A mud continuous wave measurement while drilling control system and method

Abstract

The present invention belongs to the technical field of mud continuous wave measurement, and in particular, relates to a mud continuous wave measurement while drilling control system and method, wherein the system includes a valve monitoring module, a position monitoring module and an adaptive control module; the valve monitoring module includes a downhole communication platform I, a host computer, a downhole control platform, a lower computer and a downhole communication platform II, the position monitoring module includes a position encoder, a motor and a feedback controller, and the adaptive control module includes an operating computer, a wireless communication module and a network connection device. The present application adds a measuring device to the valve of the rotary valve to monitor the changes in external environmental parameters such as pressure, flow, temperature, density, etc. After this information is fed back to the control console, the processor can control and optimize the flow area of ​​the rotary valve according to the on-site working conditions, thereby obtaining a continuous pressure wave signal with better effect and improving the stability of the signal.

Description

Technical Field

[0001] The invention belongs to the technical field of mud continuous wave measurement, and in particular relates to a mud continuous wave measurement while drilling control system and method. Background Art

[0002] As exploration and development move towards digitalization and intelligence, various new downhole measuring instruments emerge in an endless stream. The measurement parameters have evolved from geometric parameters such as well inclination, azimuth, and tool face to multiple engineering and geological parameters such as drilling pressure, vibration, pressure, and resistivity, which have placed higher and higher requirements on transmission rates. The downhole data transmission rate while drilling is difficult to meet the needs of engineering operations, and has become a bottleneck for the continued development of the MWD / LWD field.

[0003] At present, the transmission of the measurement while drilling system widely adopts the positive pulse transmission method, which has the advantages of simple implementation, strong anti-interference ability and high reliability. However, it is a discrete wave, and its working principle is to use mud pulses to realize data transmission, and the data transmission efficiency is slow. The mud continuous wave uses continuous pressure fluctuations to realize data transmission. The carrier frequency is generally tens of hertz, with a high transmission rate and strong anti-interference ability; but due to the complex structure and difficulty in development, the theory, technology and process are not mature enough. Compared with the mud pulse measurement while drilling system, the continuous wave measurement while drilling system has technical problems that need to be solved in terms of continuous wave attenuation law, continuous signal formation in the well, and effective extraction and accurate identification of the collected mud signals, and the research is difficult. At present, in the process of continuous wave transmission of mud, when the flow rate and density of drilling fluid remain unchanged, the pressure difference ∆P is only related to the flow area of ​​the rotary valve. Under field conditions, the flow rate and density will change, resulting in the inability to accurately control the flow area of ​​the rotary valve; at the same time, the continuous wave signal transmission system uses a carrier to transmit the phase modulation (PSK) or frequency modulation (FSK) coded signal, but when changing the phase or frequency, it is impossible to determine whether the motor has completed the acceleration, deceleration and change of direction within one rotation.

[0004] Although there are also measurement while drilling control systems on the market, the existing measurement while drilling control systems have the following problems:

[0005] 1. The existing unified control system cannot accurately monitor the change of the flow area of ​​the rotary valve. The existing mud continuous wave measurement while drilling control system lacks a device to monitor the flow area of ​​the rotary valve when the drilling fluid is flowing. When the flow area of ​​the rotary valve changes, it cannot be discovered in time, and then the operation may be stopped for maintenance, causing huge economic losses to production operations.

[0006] 2. The existing unified control system lacks a control system for monitoring the rotation position of the motor. When the existing continuous wave carrier changes its phase or frequency, the servo cannot determine whether the control motor has completed acceleration, deceleration, and direction change within one rotation, which greatly hinders the subsequent measurement work and greatly reduces the work efficiency. A monitoring system is needed to monitor the rotation position of the motor.

[0007] 3. The existing measurement while drilling control system lacks an adaptive control system. Due to the imperfect adaptability of the hardware equipment, it is impossible to provide real-time information feedback and automatically adjust parameters such as drill bit speed and drilling pressure during the drilling process. This makes it difficult to adaptively optimize parameters during the drilling process, greatly increasing the risk of drilling accidents and energy consumption. Summary of the invention

[0008] A mud continuous wave measurement while drilling control system and method are now proposed. The present application can solve the problems existing in the existing mud continuous wave measurement while drilling control system and provide a more reliable and efficient solution for the transmission of mud continuous waves.

