Anti-deviation detection device for drill bit of rock sinking ship and inclined rock drilling method

Abstract

The invention discloses an anti-deviation detection device and an inclined rock drilling method for a drill bit of a rock sinking ship, and belongs to the technical field of offshore oil and gas engineering. The method comprises the following steps: acquiring high-frequency shaking input of a ship body, and a mixed posture, a bending moment, a torque and an axial expansion and contraction amount between an underground drill rod and the drill bit; based on the system dynamics model and ship body shaking, the equivalent damping of the model is dynamically corrected through the axial expansion amount reflecting the drilling pressure and the contact tightness; the equivalent transverse stiffness of the model is dynamically corrected by using a torque signal reflecting the torsional stress and the transverse stiffness reduction; and subtracting the prediction interference from the underground mixed attitude, performing state estimation by combining a bending moment signal, outputting pure real trajectory deviation, and generating a smooth deviation correction instruction according to the pure real trajectory deviation. According to the method, the prediction precision of underground high-frequency shaking is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of marine oil and gas engineering, specifically to an anti-deviation detection device for drill bits on rock drilling vessels and a method for drilling inclined rocks. Background Technology

[0002] With the continuous development of marine engineering drilling operations, the precision requirements for drilling vessels have significantly increased. The complex operating environment of rock drills, with high-frequency swaying caused by wave undulations, presents many challenges to the drilling process, especially in terms of drilling accuracy management and trajectory deviation monitoring. Currently, attempts are made to stabilize the drill bit trajectory using control systems or guidance tools. However, in traditional drilling control methods, the high-frequency swaying of the hull due to wave undulations severely masks the true low-frequency trajectory deviation caused by geological factors, such as the boundary between soft and hard rock layers and changes in the dip angle of the formation. This mixture of high-frequency interference and low-frequency deviation signals makes it difficult for the control system to distinguish between the two. Specifically, existing methods exhibit the following phenomena and defects: Low signal-to-noise ratio: The data collected by the actual attitude sensor of the drill bit is the sum of the hull rolling effect and the actual deviation, i.e., a mixed attitude reading, in which hull rolling accounts for the main, higher frequency energy component; Inaccurate correction action: Because the control system cannot effectively separate the high-frequency rolling component from the mixed signal, it over-responds or misjudges the high-frequency rolling, generating uneven and unstable correction action commands; Decreased accuracy: This over-response to high-frequency interference affects the accuracy of the borehole trajectory and may aggravate the fatigue damage of the drill string.

[0003] Therefore, how to separate the pure true trajectory deviation signal from the mixed attitude readings in a timely and accurate manner has become a key problem that urgently needs to be solved in this field.

[0004] The information disclosed in the background section above is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide an anti-deviation detection device for drill bits on rock drill ships and a method for drilling inclined rocks, so as to solve the problems mentioned in the background art. Specifically, the technical solution of this invention includes: Data acquisition: High-frequency hull sway input is acquired by the surface motion reference unit mounted on the drilling feed mechanism; simultaneously, downhole mixed attitude readings, bending moment and torque signals, and axial extension are acquired by the differential motion sensing sub connected in series between the drill string end and the drill bit. Interference prediction: Based on the preset system dynamics model and the high-frequency sway input of the hull, the equivalent damping parameter of the model is dynamically corrected by the axial extension and the equivalent lateral stiffness parameter of the model is dynamically corrected by the torque signal, and the predicted downhole high-frequency sway attitude is output as a pure interference component. Decoupling estimation: Subtract the predicted downhole high-frequency swaying attitude from the downhole mixed attitude reading to obtain a preliminary trajectory deviation signal; input the preliminary trajectory deviation signal and the bending moment signal into the state estimation algorithm to output a clean true trajectory deviation; Generate instruction: Input the pure real trajectory deviation into the controller to generate a smooth correction action instruction.

