A method for automatic hole deviation correction in deep hole drilling of coalfield drilling

Abstract

The application discloses a kind of automatic deviation correction methods in deep hole drilling of coalfield drilling, it is related to coalfield drilling technical field, the application will be determined to deviation correction attitude by four attitude solution algorithm, while the modeling of drilling attitude estimation problem based on Kalman filter is established to avoid the drift and error accumulation problem of attitude quaternion, effectively inhibit the drift and error accumulation in sensor data, by deviation calculation, the actual measured drilling attitude is compared with preset direction, the deviation between actual direction and preset direction is determined, the risk and injury possibility of operator in dangerous environment are reduced, automatic drilling deviation detection and correction are realized, reduce manual intervention, improve drilling operation efficiency, reduce manual operation error.

Description

Technical Field

[0001] This invention relates to the field of coalfield drilling technology, specifically to an automatic borehole correction method in deep hole drilling in coalfields. Background Technology

[0002] Coalfield drilling refers to exploration and pre-mining drilling activities conducted in coal mining areas. It is primarily used to obtain information about the underground geological conditions of coal mines, including parameters such as the distribution, thickness, quality, and dip angle of coal seams. This information is crucial for coal mine planning and design. The main purpose of coalfield drilling is to determine the reserves and quality of coalfields to facilitate mine design and mining plan formulation. Through drilling sampling and measurement, the physical properties, chemical composition, and other geological parameters of coal seams can be determined, providing a basis for subsequent coal mining operations. Common drilling methods in coalfield drilling include borehole drilling and core drilling. Borehole drilling involves rotating the drill rod and drill bit to open underground rock, then using the borehole to obtain geological samples and measure underground geological parameters. Core drilling uses specialized core drill bits to collect rock samples to obtain more accurate geological information.

[0003] However, in existing technologies, the actual drilling parameters must be close to the preset drilling parameters. For example, Chinese patent CN114482861A discloses an automatic borehole correction method for deep borehole drilling in coalfields, which includes the following steps: S1. Ensure the site is flat so that the reserved mud is higher than the construction water level to prevent borehole collapse due to the pressure inside the hole being less than the pressure outside the hole during drilling; S2. After confirming the borehole position, move the drilling rig to the construction position; S3. Operate the center of the drilling rig's lifting wire rope to align with the pile center; S4. After the drilling rig is in place, correct it so that the base is flat and stable to ensure that there is no tilting or displacement during drilling, and to ensure the stability of the drilling tools and the quality of the borehole; S5. Before drilling, install a verticality monitoring system and a drill bit correction system to automatically correct the deviation before drilling; S6. After cleaning the hole, conduct a phased borehole quality inspection; S7. Grout the hole to complete the drilling. Before drilling, the drill bit correction system corrects the verticality of the drill rod back to the normal range, and automatically corrects the deviation during the drilling process to improve the drilling quality.

[0004] While the aforementioned solutions offer advantages, deep-hole drilling in coalfields presents numerous challenges. Factors causing borehole deviation are multifaceted, primarily categorized as mechanical bending and aggregate deviation factors. Traditional manual drilling methods cannot promptly adjust deviations caused by either factor, potentially leading to drilling accidents, personnel injuries, and equipment damage. While some drill bit systems with deviation correction capabilities, such as those described above, employ drill bit detection and correction systems to monitor borehole movement and promptly correct deviations, the actual detection process requires sensors to monitor various borehole parameters. However, the accumulation of sensor errors cannot be effectively reduced, leading to secondary and tertiary corrections even after initial corrections. Therefore, an automatic borehole deviation correction method is urgently needed to address these issues in deep-hole drilling in coalfields. Summary of the Invention

[0005] The purpose of this invention is to solve the problem in the prior art that it is impossible to effectively reduce or minimize the cumulative error of sensors, and even if correction is performed, secondary or tertiary correction is still required due to the cumulative error of the sensors.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] This invention provides an automatic borehole correction method for deep borehole drilling in coalfield drilling, characterized by the following steps:

[0008] (1) Correction data collection

[0009] An inclination sensor is installed in the middle of the drill rod, an azimuth sensor is installed at the bottom of the drill rod, a rotation speed sensor is installed at the top of the drill rod, and inclination and azimuth sensors are also installed on the drilling arm. Multiple sensors continuously monitor and record the inclination, azimuth, and rotation speed of the drill rod during drilling.