[0009] In order to achieve the above technical effects, the technical solution of the present invention is as follows:

[0010] A mud continuous wave measurement while drilling control system comprises a valve monitoring module, a position monitoring module and an adaptive control module; the valve monitoring module and the position monitoring module are two independent monitoring modules, which respectively monitor and correct the flow area of ​​a rotary valve and the rotation position of a motor, and the valve monitoring module and the position monitoring module are integrated in the adaptive control module, and the adaptive control module dynamically adjusts the valve monitoring module and the position monitoring module according to data provided by a sensor, so as to realize adaptive optimization during the drilling process.

[0011] Further, the valve monitoring module includes: a downhole communication platform I, a host computer, a downhole control platform, a lower computer and a downhole communication platform II, wherein the downhole communication platform I and the downhole control platform are both connected to the host computer signal; the host computer is respectively connected to the pressure sensor, the temperature sensor, the turbine flowmeter, and the straight tube density meter signal through a rotary valve, the lower computer is connected to the pressure sensor, the temperature sensor, the turbine flowmeter, and the straight tube density meter signal, and the lower computer is connected to the downhole communication platform II signal;

[0012] The position monitoring module comprises: a position encoder, a motor and a feedback controller, wherein the motor is connected to the position encoder and the feedback controller respectively, the feedback controller is connected to the position encoder and the rotary valve, and the rotary valve is connected to the speed sensor and the displacement sensor;

[0013] The adaptive control module includes: an operating computer, a wireless communication module and a network connection device, the operating computer is respectively connected to the wireless communication module and the network connection device, the wireless communication module and the network connection device are connected to an operating panel, the operating panel is connected with an embedded processor, a touch screen controller and a monitor, and the embedded processor, the touch screen controller and the monitor are connected to a hydraulic control platform, the hydraulic control platform is connected to an actuator and a drive motor, the actuator and the drive motor are connected to a regulating valve, the regulating valve is respectively connected to a data acquisition card, an emergency stop device and an explosion-proof device, and the data acquisition card is respectively connected to a formation sensor, a pressure sensor, a temperature sensor and a turbine flowmeter.

[0014] Furthermore, the pressure sensor is installed on the mud flow channel near the rotary valve. The pressure sensor senses the changes in the liquid column pressure of the mud, converts it into an electrical signal, and transmits it to the adaptive control module. The adaptive control module adjusts the rotary valve based on the pressure data and real-time formation information.

[0015] The temperature sensor is installed on the downhole drilling tool near the drill bit. The temperature sensor measures the temperature of the mud through the thermistor and transmits the temperature data to the adaptive control module in real time. The adaptive control module adjusts the drilling parameters based on the temperature data.

[0016] The turbine flowmeter is installed in the straight pipe section in the middle of the mud flow pipeline to ensure stable fluid flow and reduce the interference of turbulence on flow measurement. The turbine flowmeter senses the mud flow rate through the internal turbine rotation and converts it into an electrical signal, which is transmitted to the valve monitoring module. The mud flow rate is calculated based on the rotation speed of the turbine. The adaptive control module dynamically adjusts the valve opening and mud pump speed based on the flow data.

[0017] The straight tube densitometer is installed upstream of the mud flow pipeline, close to the inlet of the mud pump, to measure the density of the mud before it enters the well. The straight tube densitometer measures the mud flowing through the straight pipe section and uses the principles of buoyancy and gravity to detect the density change of the mud. The measurement data of the straight tube densitometer is transmitted to the valve monitoring module through the wireless module, and the adaptive control module automatically adjusts the drilling parameters according to the mud density.

[0018] Furthermore, the downhole communication platform I and the downhole control platform are connected to the host computer via cables; the host computer is connected to the rotary valve signal via wireless, the rotary valve and the lower computer are connected to the pressure sensor, temperature sensor, turbine flowmeter, and straight tube density meter via cables, and the lower computer is connected to the downhole communication platform II via wireless.

[0019] Furthermore, the motor is connected to the position encoder via a cable, the feedback controller is connected to the motor via a cable, the feedback controller position encoder is connected wirelessly, the rotary valve is connected to the feedback controller via a cable, and the speed sensor, displacement sensor and rotary valve are connected via a cable.

[0020] Furthermore, the formation sensor is connected to the regulating valve through a cable, the regulating valve is connected to the actuator wirelessly, the actuator is connected to the embedded processor through a cable, the embedded processor is connected to the data acquisition card through a cable, the data acquisition card is connected to the operating computer through a wired connection, the operating computer is connected to the wireless communication module through a wireless connection, the wireless communication module is connected to the network connection device through a wireless connection, the network connection device is connected to the drive motor through a wired connection, the drive motor is connected to the hydraulic control platform through a pipeline, the hydraulic control platform is connected to the emergency stop device and the explosion-proof device through a wired connection, and the touch screen controller, monitor, and operation panel are connected to the operating computer through a wired connection.