[0006] Preferably, the step of dynamically correcting the equivalent lateral stiffness parameter of the model using the torque signal specifically includes: The current torsional stress level of the drill string is calculated based on the torque signal. The built-in torsional stress-lateral stiffness conversion relationship is used to calculate the dynamic stiffness reduction factor; The equivalent lateral stiffness parameter in the model is reduced using the dynamic stiffness reduction factor.

[0007] Preferably, the conversion relationship between torsional stress and lateral stiffness is obtained through calibration on a land-based test bench.

[0008] Preferably, the logic of the state estimation algorithm includes: When the bending moment signal shows a continuous and stable increase, the confidence level in the initial trajectory deviation signal is increased; Preferably, the system dynamics model is pre-established based on the material, geometry, and boundary conditions of the drill string using the finite element analysis method.

[0009] A device for preventing deviation detection of drill bits on rock drilling vessels, the device comprising: A surface motion reference unit, installed on the drilling feed mechanism, is used to acquire high-frequency hull sway input; The differential motion sensing sub is connected in series between the end of the drill string and the drill bit to acquire downhole mixed attitude readings, bending moment and torque signals, and axial extension / retraction. The controller is configured to receive data from the surface motion reference unit and the differential motion sensing section, and to perform the steps of interference prediction, decoupling estimation and instruction generation.

[0010] Preferably, the surface motion reference unit includes an integrated multi-axis inertial measurement unit and motion reference unit.

[0011] Preferably, the differential motion sensing section includes: The outer casing is used to connect the drill string above; An inner mandrel passes through the outer housing, and its lower end is used to connect to a drill bit. The inner mandrel can produce slight axial and radial relative displacement within the outer housing. An axial displacement sensor group is installed between the outer housing and the inner spindle to measure the axial expansion and contraction. A bending moment and torque sensing assembly is mounted on the surface of the inner mandrel and is used to measure the bending moment and torque signals; A downhole attitude gauge, installed inside the inner mandrel, is used to measure the downhole mixed attitude reading.

[0012] Preferably, the axial displacement sensor group is a set of linear variable differential transformers.

[0013] Preferably, the bending moment and torque sensing group consists of multiple Wheatstone bridge strain gauges.

[0014] The present invention provides an improved anti-deviation detection device for drill bits on rock drilling vessels and a method for drilling inclined rocks, which, compared with the prior art, has the following improvements and advantages: 1. This scheme acquires the high-frequency sway input of the hull through a surface motion reference unit and synchronously acquires axial extension and torque signals using a differential motion sensing sub. In the interference prediction step, the axial extension is used to dynamically correct the equivalent damping parameters of the system dynamics model, and the torque signal is used to dynamically correct the equivalent lateral stiffness parameters of the model. This dynamic parameter correction, i.e., damping and stiffness, enables the preset system dynamics model to accurately calculate and output the predicted downhole high-frequency sway attitude. As a pure interference component, in the decoupling estimation step, the predicted high-frequency sway attitude is subtracted from the downhole mixed attitude reading, thus achieving the separation of high-frequency interference and overcoming the limitation of the preset dynamics model parameters remaining static in traditional methods. By dynamically correcting the key parameters of the model through real-time downhole parameters, the model's prediction accuracy for interference transmission is significantly improved. 2. Because the bending moment signal is used as a criterion for weighting or smoothing the deviation signal, random downhole vibration noise is further filtered out on the basis of removing high-frequency interference. This results in a higher signal-to-noise ratio for the output pure true trajectory deviation signal, thus ensuring that the correction action is only for the true deviation caused by stable lateral force. Attached Figure Description

[0015] The present invention will be further explained below with reference to the accompanying drawings and embodiments: Figure 1 This is a schematic diagram of the overall structure of the device; Figure 2 This is a schematic diagram of the external structure of the inner mandrel; Figure 3This is a schematic diagram of the downhole attitude device; Figure 4 This is a schematic diagram of the process flow of the method of the present invention.