[0010] (2) Correction data processing

[0011] Preprocess the data on inclination angle, azimuth angle, and rotation speed during drilling;

[0012] (3) Correction attitude calculation

[0013] The four-element attitude calculation algorithm is used to determine the correction attitude. Specifically, the algorithm includes: initializing the attitude calculation and updating the sensor data. The specific steps for updating the sensor data are as follows:

[0014] 3.1 Obtain angular velocity data from sensor data;

[0015] 3.2 The attitude change quaternion is estimated using the fourth-order Runge-Kutta method based on the rotational velocity data acquired at the current moment. Specifically:

[0016] 3.2.1 Define the rotational speed sensor update frequency as... That is, the time step of discretization;

[0017] 3.2.2 Calculate the increment of the attitude change quaternion from the current angular velocity data. ;

[0018] 3.2.3 Multiply the current angular velocity data by Half of that, we get the angular velocity at the midpoint: ;

[0019] 3.2.4 Calculate the increment of the attitude change quaternion at the intermediate time step from the angular velocity at the intermediate time step. ;

[0020] 3.2.5 Multiply the angular velocity at the midpoint of the time interval again by... Half of it, to obtain the angular velocity at another intermediate moment: ;

[0021] 3.2.6 Calculate the increment of the attitude change quaternion at another intermediate time point from the angular velocity at another intermediate time point. ;

[0022] 3.2.7 The three attitude change quaternion increments are weighted and averaged to obtain the final attitude change quaternion increment: ,in The increment of the attitude change quaternion calculated using the current angular velocity;

[0023] 3.2.8 Multiply the attitude change quaternion increment by the attitude quaternion from the previous time step to obtain the attitude quaternion for the current time step: ;

[0024] 3.3 In step (3), the attitude quaternion is normalized so that its norm is equal to 1;

[0025] (4) Attitude result output conversion

[0026] Based on the attitude quaternions, the inclination and azimuth angles of the borehole are calculated, specifically:

[0027] 4.1 The tilt angle is represented by converting attitude quaternions to Euler angles;

[0028] 4.2 Converting attitude quaternions to rotation matrices, attitude quaternions The direction vector is represented as: According to the direction vector To calculate the azimuth angle, the arctangent function is used to calculate the direction vector. Quantity and The ratio of the components, i.e. ;

[0029] (5) Modeling the borehole attitude estimation problem

[0030] Modeling the borehole attitude estimation problem based on Kalman filters, specifically:

[0031] 5.1 The drilling attitude estimation problem is established as a state-space model, and the state equation and observation equation are established;

[0032] 5.2 Initialize the state vector and covariance matrix of the Kalman filter;

[0033] 5.3 Based on the state equation in the modeling of the current attitude estimation problem of borehole, the process model is used to predict the current state and calculate the covariance matrix of the predicted state. The prediction step uses prior information to predict the state at the next moment.

[0034] 5.4 Based on the observation equation in the system modeling, compare the measured values ​​of each sensor with the predicted state, calculate the measurement residual of the predicted state, and calculate the Kalman gain;

[0035] 5.5 The predicted state and covariance matrix are corrected using Kalman gain to obtain the updated state estimate and covariance;

[0036] (6) Calculation of actual correction value

[0037] The actual measured drilling posture is compared with the preset direction through vector operations to determine the deviation;

[0038] (7) Confirmation of correction values

[0039] Based on the calculated deviation value, a PID algorithm is used for correction;

[0040] (8) Output of correction command

[0041] Based on the output of the PID algorithm, corresponding control commands are generated to adjust the working parameters of the drilling rig.

