sliding drilling is calculated through steps S21~S22. The anti-torsion angle of the screw drill string is added to the target tool face and then subtracted from the current tool face to obtain the angle that the downhole tool face should rotate when the drill string is rotated at the wellhead to adjust the tool face. Then, the wellhead rotation angle and speed are calculated through steps S31~S34. The automated actuator executes the wellhead rotation angle and speed, and lowers the drill string to reach and maintain the drilling pressure during normal sliding drilling, etc., to complete the tool face control in the drill bit lifting from the bottom of the well mode.

[0070] S5: In the tool face adjustment mode when the drill bit contacts the bottom of the well, based on the difference between the current drilling pressure and the drilling pressure range set during normal sliding drilling, steps S21-S22 determine whether the reverse torsion angle of the curved shell screw drill bit can be changed by changing the drilling pressure to make the tool face angle reach the target tool face. If the tool face can reach the target tool face by changing the drilling pressure, the drilling pressure change value is calculated and executed by the automated actuator. If the tool face cannot reach the target tool face by changing the drilling pressure, steps S31-S34 calculate the wellhead rotation angle and rotation speed and hand them over to the automated actuator to complete the tool face control in the drill bit contacting the bottom of the well mode.

[0071] Fourth, such as Figure 1 As shown, the designed sliding / composite drilling switching scheme and tool face control parameters are stored in the intelligent decision-making system. The intelligent decision-making system then directs the automated actuators to implement the sliding / composite drilling switching scheme and tool face control parameters.

[0072] Fifth, such as Figure 1As shown, the actuator executes the wellbore trajectory control commands issued by the intelligent decision-making system, and the dynamic measurement system records relevant data during the execution process.

[0073] Sixth, such as Figure 1 As shown, the data recorded by the dynamic measurement system is sent to the monitoring system in real time. When the monitoring system detects situations such as trajectory deviation exceeding the threshold, tool face not being adjusted properly during tool face adjustment, or tool face angle exceeding the threshold during sliding drilling, it prompts the intelligent decision-making system to make corresponding decisions.

[0074] Seventh, such as Figure 1 As shown, after drilling a single shaft or column to a certain depth, or after receiving an early warning from the monitoring system, the intelligent decision-making system will formulate the next stage of sliding / compound drilling switching scheme and tool face control parameters.

[0075] Based on the above embodiments, the present invention has at least the following technical effects:

[0076] (1) Before drilling a single section or column, the sliding drilling ratio and the switching scheme between sliding / composite drilling have been formulated based on the intelligent prediction model of the build-up rate of the sliding / composite drilling section and the design of the wellbore trajectory, which reduces the negative impact on the accuracy of wellbore trajectory control caused by the lag in wellbore trajectory measurement data due to the zero length of MWD.

[0077] (2) Before the tool face is adjusted, the tool face control parameters have been formulated based on the drill string dynamics model and the tool face intelligent prediction model. The tool face can be quickly and accurately adjusted to the target position, avoiding the large amount of non-drilling time consumed by repeated adjustments and improving drilling efficiency.

[0078] (3) The intelligent directional closed-loop control method of the curved shell screw drill bit combination is based on artificial intelligence methods and automated drilling equipment to realize closed-loop control of wellbore trajectory, which reduces the dependence on the experience of construction personnel in the wellbore trajectory control process.

[0079] It should be noted that, for the sake of simplicity, the foregoing embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to this application.

[0080] The above embodiments describe the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Modifications and variations made by those skilled in the art without departing from the spirit and scope of the invention should be within the protection scope of the appended claims.