[0016] In the diagram: 100, Surface motion reference unit; 110, High-frequency motion sensor group; 200, Differential motion sensing sub; 210, Outer shell; 220, Inner spindle; 230, Axial displacement sensor group; 240, Bending moment and torque sensing group; 250, Downhole attitude instrument; 300, Controller. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments. Example

[0018] Please see Figure 1-4 This invention provides a drilling method for preventing drill bit deviation in rock drilling vessels, comprising the following steps: Data acquisition: High-frequency hull sway input is acquired by the surface motion reference unit 100 installed on the drilling feed mechanism; Simultaneously, downhole mixed attitude readings, bending moment and torque signals, and axial extension are acquired by the differential motion sensing sub 200 connected in series between the drill string end and the drill bit. Interference prediction: Based on the preset system dynamics model and the high-frequency sway input of the hull, the equivalent damping parameters of the model are dynamically corrected by the axial extension and the equivalent lateral stiffness parameters of the model are dynamically corrected by the torque signal, and the predicted downhole high-frequency sway attitude is output as the pure interference component. Decoupling estimation: Subtract the predicted downhole high-frequency swaying attitude from the downhole mixed attitude readings to obtain the preliminary trajectory deviation signal; input the preliminary trajectory deviation signal and the bending moment signal into the state estimation algorithm to output the pure true trajectory deviation; Generate instruction: Input the pure, true trajectory deviation into the controller 300 to generate a smooth correction action instruction.

[0019] In the step of generating instructions, after receiving the pure true trajectory deviation, the controller 300 further processes the deviation signal by using a low-pass filter and combines it with a preset dynamic correction strategy, such as PID control or model predictive control, to output a smooth correction action instruction with limited rate of change and no high-frequency components, so as to avoid over-responding to high-frequency noise and reduce the impact on the actuator. This embodiment provides a drilling method for preventing drill bit deviation in rock drilling vessels. It aims to address the problem that during drilling operations, the high-frequency swaying of the hull caused by wave undulations can severely mask the actual low-frequency trajectory deviation of the drill bit due to formation factors, making it difficult for the control system to distinguish between the two. The data acquisition step of this method, through the cooperation of a surface motion reference unit 100 and a differential motion sensing sub-section 200, simultaneously collects information on the hull swaying (an interference source) and the actual motion and force information at the end of the downhole drill string. The interference prediction step utilizes two real-time downhole parameters—axial extension and torque signals—to dynamically correct key parameters of the preset system dynamics model, namely damping and stiffness, enabling it to accurately calculate the predicted downhole high-frequency swaying attitude transmitted from the hull swaying to the drill bit.

[0020] The principle behind correcting the equivalent damping parameter is that the axial extension directly reflects the real-time axial drilling pressure borne by the drill bit. The magnitude of this drilling pressure determines the contact state between the drill bit and the rock, as well as the tightness of contact between the lower part of the drill string and the borehole wall. When the axial extension is large, i.e., the drilling pressure is high, the drill bit fully engages with the rock, and the frictional effect between the lower part of the drill string and the borehole wall is also enhanced. At this time, the overall equivalent damping of the system, especially the damping from the rock fracturing process and contact friction, is at a high level. Conversely, when the axial extension is small, such as when the drill bit is suspended or just in contact with the rock surface, this damping generated by engagement and friction is significantly reduced.

[0021] Therefore, the controller 300 can have a built-in conversion relationship between axial expansion and equivalent damping. This conversion relationship can be obtained in advance by extending the finite element analysis model, adding the nonlinear relationship between drilling pressure and damping to the model, or by using a method similar to the calibration of a land test bench, i.e., applying different axial pressures on the test bench and measuring the damping response of the system. During operation, the controller 300 calls this conversion relationship based on the measured axial expansion to calculate the dynamic damping coefficient value, and uses this value to update the equivalent damping parameters in the dynamic model in real time.