[0042] (9) Alarm after correction

[0043] Continuously monitor the borehole attitude data and provide real-time feedback based on the correction results.

[0044] The present invention is further configured such that: in step (1), a wireless transmission network topology is established based on LoRa wireless transmission technology, the network is composed of multiple sensor nodes, and the correction data is transmitted by the relay point;

[0045] The present invention is further configured such that, in step (2), the preprocessing includes calibration and filtering;

[0046] The present invention is further configured such that: in step (3), the initial attitude calculation initializes the quaternion and sets it as the initial value. This represents the non-rotating state of the drill pipe, i.e., the initialization state.

[0047] The present invention is further configured such that: in step 4.1, the Euler angles are pitch angle, roll angle and yaw angle, wherein the pitch angle represents the inclination angle of the borehole;

[0048] The present invention is further configured such that: in step 5.1, the actual attitude of the borehole is defined as a state variable, the attitude data measured by each sensor is defined as an observation variable, and the relationship between the state variable and the observation variable is defined;

[0049] The present invention is further configured such that, in step (9), the implementation feedback specifically means: when the deviation exceeds a preset threshold, an alarm is triggered; when a second correction is required after correction, an alarm is triggered.

[0050] Compared with known public technologies, the technical solution provided by this invention has the following beneficial effects:

[0051] This invention determines the correction attitude using a quaternion attitude calculation algorithm. Simultaneously, it avoids the drift and error accumulation problems of attitude quaternions by modeling the borehole attitude estimation problem based on a Kalman filter. The Kalman gain fuses the measurement residual with the state prediction in the prediction step to obtain the optimal estimated attitude. The Kalman filter continuously predicts and updates the state, fusing measured values ​​and prior information to effectively suppress drift and error accumulation in sensor data and provide more accurate attitude estimation results. Then, the actual measured borehole attitude is compared with a preset direction through deviation calculation to determine the deviation between the actual and preset directions. The specific deviation value is calculated and corrected using a PID algorithm to adjust the drilling rig's operating parameters, thereby achieving automatic correction. Simultaneously, the drill rod status is monitored after adjustment, and when the deviation exceeds a preset threshold... The system issues alarms when a second correction is needed after initial correction, promptly alerting operators to intervene and prevent drill jamming accidents. This reduces the risk and possibility of injury to operators in hazardous environments. Unlike traditional deep-hole drilling, real-time acquisition and processing of sensor data allows for timely detection and correction of borehole deviations during drilling. Furthermore, a quaternion attitude calculation algorithm is used to determine the correction attitude, and a Kalman filter is used to model the borehole attitude estimation problem, avoiding drift and error accumulation issues in attitude quaternions. This achieves automated borehole deviation detection and correction, reducing manual intervention, improving drilling efficiency, and minimizing human error. It solves the problem in existing technologies where the cumulative error of sensors cannot be effectively reduced, and even after correction, secondary and tertiary corrections are required due to accumulated sensor errors. Detailed Implementation

[0052] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] This invention provides a technical solution: an automatic borehole correction method in deep borehole drilling in coalfields, characterized by comprising the following steps:

[0054] (1) Correction data collection

[0055] An inclination sensor is installed in the middle of the drill rod, an azimuth sensor is installed at the bottom of the drill rod, a rotation speed sensor is installed at the top of the drill rod, and inclination and azimuth sensors are also installed on the drilling arm. Multiple sensors continuously monitor and record the inclination, azimuth, and rotation speed of the drill rod during drilling.