[0021] A mud continuous wave measurement while drilling control method comprises the following steps:

[0022] S1: Rotary valve flow area correction control: By adding a measuring device at the valve of the rotary valve, the changes in external environmental parameters such as pressure, flow, temperature, and density are monitored. After the monitored information is fed back to the control console, the flow area of ​​the rotary valve is controlled and optimized;

[0023] S2: Motor position monitoring control: The position encoder can monitor the motor's rotation position in real time. When the motor position deviates, the motor position can be corrected in combination with feedback control to ensure the normal generation of continuous wave signals.

[0024] S3: Integrated system control: Based on real-time formation feedback information, the drill bit speed, drilling pressure and other parameters are automatically adjusted during drilling to achieve adaptive optimization during drilling.

[0025] Furthermore, step S1 specifically includes:

[0026] S101: When the flow rate and density of the drilling fluid change, the pressure sensor, temperature sensor, turbine flowmeter, and straight tube density meter start to work to monitor the changes in pressure, temperature, flow rate, and density of the rotary valve;

[0027] S102: After receiving the data from the pressure sensor, temperature sensor, turbine flowmeter, and straight tube density meter, the lower computer processes the data and then transmits it to the downhole communication platform II. The downhole communication platform II filters, amplifies, and A / D converts the data and then transmits it to the downhole communication platform I through the transmission method of radio electromagnetic waves;

[0028] S103: After receiving the data transmitted by the downhole communication platform II, the downhole communication platform I sends it to the upper computer and processes it together with the downhole control platform. The downhole control platform adjusts the opening of the rotary valve according to the data monitored by multiple sensors, thereby controlling and optimizing the flow area of ​​the rotary valve, and subsequently obtaining a continuous pressure wave signal with better effect.

[0029] Furthermore, in step S103, data fusion is first performed based on the data collected by different sensors, and the data of multiple sensors are processed through fuzzy logic to eliminate the errors that may be caused by the data of a single sensor. Based on the fused data, the priority of each parameter under different working conditions is set. When the pressure sensor detects that the system pressure exceeds the preset threshold, the opening of the rotary valve is reduced to reduce the pressure; when the flow sensor detects that the flow rate is reduced, the valve opening is increased to maintain the flow rate stable; if the data of the temperature or density sensor deviates from the normal range.

[0030] Furthermore, step S2 specifically includes:

[0031] S201: When it is necessary to determine whether the motor has completed acceleration, deceleration and direction change within one rotation, the position and speed of the motor are monitored by a position encoder;

[0032] S202: After the speed sensor and the displacement sensor monitor the position and speed of the rotary valve, they simultaneously send the rotation data of the motor to the feedback controller for comparison processing, and after comparing with the original position data, feedback control is performed on the motor;

[0033] S203: When the feedback controller detects that the position has deviated, it will re-adjust the position of the motor through the downhole control platform, and the position encoder will monitor the position and speed of the motor again until the position deviation is completely eliminated.

[0034] Furthermore, the comparison processing of step S202 is specifically as follows: the feedback controller synchronizes and filters the received real-time rotation data, compares the real-time rotation position with the preset target position, and calculates the position error. The position error is expressed as the difference between the current actual position and the target position, and the error value = real-time position - target position; the feedback controller analyzes the size and direction of the error value. If the error value is positive, it indicates that the motor position is ahead; if the error value is negative, it indicates that the motor position is lagging. The error change trend is analyzed to determine whether there is a systematic deviation or a temporary deviation in the motor movement.

[0035] Furthermore, step S3 specifically includes:

[0036] S301: Install formation sensors, temperature sensors, pressure sensors and turbine flowmeters to collect various data involved in the drilling process in real time. The formation sensors measure the physical properties of the formations, the temperature sensors and pressure sensors monitor the temperature and pressure changes in the drilling wellbore, and the turbine flowmeter measures the flow and speed of the drilling fluid.