Claims

1. A method for intelligent directional closed-loop control of a curved-shell screw drill assembly, characterized in that, This includes intelligent switching control between sliding / combined drilling modes and intelligent tool face adjustment, among which, The intelligent switching control of sliding / compound drilling mode takes a single column or column as the controlled object, intelligently designs the sliding / compound drilling length of the single column or column to be drilled and the switching scheme between the two, and executes it by an automated actuator to realize intelligent switching between sliding / compound drilling. The intelligent control of the tool face includes changing the drilling pressure control tool face and the wellhead rotary drill string control tool face. Before the tool face control, the tool face control parameters are intelligently designed and executed by the automated actuator to achieve intelligent closed-loop control of the tool face. The intelligent control of the tool surface includes the following steps: In the tool face adjustment mode when the drill bit is lifted from the bottom of the well, based on the set drilling pressure during normal sliding drilling after the tool face adjustment is completed, the tool face control is completed by obtaining the relationship between the reverse twist angle and the drilling pressure or standpipe pressure difference, as well as the relationship between the wellhead drill string rotation angle and the change value of the downhole tool face. In the tool face adjustment mode when the drill bit contacts the bottom of the well, the tool face control is completed by obtaining the relationship between the reverse twist angle and the drill pressure or standpipe pressure difference, and the relationship between the wellhead drill string rotation angle and the change value of the downhole tool face, based on the difference between the current drill pressure and the set drill pressure range during normal sliding drilling. The process of obtaining the relationship between the wellhead drill string rotation angle and the downhole tool face change includes the following steps: S31: Using the wellbore trajectory, well structure, drill string assembly, drilling fluid data, drilling pressure or hook load data during tool face adjustment, and top drive rotation angle and rotation speed data during tool face adjustment, the theoretical change value of the tool face is calculated by using the drill string dynamics model to change the tool face mode by rotating the drill string at the wellhead. S32: Using the theoretical change value of the tool face and the parameters that cause the difference between the theoretical change value and the measured change value of the tool face as input parameters, and the measured change value of the tool face as output parameters, a GA-BP neural network is used to fit the relationship between the input parameters and the output parameters to construct and train an intelligent prediction model of the tool face under the known tool face control parameter conditions in the wellhead rotary drill string tool face adjustment mode. S33: After the tool face intelligent prediction model reaches the accuracy requirements, the theoretical change value of the downhole tool face is calculated by preset the wellhead rotation angle and speed of the drill string and the drill string dynamics model. The trained tool face intelligent prediction model is then used to predict the change value of the downhole tool face. S34: By adjusting the wellhead rotation angle and speed data, reasonable tool face control parameters are obtained when the prediction results of the tool face intelligent prediction model are within the allowable error range of the required tool face change value.

2. The intelligent directional closed-loop control method for a curved outer shell screw drill bit assembly as described in claim 1, characterized in that, The intelligent switching control of the sliding / combined drilling mode includes the following steps: S11: Based on the interval between two MWD trajectory measurements, group the data of adjacent wells and the drilled sections of the current well; S12: Based on the data of each group, construct and train an intelligent prediction model for the build-up rate of the sliding / composite hybrid drilling section of the curved shell screw drill string; S13: Use a trained intelligent prediction model for inclination rate to predict the inclination rate of a single section or column to be drilled. S14: By adjusting the sliding drilling ratio data of the single section or column to be drilled, the optimal sliding drilling ratio of the single section or column to be drilled is obtained, and sliding drilling and compound drilling are carried out.

3. The intelligent directional closed-loop control method for a curved outer shell screw drill bit assembly as described in claim 2, characterized in that, Step S12 specifically involves: using the longitudinal and transverse bending continuous beam method and the limit curvature method to calculate the drill bit lateral force and limit curvature under the sliding drilling and composite drilling modes of the curved shell screw drill bit for each group of data. The wellbore trajectory data and the sliding drilling ratio are used as input parameters of the GA-BP neural network, and the actual curvature of the wellbore trajectory is used as the output parameter. The relationship between the input parameters and the output parameters is fitted to construct and train an intelligent prediction model for the build-up rate of the sliding / composite hybrid drilling section of the curved shell screw drill bit.

4. The intelligent directional closed-loop control method for a curved outer shell screw drill bit assembly as described in claim 2, characterized in that, Step S13 specifically involves: after the intelligent prediction model for the build-up rate reaches the preset accuracy requirements, taking a single shaft or column as the control object, and using the designed wellbore trajectory data and sliding / composite drilling pressure as the basic parameters, the lateral force and ultimate curvature of the drill bit under the sliding drilling and composite drilling modes of the single shaft or column to be drilled are calculated using the longitudinal and transverse bending continuous beam method and the ultimate curvature method, respectively. Then, combined with the designed wellbore trajectory data, and through the preset sliding drilling ratio data of the single shaft or column, the trained intelligent prediction model for the build-up rate is used to predict the build-up rate of the single shaft or column to be drilled.