[0022] The axial expansion / contraction-equivalent damping conversion relationship is a dynamic, nonlinear conversion table or function used to quantify in real time the degree of drill bit-rock engagement and drill string-hole wall friction effect caused by changes in drilling pressure, thereby characterizing the overall system's damping magnitude for lateral vibration. This relationship is derived by correlating the measured axial expansion / contraction with the equivalent damping coefficient curve obtained beforehand through onshore test bench calibration or extended finite element analysis; it reflects the physical law that higher drilling pressure results in higher equivalent system damping. The controller 300 uses the dynamic damping coefficient value derived from this relationship as logical input to update the equivalent damping parameters in the disturbance prediction model and system dynamics model in real time, ensuring the accuracy of the model's prediction of high-frequency disturbance components transmitted downhole by hull sway. This dynamic correction to damping, combined with the correction to stiffness, improves the model's accuracy in predicting high-frequency swaying attitudes downhole.

[0023] The core of the decoupling estimation step lies in removing the predicted interference component from the mixed attitude readings in the wellbore and using the bending moment signal as a criterion to estimate the pure true trajectory deviation from the remaining signal. The command generation step ensures that the controller 300 only responds to this true, low-frequency trajectory deviation, generating smooth correction commands. This method accurately separates high-frequency interference from low-frequency deviation through a dynamically corrected model, ensuring that the correction action targets only the true borehole trajectory deviation, improving the accuracy of drilling in complex sea conditions, while avoiding over-response to high-frequency oscillations.

[0024] The specific steps for dynamically correcting the equivalent lateral stiffness parameters of the model using torque signals include: The current torsional stress level of the drill string is calculated based on the torque signal. The built-in torsional stress-lateral stiffness conversion relationship is used to calculate the dynamic stiffness reduction factor; Use the dynamic stiffness reduction factor to lower the equivalent lateral stiffness parameter in the model.

[0025] The purpose of dynamically correcting the equivalent lateral stiffness parameter of the model using torque signals is to address the issue that the lateral mechanical properties of the drill string change under different torques, i.e., the torsional state of the drill string affects its ability to resist lateral deformation. Specifically, the controller 300 monitors the torque signal in real time and calculates the current torsional stress level of the drill string based on the torque signal. For example, when the torque signal increases significantly, it is determined that the drill string may be in a stuck state, and the torsional stress level increases. The controller 300 calls the built-in torsional stress-lateral stiffness conversion relationship, which reflects the physical phenomenon that the higher the torsional stress, the lower the equivalent lateral stiffness of the drill string. Based on this relationship, a dynamic stiffness reduction factor is calculated and used to lower the equivalent lateral stiffness parameter in the model. The purpose of this correction is to make the prediction of the system dynamics model more accurate, because the response of a high-stress, low-stiffness drill string to hull rolling, i.e., the disturbance transmission, is different from that of a low-stress, high-stiffness drill string. This dynamic parameter adjustment based on actual working conditions improves the fidelity of the disturbance prediction step.

[0026] The conversion relationship between torsional stress and lateral stiffness was obtained through calibration on a land-based test bench.

[0027] To ensure its accuracy in practical applications, the conversion relationship between torsional stress and lateral stiffness was calibrated on a land-based test bench. In the controlled environment of the test bench, a test specimen of the same specifications as an actual drill string was simultaneously subjected to controllable axial pressure, different levels of torsional loads, and known lateral excitation. Sensors measured the test specimen's response to lateral excitation under different torsional load levels, thus data-driven fitting of the correspondence between torsional stress and equivalent lateral stiffness. Using the calibrated relationship, rather than purely theoretical derivation, ensures that the conversion relationship fully considers complex factors such as material nonlinearity and joint effects. This allows it to provide a stiffness reduction factor closer to physical reality when invoked in the controller 300, providing a reliable data basis for dynamically correcting model parameters.

[0028] The conversion relationship between torsional stress and lateral stiffness is an empirical relationship table or function with inverse correlation, used to quantify in real time the drill string's ability to resist lateral deformation under the current torsional stress level, i.e., the degree of lateral stiffness reduction. The input to this relationship is the torsional stress level calculated based on the real-time torque signal, and the output is the dynamic stiffness reduction coefficient. This relationship was obtained through calibration on an onshore test bench, and it characterizes the physical phenomenon that the higher the torsional stress, the lower the equivalent lateral stiffness of the drill string. The controller 300 uses the dynamic stiffness reduction coefficient calculated from this relationship to lower the equivalent lateral stiffness parameter in the system dynamics model. This is the key logic to ensure that the model accurately predicts the downhole high-frequency swaying attitude under different drilling torque conditions. The logic of the state estimation algorithm includes: When the bending moment signal shows a continuous and stable increase, increase the confidence level in the initial trajectory deviation signal; When the bending moment signal is chaotic, smooth the initial trajectory deviation signal.