[0037] S302: Multiple sensors transmit the collected data to the data processing unit in the feedback controller for subsequent data processing and analysis; the data acquisition card collects data in real time, and the collected data will be sent to the data processing unit for real-time processing and analysis through algorithms and models. The data processing includes data cleaning, feature extraction, and pattern recognition steps. The analysis results will be used for subsequent intelligent decision-making and adjustment and optimization of drilling parameters;

[0038] S303: The processed data is fed back to the control system in the feedback controller to provide real-time drilling process monitoring and guidance for the drilling operator.

[0039] Furthermore, the data processing in S302 is specifically as follows:

[0040] Data cleaning: Assume that the original data set collected is , i=1,2,…, m , m is the number of data, For the i-th data collected by the corresponding sensor, the cleaning process can be performed by the mean filtering algorithm.

[0041] Use a sliding window to smooth the sensor data. The formula is:

[0042] ;

[0043] in, is the window size, Represents the filtered i data, Represents the filtered j data.

[0044] Feature extraction:

[0045] After cleaning the data, extract features from the sensor data;

[0046] For pressure sensor data:

[0047] Extract the statistical characteristics of pressure fluctuations, including the mean and variance ;

[0048] ;

[0049] in The pressure sensor collects p The first i data points, n Represents the length of each segment of data;

[0050] For temperature sensor data:

[0051] The frequency domain features are extracted by Fourier transform to analyze the periodic changes of temperature. The formula is:

[0052] ;

[0053] in For time t Temperature data on is the frequency, It is the temperature data The Fourier transform in the frequency domain represents the changes in is the base of natural logarithms, approximately equal to 2.71828, is a complex exponential function, which means that at the frequency The rotation factors below are used to transform the time domain signal into the frequency domain;

[0054] For flow and density data:

[0055] Perform trend analysis on flow and density, and fit flow Q and density by least squares method Linear trend over time:

[0056] ;

[0057] in a, b, c and d is the fitting coefficient, t Represents time;

[0058] Pattern recognition includes the following:

[0059] After feature extraction, the system needs to identify patterns in the data, which can be achieved through machine learning or statistical models;

[0060] Classification based on support vector machine:

[0061] By using the classification algorithm to identify normal operations and abnormal situations, assuming that there is a feature vector , the classification decision function of the support vector machine model is:

[0062] ;

[0063] in, andb are the model parameters obtained through training, For labels, is the kernel function, which is used to calculate the similarity between two feature vectors;

[0064] State estimation based on Kalman filter:

[0065] The real-time data of the sensor is used to estimate the state of the system through the Kalman filter. t , and its update formula is:

[0066] ;

[0067] in, A is the state transfer matrix, B is the control input matrix, For input, is the process noise.

[0068] Intelligent decision-making and parameter optimization specifically include the following steps:

[0069] After processing and analyzing the sensor data, the system makes intelligent decisions and optimizes drilling parameters;

[0070] Based on feedback control theory, the adaptive control module adjusts the drilling parameters and drilling pressure according to the data fed back by the sensor. W and drilling speed R , drilling pressure W The formula is:

[0071] ;

[0072] in, is the real-time pressure, is the target pressure, It is the proportional gain, which adjusts the drilling pressure through feedback.

[0073] Drilling speed R The adjustment idea is: the sensor monitors the mechanical parameters of the drill bit and the formation parameters in real time, and the real-time pressure obtained by the sensor With target pressure The difference between the pressure error and the drilling state error is used to determine whether the current drilling state is ideal. and drilling pressure W Adjustment of drilling speed R It automatically adjusts as the error increases or decreases, allowing the drill bit to achieve the optimal drilling state under different formation conditions.

[0074] The advantages of the present invention are:

[0075] 1. The system and method of the present application both increase a measuring device at the valve of the rotary valve to monitor changes in external environmental parameters such as pressure, flow, temperature, density, etc. After this information is fed back to the control console, the processor can control and optimize the flow area of ​​the rotary valve according to the on-site working conditions, thereby obtaining a better continuous pressure wave signal and improving the stability of the signal.

[0076] 2. The system and method of the present application can monitor the rotation position of the motor in real time through the position encoder. When the motor position deviates, the position of the motor can be corrected in combination with feedback control to ensure the normal generation of the continuous wave signal, thereby improving work efficiency.

[0077] 3. By designing a set of adaptive control modules, the drill bit speed, drilling pressure and other parameters can be automatically adjusted during drilling based on real-time formation feedback information, achieving adaptive optimization during drilling and greatly reducing the risk of drilling accidents and energy consumption.