5. The intelligent directional closed-loop control method for a curved outer shell screw drill bit assembly as described in claim 2, characterized in that, Step S14 specifically involves adjusting the sliding drilling ratio data of the single section or column to be drilled. When the prediction result of the intelligent prediction model of the build-up rate is consistent with the curvature of the designed wellbore trajectory, the optimal sliding drilling ratio of the single section or column to be drilled is obtained. Subsequently, the single section or column to be drilled first undergoes sliding drilling. After completing the designed sliding drilling footage, it is then switched to composite drilling. The automated actuator acquires and automatically executes the sliding / composite drilling mode switching scheme of the single section or column to be drilled.

6. The intelligent directional closed-loop control method for a curved outer shell screw drill bit assembly as described in claim 1, characterized in that, The process of obtaining the relationship between the anti-torsion angle and the drilling pressure or riser pressure differential includes the following steps: S21: Using the wellbore trajectory, well structure, drill string assembly, drilling fluid data, drilling pressure change value or stand pressure change value, and screw drill string anti-torsion angle change data after drilling pressure or stand pressure change, the relationship between the anti-torsion of the bent shell screw drill string and the drilling pressure change value or stand pressure change value is inverted using the drill string dynamics model. S22: Given the known changes in drill pressure or stand pressure, calculate the change in the anti-torsion angle of the bent shell screw drill bit using the drill string dynamics model, or, given the known change in the anti-torsion angle of the bent shell screw drill bit, inversely derive the change in drill pressure or stand pressure using the drill string dynamics model.

7. The intelligent directional closed-loop control method for a curved outer shell screw drill bit assembly as described in claim 6, characterized in that, The intelligent control of the tool surface includes the following steps: In the tool face adjustment mode when the drill bit is lifted from the bottom of the well, based on the set drilling pressure during normal sliding drilling after the tool face adjustment is completed, the anti-torsion angle of the screw drill string after bending the outer shell before the drill bit contacts the bottom of the well to reach the set drilling pressure during normal sliding drilling is calculated through steps S21~S22. The anti-torsion angle of the screw drill string is added to the target tool face and then subtracted from the current tool face to obtain the angle that the downhole tool face should rotate when the drill string is rotated at the wellhead to adjust the tool face. Then, the wellhead rotation angle and speed are calculated through steps S31~S34. The automated actuator executes the wellhead rotation angle and speed and lowers the drill string to reach and maintain the drilling pressure during normal sliding drilling, thus completing the tool face control in the drill bit lifting from the bottom of the well mode. In the tool face adjustment mode when the drill bit contacts the bottom of the well, based on the difference between the current drilling pressure and the drilling pressure range set during normal sliding drilling, steps S21 to S22 determine whether the reverse torsion angle of the curved shell screw drill bit can be changed by changing the drilling pressure to make the tool face angle reach the target tool face. If the tool face can reach the target tool face by changing the drilling pressure, the drilling pressure change value is calculated and executed by the automated actuator. If the tool face cannot reach the target tool face by changing the drilling pressure, steps S31 to S34 calculate the wellhead rotation angle and rotation speed and hand them over to the automated actuator to complete the tool face control in the drill bit contacting the bottom of the well mode.

8. A smart directional closed-loop control system for a curved housing screw drill bit assembly, used to implement the smart directional closed-loop control method for a curved housing screw drill bit assembly as described in any one of claims 1 to 7, characterized in that, It includes dynamic measurement systems, monitoring systems, intelligent decision-making systems, and execution mechanisms, among which, The dynamic measurement system includes MWD, an integrated logging system, and a top drive spindle rotation positioning system. MWD is used to measure well inclination angle, azimuth angle, and the tool face angle of the screw drill under sliding drilling conditions. The integrated logging system is used to measure and record well depth, drill bit depth, drill pressure, rotation speed, standpipe pressure, and hook load in real time. The top drive spindle rotation positioning system is used to control and record the angle, speed, and direction of the top drive rotation. The monitoring system includes a well inclination monitoring module, an azimuth monitoring module, and a tool face monitoring module. The well inclination monitoring module and the azimuth monitoring module are used to compare the actual drilling data with the designed wellbore trajectory; the tool face monitoring module is used to monitor the tool face in real time during tool face adjustment and sliding drilling. The intelligent decision-making system is used to intelligently set wellbore trajectory control parameters; The actuator is used to execute the trajectory control parameters set by the intelligent decision-making system.

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