[0029] The logical design of the state estimation algorithm aims to further separate the true low-frequency deviation and random downhole vibration noise from the initial trajectory deviation signal, which has already been freed from high-frequency swaying interference. This algorithm relies on the bending moment signal as a criterion, as the bending moment directly reflects the lateral force acting on the drill bit. When the bending moment signal shows a continuous and stable increase, it physically indicates that the drill bit is continuously subjected to a stable thrust from a certain rock layer. This thrust is the root cause of the true deviation, so the algorithm increases its confidence in the initial trajectory deviation signal, assuming that the deviation signal at this time mainly reflects the true deviation. Conversely, when the bending moment signal is chaotic, it indicates that the drill bit is only experiencing random, brief impacts, not continuous lateral forces. In this case, the algorithm judges that the initial trajectory deviation signal contains a large noise component and smooths it, for example, by using low-pass filtering or weighted averaging to filter out the noise. This estimation method, which combines bending moment signal for judgment, results in a higher signal-to-noise ratio for the output pure true trajectory deviation signal. It only responds to those true trajectory deviations that need to be corrected due to stable lateral forces, without misjudging random vibrations.

[0030] The state estimation algorithm receives two main logical inputs: a preliminary trajectory deviation signal, minus predicted high-frequency swaying interference and a bending moment signal, reflecting the magnitude and duration of the lateral force on the drill bit. The logical steps include: Step 1: Duration assessment; the algorithm performs time-series analysis on the input bending moment signal to evaluate whether it exhibits a continuous and stable increasing trend, indicating the presence of stable lateral thrust, i.e., true deviation. Step 2: Noise assessment; if the bending moment signal exhibits chaotic instantaneous impacts, it indicates the presence of random downhole vibration noise. Step 3: Confidence weighting; if the assessment indicates a continuous and stable increase, the algorithm increases the confidence level of the preliminary trajectory deviation signal, i.e., increases its weight or does not perform smoothing. Step 4: Smoothing; if the assessment indicates chaos, the algorithm smooths the preliminary trajectory deviation signal, for example, by using low-pass filtering or weighted averaging to filter out random noise. The final output of the process is the clean, true trajectory deviation, which is then transmitted to the controller 300 to generate a correction command. The system dynamics model is established in advance based on the material, geometry, and boundary conditions of the drill string using the finite element analysis method.

[0031] The system dynamics model is the foundation of the entire disturbance prediction process. To accurately describe the complex motion transmission from hull swaying to the downhole drill bit, this model is pre-established using the finite element method (FEM) based on the drill string's material, geometry, and boundary conditions. Model building requires inputting material and geometric information such as the drill string's elastic modulus, density, and the inner and outer diameters and lengths of each drill string section. Crucially, it involves setting boundary conditions, such as the contact between the drill string and the borehole wall, the added mass effect from the drilling fluid, and fluid damping effects. Solving this complex dynamic system using finite element software yields a transfer function or state-space model that describes the relationship between the hull swaying input, excitation, and drill bit attitude response, as well as the output. Compared to a simplified lumped parameter model, the model built using the finite element method more precisely reflects the vibration characteristics of the drill string as a flexible body in a fluid environment. This pre-established high-fidelity model provides an accurate foundation for subsequent dynamic parameter correction using axial extension and torque signals.