[0056] (2) Correction data processing

[0057] Preprocess the data on inclination angle, azimuth angle, and rotation speed during drilling;

[0058] (3) Correction attitude calculation

[0059] The four-element attitude calculation algorithm is used to determine the correction attitude. Specifically, the algorithm includes: initializing the attitude calculation and updating the sensor data. The specific steps for updating the sensor data are as follows:

[0060] 3.1 Obtain angular velocity data from sensor data;

[0061] 3.2 The attitude change quaternion is estimated using the fourth-order Runge-Kutta method based on the rotational velocity data acquired at the current moment. Specifically:

[0062] 3.2.1 Define the rotational speed sensor update frequency as... That is, the time step of discretization;

[0063] 3.2.2 Calculate the increment of the attitude change quaternion from the current angular velocity data. ;

[0064] 3.2.3 Multiply the current angular velocity data by Half of that, we get the angular velocity at the midpoint: ;

[0065] 3.2.4 Calculate the increment of the attitude change quaternion at the intermediate time step from the angular velocity at the intermediate time step. ;

[0066] 3.2.5 Multiply the angular velocity at the midpoint of the time interval again by... Half of it, to obtain the angular velocity at another intermediate moment: ;

[0067] 3.2.6 Calculate the increment of the attitude change quaternion at another intermediate time point from the angular velocity at another intermediate time point. ;

[0068] 3.2.7 The three attitude change quaternion increments are weighted and averaged to obtain the final attitude change quaternion increment: ,in The increment of the attitude change quaternion calculated using the current angular velocity;

[0069] 3.2.8 Multiply the attitude change quaternion increment by the attitude quaternion from the previous time step to obtain the attitude quaternion for the current time step: ;

[0070] 3.3 In step (3), the attitude quaternion is normalized so that its norm is equal to 1;

[0071] (4) Attitude result output conversion

[0072] Based on the attitude quaternions, the inclination and azimuth angles of the borehole are calculated, specifically:

[0073] 4.1 The tilt angle is represented by converting attitude quaternions to Euler angles;

[0074] 4.2 Converting attitude quaternions to rotation matrices, attitude quaternions The direction vector is represented as: According to the direction vector To calculate the azimuth angle, the arctangent function is used to calculate the direction vector. Quantity and The ratio of the components, i.e. ;

[0075] (5) Modeling the borehole attitude estimation problem

[0076] Modeling the borehole attitude estimation problem based on Kalman filters, specifically:

[0077] 5.1 The drilling attitude estimation problem is established as a state-space model, and the state equation and observation equation are established;

[0078] 5.2 Initialize the state vector and covariance matrix of the Kalman filter;

[0079] 5.3 Based on the state equation in the modeling of the current attitude estimation problem of borehole, the process model is used to predict the current state and calculate the covariance matrix of the predicted state. The prediction step uses prior information to predict the state at the next moment.

[0080] 5.4 Based on the observation equation in the system modeling, compare the measured values ​​of each sensor with the predicted state, calculate the measurement residual of the predicted state, and calculate the Kalman gain;

[0081] 5.5 The predicted state and covariance matrix are corrected using Kalman gain to obtain the updated state estimate and covariance;

[0082] (6) Calculation of actual correction value

[0083] The actual measured drilling posture is compared with the preset direction through vector operations to determine the deviation;

[0084] (7) Confirmation of correction values

[0085] Based on the calculated deviation value, a PID algorithm is used for correction;

[0086] (8) Output of correction command

[0087] Based on the output of the PID algorithm, corresponding control commands are generated to adjust the working parameters of the drilling rig.

[0088] (9) Alarm after correction

[0089] Continuously monitor the borehole attitude data and provide real-time feedback based on the correction results.

[0090] Further configuration: In step (1), a wireless transmission network topology is established based on LoRa wireless transmission technology, with multiple sensor nodes forming the network, and the correction data is transmitted by the relay point;

[0091] A further setting is that, in step (2), the preprocessing includes calibration and filtering;

[0092] A further setting is as follows: In step (3), the initial attitude calculation initializes the quaternion and sets it as the initial value. This represents the non-rotating state of the drill pipe, i.e., the initialization state.

[0093] A further setting is as follows: In step 4.1, the Euler angles are pitch angle, roll angle, and yaw angle, wherein the pitch angle represents the inclination angle of the borehole;

[0094] Further settings are as follows: In step 5.1, the actual attitude of the borehole is defined as the state variable, the attitude data measured by each sensor is defined as the observation variable, and the relationship between the state variable and the observation variable is defined.