[0078] 4. The system and method of the present application improve the control level of the mud continuous wave downhole measurement system, realize efficient, accurate and reliable production operation, thereby improving production efficiency, reducing losses, and providing a more reliable and efficient solution for the transmission of mud continuous wave signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 This is the valve monitoring schematic diagram of this system.

[0080] Figure 2 This is the position monitoring principle diagram of this system.

[0081] Figure 3 This is the adaptive control module diagram of this system.

[0082] In the figure, 1-downhole communication platform I, 2-upper computer, 3-downhole control platform, 4-rotary valve, 5-pressure sensor, 6-temperature sensor, 7-turbine flowmeter, 8-straight tube density meter, 9-lower computer, 10-downhole communication platform II, 11-position encoder, 12-motor, 13-feedback controller, 14-rotary valve, 15-speed sensor, 16-displacement sensor, 17-formation sensor, 18-regulating valve, 19-actuator, 20-embedded processor, 21-data acquisition card, 22-operating computer, 23-wireless communication module, 24-network connection equipment, 25-drive motor, 26-hydraulic control platform, 27-emergency stop device, 28-explosion-proof device, 29-touch screen controller, 30-monitor, 31-operation panel. DETAILED DESCRIPTION

[0083] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0084] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0085] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0086] In the description of the present invention, it should be noted that the terms "upper", "vertical", "inner", "outer", etc. indicate the orientation or position relationship based on the orientation or position relationship shown in the drawings, or the orientation or position relationship in which the product of the application is usually placed when in use, or the orientation or position relationship commonly understood by those skilled in the art, which is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0087] In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "setting", "installation" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0088] Example 1

[0089] A mud continuous wave measurement while drilling control system includes a valve monitoring module, a position monitoring module and an adaptive control module; the valve monitoring module and the position monitoring module are two independent monitoring modules, which respectively monitor and correct the flow area of ​​a rotary valve 14 and the rotation position of a motor 12, and the valve monitoring module and the position monitoring module are integrated in the adaptive control module. The adaptive control module dynamically adjusts the valve monitoring module and the position monitoring module according to data provided by a sensor to achieve adaptive optimization during the drilling process.

[0090] like Figure 1 As shown, the valve monitoring module includes: a downhole communication platform I1, an upper computer 2, a downhole control platform 3, a lower computer 9 and a downhole communication platform II10, wherein the downhole communication platform I1 and the downhole control platform 3 are both connected to the upper computer 2 by signal; the upper computer 2 is respectively connected to the pressure sensor 5, the temperature sensor 6, the turbine flowmeter 7, and the straight tube density meter 8 by signal through a rotary valve 4, the lower computer 9 is connected to the pressure sensor 5, the temperature sensor 6, the turbine flowmeter 7, and the straight tube density meter 8 by signal, and the lower computer 9 is connected to the downhole communication platform II10 by signal;

[0091] like Figure 2 As shown, the position monitoring module includes: a position encoder 11, a motor 12 and a feedback controller 13, wherein the motor 12 is connected to the position encoder 11 and the feedback controller 13 respectively, the feedback controller 13 is connected to the position encoder 11 and the rotary valve 14, and the rotary valve 14 is connected to the speed sensor 15 and the displacement sensor 16;

[0092] like Figure 3 As shown, the adaptive control module includes: an operating computer 22, a wireless communication module 23 and a network connection device 24, the operating computer 22 is respectively connected to the wireless communication module 23 and the network connection device 24, the wireless communication module 23 and the network connection device 24 are connected to the operating panel 31, the operating panel 31 is connected with an embedded processor 20, a touch screen controller 29 and a monitor 30, and the embedded processor 20, the touch screen controller 29 and the monitor 30 are connected to a hydraulic control platform 26, the hydraulic control platform 26 is connected to an actuator 19 and a drive motor 25, the actuator 19 and the drive motor 25 are connected to a regulating valve 18, the regulating valve 18 is respectively connected to a data acquisition card 21, an emergency stop device 27 and an explosion-proof device 28, the data acquisition card 21 is respectively connected to a formation sensor 17, a pressure sensor 5, a temperature sensor 6, and a turbine flowmeter 7.

[0093] The pressure sensor 5 is installed on the mud flow channel near the rotary valve 4, and can directly sense the pressure change of the mud after passing through the valve. The pressure sensor 5 mainly detects the pressure of the mud, that is, the flow resistance of the mud in the drilling fluid system. These pressure data are used to monitor the fluctuation of downhole pressure, help to timely identify abnormal downhole pressure conditions (such as well kicks and well leaks), and automatically adjust the valve opening through the adaptive control module to optimize the mud flow and maintain a stable continuous wave signal; the pressure sensor 5 senses the pressure change of the liquid column of the mud, converts it into an electrical signal, and transmits it to the adaptive control module. The adaptive control module adjusts the rotary valve 14 based on the pressure data and real-time formation information to ensure that the downhole pressure remains within a safe range.