[0032] The purpose of the system dynamics model is to accurately describe how the high-frequency swaying input of the hull is transmitted to the downhole drill bit through the drill string and drilling fluid environment, and ultimately manifests as a downhole high-frequency swaying attitude, a pure disturbance component. Logically, this model is a state-space model or a transfer function model. It receives the high-frequency swaying input of the hull as excitation and combines dynamically corrected equivalent damping parameters and equivalent lateral stiffness parameters as model characteristic inputs. The model internally calculates the vibration and wave propagation characteristics of the drill string as a flexible body, and the model outputs the predicted downhole high-frequency swaying attitude. Overall, this model characterizes the drill string as a continuous elastic body, under fluid environment and boundary conditions, such as drill bit contact with rock and drill string friction constraints with borehole wall, the complex vibration transmission path and dynamic characteristics of high-frequency motion excitation from the hull being attenuated and delayed. Example

[0033] Please see Figure 1-3 A device for preventing deviation of drill bits on rock drilling vessels, comprising: The surface motion reference unit 100 is installed on the drilling feed mechanism to acquire high-frequency hull sway input; The differential motion sensing sub 200 is connected in series between the end of the drill string and the drill bit to acquire downhole mixed attitude readings, bending moment and torque signals, and axial extension / retraction. Controller 300, as the computing core of the system, has additional functions in the attached... Figure 1 The physical location is for illustrative purposes only. Physically, it can be set on the hull surface or integrated into the downhole tool as needed. It is used to receive data from the surface motion reference unit 100 and the differential motion sensing sub 200, and to perform the steps of interference prediction, decoupling estimation and command generation.

[0034] A deviation detection device for drill bits on rock drilling vessels, using the method described above, comprises a surface motion reference unit 100 mounted on the drilling feed mechanism. This unit moves with the hull and its function is to acquire high-frequency hull sway input. A differential motion sensing section 200 is connected in series between the drill string end and the drill bit. This position allows it to sensitively acquire downhole mixed attitude readings, bending moment and torque signals, and axial extension / retraction, data reflecting the actual motion and forces acting on the near end of the drill bit. A controller 300 is connected to the first two units via a data cable or acoustic communication system to receive their data and serves as the core of the calculation, incorporating algorithmic logic to perform disturbance prediction, decoupling estimation, and command generation. This system, through a combination of surface and downhole sensors and in conjunction with a specific algorithm from the controller 300, achieves dynamic monitoring and separation of borehole deviation. It can distinguish between hull sway disturbances and actual trajectory deviations, thus providing accurate control basis for subsequent deviation correction mechanisms, such as dynamic positioning systems or guidance tools (not shown).

[0035] The controller 300 can be implemented in hardware as an industrial-grade embedded computer or a high-speed digital signal processor, and it incorporates specific algorithm software modules for performing interference prediction, decoupling estimation, and instruction generation steps. The controller 300 is connected to the surface motion reference unit 100 and the differential motion sensing section 200 via a high-speed data cable or an acoustic communication system to receive data. The surface motion reference unit 100 includes an integrated multi-axis inertial measurement unit and motion reference unit.

[0036] The surface motion reference unit 100 includes an integrated multi-axis inertial measurement unit and motion reference unit, wherein the multi-axis inertial measurement unit is the high-frequency motion sensor group 110 shown in the attached drawings; In this system, the surface motion reference unit 100, in order to accurately measure the complex motion of the hull, is specifically implemented by an integrated multi-axis inertial measurement unit (IMU) and motion reference unit. The IMU typically includes a gyroscope and an accelerometer, such as the ADIS16488, for high-frequency sampling of the hull's angular velocity and linear acceleration. The motion reference unit is a dedicated sensor, such as the SeatexMRU5 based on MEMS or fiber optic gyroscope technology. It can directly output the pitch, roll, and heave motion data generated by the hull in waves by integrating and filtering the raw IMU data, i.e., the high-frequency hull sway input mentioned above. Using an integrated IMU and MRU as the specific implementation of the surface motion reference unit 100 can provide high-frequency, high-precision hull attitude and motion data, which is a necessary input prerequisite for the system dynamics model to accurately predict disturbances.