[0095] A further setting is as follows: In step (9), the implementation feedback is specifically as follows: when the deviation exceeds the preset threshold, an alarm is triggered; when a second correction is required after correction, an alarm is triggered.

[0096] Working principle

[0097] An inclination sensor installed on the drill rod is used to measure the inclination angle of the drill rod, an azimuth sensor is used to measure the azimuth angle of the drill rod, and a rotation speed sensor is used to measure the rotation speed of the drill rod. An inclination sensor and azimuth sensor installed on the drill arm are used to measure the inclination angle and azimuth angle of the drill rig structure. Here, the middle, lower, and upper parts are defined with the end of the drill rod that contacts and extends into the ground as the lower part. In the data acquisition for correction, the data records can also be stored in a database. Then, correction data preprocessing is used to eliminate sensor errors and offsets, ensuring data accuracy. Filtering can remove high-frequency noise and oscillations, improving data stability.

[0098] The correction attitude is determined using a quaternion attitude calculation algorithm. In the attitude calculation, the angular velocity data updated by the sensors is used to represent the current rotation rate of the drill pipe, while the increment of the quaternion in the attitude change is also considered. In this process, the attitude quaternions are normalized to make their norm equal to 1, thus preserving the unit length characteristic of the quaternions. At the same time, the drilling attitude estimation problem modeling based on Kalman filter avoids the drift and error accumulation problems of attitude quaternions. Kalman gain fuses the measurement residual with the state prediction in the prediction step to obtain the optimal estimated attitude. Kalman filter continuously predicts and updates the state, fuses the measured values ​​and prior information, effectively suppresses the drift and error accumulation in sensor data, and provides more accurate attitude estimation results.

[0099] By comparing the actual measured drilling posture with the preset direction through deviation calculation, the deviation between the actual direction and the preset direction is determined, the specific deviation value is calculated, and the PID algorithm is used for correction to adjust the drilling rig's working parameters, thereby achieving automatic correction. At the same time, the status of the drill rod is monitored after adjustment. When the deviation exceeds the preset threshold, an alarm is issued. When a second correction is required after correction, an alarm is issued, thereby promptly reminding the operator to intervene, avoiding drill jam accidents, and reducing the risk and possibility of injury to the operator in dangerous environments.

[0100] Unlike traditional deep hole drilling, real-time acquisition and processing of sensor data enables timely detection and correction of borehole deviations during the drilling process. At the same time, a quaternion attitude calculation algorithm is used to determine the correction attitude, and the borehole attitude estimation problem model is established by Kalman filter to avoid the drift and error accumulation of attitude quaternions. This achieves automated borehole deviation detection and correction, reduces manual intervention, improves drilling efficiency, and reduces human operation errors.