[0094] The temperature sensor 6 is installed on the downhole drilling tool near the drill bit. This position can accurately reflect the temperature change of the mud in the high-temperature and high-pressure downhole environment. The temperature sensor 6 detects the temperature of the mud and monitors the temperature change of the mud during drilling. The temperature sensor 6 measures the temperature of the mud through the thermistor and transmits the temperature data to the adaptive control module in real time. The adaptive control module adjusts the drilling parameters (such as the mud circulation rate and the cooling system) based on the temperature data to keep the mud within the appropriate temperature range, thereby ensuring that the continuous wave signal is not affected by high temperature.

[0095] The turbine flowmeter 7 is installed in the straight pipe section in the middle of the mud flow pipeline. This position can ensure the stability of fluid flow and reduce the interference of turbulence on flow measurement. The turbine flowmeter 7 measures the mud flow, that is, the volume or mass of mud passing through the pipeline per unit time. The turbine flowmeter 7 senses the flow rate of the mud through the internal turbine rotation, and converts it into an electrical signal, which is transmitted to the valve monitoring module. The mud flow is calculated according to the rotation speed of the turbine. The adaptive control module dynamically adjusts the valve 18 door opening and the mud pump speed according to the flow data to ensure that the mud flow is suitable for the transmission requirements of the continuous wave signal.

[0096] The straight tube density meter 8 is installed at the upstream position of the mud flow pipeline, close to the inlet of the mud pump. This position can measure the density of the mud before it enters the well, ensuring that the density of the mud is within the standard range, and avoiding excessive or excessive density fluctuations that affect the well operation. The straight tube density meter 8 measures the mud flowing through the straight pipe section and uses the principles of buoyancy and gravity to detect the density change of the mud. The measurement data of the straight tube density meter 8 is transmitted to the valve monitoring module through the wireless module. The adaptive control module automatically adjusts the drilling parameters according to the mud density to ensure that the density of the mud remains stable in the well, thereby reducing the risk of leakage or blowout.

[0097] The downhole communication platform I1 and the downhole control platform 3 are both connected to the upper computer 2 through cables; the upper computer 2 is connected to the rotary valve 4 signal through wireless, the rotary valve 4 and the lower computer 9 are connected to the pressure sensor 5, the temperature sensor 6, the turbine flowmeter 7, and the straight tube density meter 8 through cables, and the lower computer 9 is connected to the downhole communication platform II10 through wireless.

[0098] The motor 12 is connected to the position encoder 11 via a cable, the feedback controller 13 is connected to the motor 12 via a cable, the feedback controller 13 and the position encoder 11 are connected wirelessly, the rotary valve 14 is connected to the feedback controller 13 via a cable, and the speed sensor 15 and the displacement sensor 16 are connected to the rotary valve 14 via a cable.

[0099] The formation sensor 17 is connected to the regulating valve 18 through a cable, the regulating valve 18 is connected to the actuator 19 through a wireless connection, the actuator 19 is connected to the embedded processor 20 through a cable, the embedded processor 20 is connected to the data acquisition card 21 through a cable, the data acquisition card 21 is connected to the operating computer 22 through a wired connection, the operating computer 22 is connected to the wireless communication module 23 through a wireless connection, the wireless communication module 23 is connected to the network connection device 24 through a wireless connection, the network connection device 24 is connected to the drive motor 25 through a wired connection, the drive motor 25 is connected to the hydraulic control platform 26 through a pipeline, the hydraulic control platform 26 is connected to the emergency stop device 27 and the explosion-proof device 28 through a wired connection, and the touch screen controller 29, the monitor 30, the operation panel 31 and the operating computer 22 are connected through a wired connection.