[0037] The differential motion sensing section 200 includes: The outer casing 210 is used to connect the upper drill string; The inner mandrel 220 passes through the outer casing 210, and its lower end is used to connect the drill bit. The inner mandrel 220 can produce small axial and radial relative displacements within the outer casing 210. An axial displacement sensor group 230 is installed between the outer housing 210 and the inner spindle 220 and is used to measure axial expansion and contraction. A moment and torque sensing assembly 240 is mounted on the surface of the inner spindle 220 and is used to measure moment and torque signals. The downhole attitude gauge 250 is installed inside the inner spindle 220 and is used to measure downhole mixed attitude readings.

[0038] The structural design of the differential motion sensing sub 200 is crucial for realizing downhole differential measurement. It comprises an outer shell 210 and an inner mandrel 220. The outer shell 210, connected to the drill string above via a standard drill pipe connector, represents the motion of the drill string body. The inner mandrel 220 passes through the outer shell 210, with its lower end connected to the drill bit, representing the motion of the proximal end of the drill bit. The core of this inner and outer shell structure design lies in the fact that the inner mandrel 220 can generate minute axial and radial relative displacements within the outer shell 210. This relative displacement accurately reflects the elastic deformation of the drill string end, i.e., the portion between the inner mandrel 220 and the outer shell 210, under drilling pressure, torque, and lateral forces. An axial displacement sensor group 230, mounted between the outer shell 210 and the inner mandrel 220, measures axial expansion and contraction, i.e., axial relative displacement. A bending moment and torque sensor group 240 is mounted on the surface of the inner mandrel 220 to measure its stress-induced deformation. The downhole attitude instrument 250, such as a set of low-frequency response inclinometers and gyroscopes, is installed inside the inner mandrel 220 and moves with the drill bit to measure downhole mixed attitude readings. This structure, by measuring the relative displacement between the inner and outer shafts and the absolute force and attitude of the inner shaft, simultaneously acquires all key downhole data, such as axial extension and torque for correcting the model, as well as mixed attitude and bending moment for decoupling, within an integrated short section.

[0039] The axial displacement sensor group 230 is a set of linear variable differential transformers.

[0040] To accurately measure the minute axial relative displacement between the outer casing 210 and the inner mandrel 220, the axial displacement sensor group 230 is, in one specific implementation, a set of linear variable differential transformers (LVDTs). An LVDT is a high-precision non-contact displacement sensor, such as the HGSLVDT-1000 model, whose core is fixed to the end of the inner mandrel 220, and the coil is fixed to the corresponding position on the outer casing 210. When the inner mandrel 220 undergoes axial expansion or contraction relative to the outer casing 210, the position of the core within the coil changes, and the voltage signal output by the LVDT changes linearly accordingly. The LVDT is chosen as the specific implementation of the axial displacement sensor because of its robust structure, high pressure resistance, vibration resistance, and high resolution, which can meet the requirement of reliable measurement of minute elastic expansion and contraction of the drill string in harsh downhole conditions, providing accurate input for the correction of damping parameters in the dynamic model.

[0041] The moment and torque sensing group 240 consists of multiple Wheatstone bridge strain gauges.

[0042] To simultaneously measure the lateral bending moment and rotational torque experienced by the inner mandrel 220, the moment and torque sensing group 240, in one specific implementation, consists of multiple sets of Wheatstone bridge strain gauges. These strain gauges, such as the BX120-3AA type, are attached to the surface of the inner mandrel 220 at a specific angle, such as 45 degrees, and form a full-bridge or half-bridge circuit. When the inner mandrel 220 is subjected to stress and deformation, the strain gauges in different orientations produce different resistance changes. Through a specific circuit combination and subsequent signal decoupling algorithm, the controller 300 can separate and calculate the bending moment signal experienced by the inner mandrel 220 from the output signals of these Wheatstone bridges, including the magnitude and direction, and the torque signal. This method provides real-time drill bit stress data, and these two signals are key inputs for the state estimation algorithm and stiffness parameter correction, respectively.