[0101] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for automatic borehole correction in deep borehole drilling in coalfield exploration, characterized in that, Includes the following steps: (1) Correction data collection An inclination sensor is installed in the middle of the drill rod, an azimuth sensor is installed at the bottom of the drill rod, a rotation speed sensor is installed at the top of the drill rod, and inclination and azimuth sensors are also installed on the drilling arm. Multiple sensors continuously monitor and record the inclination, azimuth, and rotation speed of the drill rod during drilling. (2) Correction data processing Preprocess the data on inclination angle, azimuth angle, and rotation speed during drilling; (3) Correction attitude calculation The four-element attitude calculation algorithm is used to determine the correction attitude. Specifically, the algorithm includes: initializing the attitude calculation and updating the sensor data. The specific steps for updating the sensor data are as follows: 3.1 Obtain angular velocity data from sensor data; 3.2 The attitude change quaternion is estimated using the fourth-order Runge-Kutta method based on the rotational velocity data acquired at the current moment. Specifically: 3.2.1 Define the rotational speed sensor update frequency as... That is, the time step of discretization; 3.2.2 Calculate the increment of the attitude change quaternion from the current angular velocity data. ; 3.2.3 Multiply the current angular velocity data by Half of that, we get the angular velocity at the midpoint: ; 3.2.4 Calculate the increment of the attitude change quaternion at the intermediate time step from the angular velocity at the intermediate time step. ; 3.2.5 Multiply the angular velocity at the midpoint of the time interval again by... Half of it, to obtain the angular velocity at another intermediate moment: ; 3.2.6 Calculate the increment of the attitude change quaternion at another intermediate time point from the angular velocity at another intermediate time point. ; 3.2.7 The three attitude change quaternion increments are weighted and averaged to obtain the final attitude change quaternion increment: ,in The increment of the attitude change quaternion calculated using the current angular velocity; 3.2.8 Multiply the attitude change quaternion increment by the attitude quaternion from the previous time step to obtain the attitude quaternion for the current time step: ; 3.3 In step (3), the attitude quaternion is normalized so that its norm is equal to 1; (4) Attitude result output conversion Based on the attitude quaternions, the inclination and azimuth angles of the borehole are calculated, specifically: 4.1 The tilt angle is represented by converting attitude quaternions to Euler angles; 4.2 Converting attitude quaternions to rotation matrices, attitude quaternions The direction vector is represented as: According to the direction vector To calculate the azimuth angle, the arctangent function is used to calculate the direction vector. Quantity and The ratio of the components, i.e. ; (5) Modeling the borehole attitude estimation problem Modeling the borehole attitude estimation problem based on Kalman filters, specifically: 5.1 The drilling attitude estimation problem is established as a state-space model, and the state equation and observation equation are established; 5.2 Initialize the state vector and covariance matrix of the Kalman filter; 5.3 Based on the state equation in the modeling of the current attitude estimation problem of borehole, the process model is used to predict the current state and calculate the covariance matrix of the predicted state. The prediction step uses prior information to predict the state at the next moment. 5.4 Based on the observation equation in the system modeling, compare the measured values ​​of each sensor with the predicted state, calculate the measurement residual of the predicted state, and calculate the Kalman gain; 5.5 The predicted state and covariance matrix are corrected using Kalman gain to obtain the updated state estimate and covariance; (6) Calculation of actual correction value The actual measured drilling posture is compared with the preset direction through vector operations to determine the deviation; (7) Confirmation of correction values Based on the calculated deviation value, a PID algorithm is used for correction; (8) Output of correction command Based on the output of the PID algorithm, corresponding control commands are generated to adjust the working parameters of the drilling rig. (9) Alarm after correction Continuously monitor the borehole attitude data and provide real-time feedback based on the correction results.

2. The automatic borehole correction method in deep borehole drilling in coalfield drilling according to claim 1, characterized in that: In step (1), a wireless transmission network topology is established based on LoRa wireless transmission technology, with multiple sensor nodes forming the network, and the correction data is transmitted by the relay point.

3. The automatic borehole correction method in deep borehole drilling in coalfield drilling according to claim 1, characterized in that: In step (2), the preprocessing includes calibration and filtering.

4. The automatic borehole correction method in deep borehole drilling in coalfield drilling according to claim 1, characterized in that: In step (3), the initial attitude calculation initializes the quaternion and sets it as the initial value. This represents the non-rotating state of the drill pipe, i.e., the initial state.

5. The automatic borehole correction method in deep borehole drilling in coalfield drilling according to claim 1, characterized in that: In step 4.1, the Euler angles are pitch angle, roll angle and yaw angle, where the pitch angle represents the inclination angle of the borehole.

6. The automatic borehole correction method in deep borehole drilling in coalfield drilling according to claim 1, characterized in that: In step 5.1, the actual attitude of the borehole is defined as the state variable, the attitude data measured by each sensor is defined as the observation variable, and the relationship between the state variable and the observation variable is defined.

7. The automatic borehole correction method for deep borehole drilling in coalfield drilling according to claim 1, characterized in that: In step (9), the implementation feedback specifically means: when the deviation exceeds the preset threshold, an alarm is triggered; when a second correction is required after correction, an alarm is triggered.