[0100] Example 2

[0101] A mud continuous wave measurement while drilling control method comprises the following steps:

[0102] S1: Correction control of the flow area of ​​the rotary valve 14: By adding a measuring device at the valve of the rotary valve 14, the changes of external environmental parameters such as pressure, flow, temperature, density, etc. are monitored. After the monitored information is fed back to the control console, the processor controls and optimizes the flow area of ​​the rotary valve 14 according to the on-site working conditions to obtain a continuous pressure wave signal with better effect;

[0103] S2: Motor 12 position monitoring and control: The position of the motor 12 can be monitored in real time through the position encoder 11. When the position of the motor 12 deviates, the position of the motor 12 can be corrected in combination with feedback control to ensure the normal generation of the continuous wave signal;

[0104] S3: Integrated system control: Based on real-time formation feedback information, the drill bit speed, drilling pressure and other parameters are automatically adjusted during drilling to achieve adaptive optimization during drilling. The control system in S3 integrates the functions of S1 and S2.

[0105] Step S1 specifically includes:

[0106] S101: When the flow rate and density of the drilling fluid change, the flow area of ​​the rotary valve 14 cannot be accurately controlled. At this time, the pressure sensor 5, the temperature sensor 6, the turbine flowmeter 7, and the straight tube density meter 8 start to work to monitor the changes in the pressure, temperature, flow rate, and density of the rotary valve 4;

[0107] S102: After receiving the data from the monitoring devices such as the pressure sensor 5, the temperature sensor 6, the turbine flowmeter 7, and the straight tube density meter 8, the lower computer 9 processes the data and then transmits it to the downhole communication platform II 10. The downhole communication platform II 10 filters, amplifies, and A / D converts the data and then transmits it to the downhole communication platform I1 through the transmission method of radio electromagnetic waves;

[0108] S103: After receiving the data transmitted by the downhole communication platform II10, the downhole communication platform I1 sends it to the upper computer 2 and processes it together with the downhole control platform 3. The downhole control platform 3 timely adjusts the opening of the rotary valve 4 according to the data monitored by multiple sensors, thereby controlling and optimizing the flow area of ​​the rotary valve 14, and subsequently obtaining a continuous pressure wave signal with better effect.

[0109] In step S103, data fusion is first performed based on the data collected by different sensors (pressure, flow, temperature, density, etc.). The data of multiple sensors are processed through fuzzy logic to eliminate the errors that may be caused by the data of a single sensor. Based on the fused data, the priority of each parameter under different working conditions is set. When the pressure sensor 5 detects that the system pressure exceeds the preset threshold, the opening of the rotary valve 4 is reduced to reduce the pressure; when the flow sensor detects that the flow rate decreases, the valve opening is increased to maintain the flow rate stable; if the data of the temperature or density sensor deviates from the normal range, the valve opening is adjusted slightly to ensure the balance of the system.

[0110] In step S103, after the opening is optimized, a continuous pressure wave signal is obtained through the following steps:

[0111] 1). Stabilize the pressure waveform: Adjusting the valve opening can control the flow speed and flow rate of the mud, thereby avoiding pressure fluctuations caused by excessive or insufficient flow. Stable mud flow can produce a smooth pressure waveform, reduce noise and interference, and improve signal clarity and consistency;

[0112] 2) Reduce reflection and interference: The optimized valve opening can better match the downhole environment and drilling conditions, avoiding reflection waves and multiple wave interference caused by improper pressure or flow. By precisely controlling the flow area of ​​the valve, the reflection of the pressure wave signal in the wellbore can be reduced, thereby improving the purity and accuracy of the signal;

[0113] 3). Enhance the consistency of signal amplitude and frequency, control the valve opening so that the amplitude and frequency of the generated pressure wave signal remain within the design range, which helps to improve the consistency and predictability of the signal. Stable valve control can reduce the frequency drift and amplitude fluctuation of the signal, so that the pressure wave signal maintains a high degree of recognizability during long-term transmission;

[0114] 4). Real-time adjustment to cope with changes in the underground environment. The optimized control system can dynamically adjust the valve opening based on real-time monitoring data to cope with changes in the underground environment.

[0115] Step S2 specifically includes:

[0116] S201: When it is necessary to determine whether the motor 12 has completed acceleration, deceleration, and direction change within one rotation, the position and speed of the motor 12 are monitored by the position encoder 11;

[0117] S202: After the speed sensor 15 and the displacement sensor 16 monitor the position and speed of the rotary valve 14, they simultaneously send the rotation data of the motor 12 to the feedback controller 13 for comparison processing, and after comparing with the original position data, feedback control is performed on the motor 12;

[0118] S203: When the feedback controller 13 detects a position deviation, it will re-adjust the position of the motor 12 through the downhole control platform 3. The principle of position adjustment corresponds to the principle of comparison mentioned above. At the same time, the position encoder 11 monitors the position and speed of the motor 12 again until the position deviation is completely eliminated.