[0043] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for preventing deviation during drilling of a rock drill bit, characterized in that, Includes the following steps: Data acquisition: High-frequency hull sway input is acquired by the surface motion reference unit (100) installed on the drilling feed mechanism; Simultaneously, downhole mixed attitude readings, bending moment and torque signals, and axial extension are acquired by the differential motion sensing sub (200) connected in series between the drill string end and the drill bit. Interference prediction: Based on the preset system dynamics model and the high-frequency sway input of the hull, the equivalent damping parameter of the model is dynamically corrected by the axial extension and the equivalent lateral stiffness parameter of the model is dynamically corrected by the torque signal, and the predicted downhole high-frequency sway attitude is output as a pure interference component. Decoupling estimation: Subtract the predicted downhole high-frequency swaying attitude from the downhole mixed attitude reading to obtain a preliminary trajectory deviation signal; input the preliminary trajectory deviation signal and the bending moment signal into the state estimation algorithm to output a clean true trajectory deviation; Generate instruction: Input the pure real trajectory deviation into the controller (300) to generate a smooth correction action instruction.

2. The method for preventing deviation during drilling of a rock drill bit according to claim 1, characterized in that, The step of dynamically correcting the equivalent lateral stiffness parameters of the model using the torque signal specifically includes: The current torsional stress level of the drill string is calculated based on the torque signal. The built-in torsional stress-lateral stiffness conversion relationship is used to calculate the dynamic stiffness reduction factor; The equivalent lateral stiffness parameter in the model is reduced using the dynamic stiffness reduction factor.

3. A drilling method for preventing deviation of drill bits in rock drilling vessels according to claim 2, characterized in that, The conversion relationship between torsional stress and lateral stiffness was obtained through calibration on a land-based test bench.

4. A method for preventing deviation during drilling of a rock drill bit according to claim 1, characterized in that, The logic of the state estimation algorithm includes: When the bending moment signal shows a continuous and stable increase, the confidence level in the initial trajectory deviation signal is increased.

5. A drilling method for preventing deviation of drill bits in rock drilling vessels according to claim 1, characterized in that, The system dynamics model is established in advance based on the material, geometry, and boundary conditions of the drill string using the finite element analysis method.

6. A device for preventing deviation of drill bits in rock drilling vessels, used to perform the anti-deviation drilling method for drill bits in rock drilling vessels as described in claims 1-5, characterized in that, The device includes: A surface motion reference unit (100) is installed on the drilling feed mechanism to acquire high-frequency hull sway input; A differential motion sensing sub (200) is connected in series between the end of the drill string and the drill bit to acquire downhole mixed attitude readings, bending moment and torque signals, and axial extension / retraction. The controller (300) is configured to receive data from the surface motion reference unit (100) and the differential motion sensing section (200), and to perform the steps of interference prediction, decoupling estimation and instruction generation.

7. The anti-deviation detection device for drill bits of rock drilling vessels according to claim 6, characterized in that, The surface motion reference unit (100) includes an integrated multi-axis inertial measurement unit and motion reference unit.

8. The anti-deviation detection device for drill bits of rock drilling vessels according to claim 6, characterized in that, The differential motion sensing section (200) includes: The outer casing (210) is used to connect the drill string above; An inner mandrel (220) passes through the outer casing (210), and its lower end is used to connect to a drill bit. The inner mandrel (220) can produce small axial and radial relative displacements within the outer casing (210). An axial displacement sensor group (230) is installed between the outer casing (210) and the inner spindle (220) for measuring the axial extension and contraction. A moment and torque sensing assembly (240) is mounted on the surface of the inner mandrel (220) for measuring the moment and torque signals; A downhole attitude gauge (250), installed inside the inner spindle (220), is used to measure the downhole mixed attitude reading.

9. The anti-deviation detection device for drill bits of rock drilling vessels according to claim 8, characterized in that, The axial displacement sensor group (230) is a set of linear variable differential transformers.

10. The anti-deviation detection device for drill bits of rock drilling vessels according to claim 8, characterized in that, The bending moment and torque sensing group (240) consists of multiple Wheatstone bridge strain gauges.

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