[0119] The comparison process of step S202 is specifically as follows: the feedback controller 13 synchronizes and filters the received real-time rotation data to ensure the continuity and accuracy of the data. Filtering can remove measurement noise and ensure the accuracy of the data during the comparison process. The real-time rotation position is compared with the preset target position to calculate the position error. The position error is expressed as the difference between the current actual position and the target position, and the error value = real-time position - target position; the feedback controller 13 analyzes the size and direction of the error value. If the error value is positive, it means that the position of the motor 12 is ahead; if the error value is negative, it means that the position of the motor 12 is lagging. The error change trend is analyzed to determine whether there is a systematic deviation or a temporary deviation in the movement of the motor 12.

[0120] The comparison principles include:

[0121] 1. Minimum error principle: The core goal of the feedback controller 13 is to minimize the position error. This means that at any time, the position of the motor 12 is expected to be as close to the target position as possible to ensure the accuracy and stability of the system.

[0122] 2. Real-time response principle: The feedback control of the motor 12 needs to respond to the change of the error in real time. The controller will decide how to adjust the rotation of the motor 12 according to the size and change rate of the real-time error to quickly correct the deviation and avoid the accumulation of errors leading to system instability.

[0123] 3. Dynamic adjustment principle: According to the actual error size, the feedback controller 13 can dynamically adjust the drive signal of the motor 12 to perform position correction by increasing or decreasing the torque of the motor 12. For smaller errors, the controller may only need to make minor adjustments; for larger errors, more significant adjustments may be required.

[0124] Step S3 specifically includes:

[0125] S301: Install formation sensor 17, temperature sensor 6, pressure sensor 5 and turbine flowmeter 7 to collect various data involved in the drilling process in real time. Formation sensor 17 measures the physical characteristics of the formation, such as rock type, density, strength, etc., to help drilling operators understand the drilling environment and geological conditions; temperature sensor 6 and pressure sensor 5 monitor the temperature and pressure changes in the drilling wellbore to help prevent downhole accidents and optimize drilling parameters. At the same time, turbine flowmeter 7 measures the flow and speed of drilling fluid to provide real-time fluid dynamics information for the drilling process;

[0126] S302: Multiple sensors transmit the collected data to the data processing unit in the feedback controller 13 for subsequent data processing and analysis; the data acquisition card 21 performs data acquisition in real time to ensure that all parameters and conditions in the drilling process can be captured and recorded in a timely manner. The collected data will be sent to the data processing unit for real-time processing and analysis through algorithms and models. The data processing includes steps such as data cleaning, feature extraction, and pattern recognition to ensure the accuracy and reliability of the data. The analysis results will be used for subsequent intelligent decision-making and adjustment and optimization of drilling parameters; a real-time cleaning algorithm is used in the data cleaning process, which can filter noise and detect outliers while collecting data, which is different from the existing technology. Traditional data cleaning is usually performed after data collection, while real-time cleaning can identify and eliminate invalid data more quickly, ensuring that subsequent analysis is based on high-quality data.

[0127] S303: The processed data is fed back to the control system in the feedback controller 13 to provide real-time drilling process monitoring and guidance for the drilling operator; real-time drilling process monitoring can help to timely detect abnormal situations in the drilling process and take corresponding measures to deal with them, so as to ensure drilling safety and efficiency.

[0128] The data processing in S302 is specifically as follows:

[0129] Data cleaning: The data collected by the sensor may contain noise or outliers, so data cleaning is required first.

[0130] Assume that the original data set collected is , i=1,2,…, m , m is the number of data, For the i-th data collected by the corresponding sensor, the cleaning process can be performed by the mean filtering algorithm.

[0131] Use a sliding window to smooth the sensor data. The formula is:

[0132] ;

[0133] in, is the window size, Represents the filtered i data, Represents the filtered j data.

[0134] Feature extraction:

[0135] After cleaning the data, extract features from the sensor data;

[0136] For pressure sensor 5 data:

[0137] Extract the statistical characteristics of pressure fluctuations, including the mean and variance ;

[0138] ;

[0139] in The pressure sensor 5 collects p The first i data points, n Represents the length of each piece of data;

[0140] For temperature sensor 6 data:

[0141] Frequency domain features can be extracted through Fourier transform to analyze the periodic changes in temperature. The formula is:

[0142] ;

[0143] in For time t Temperature data on is the frequency, It is the temperature data The Fourier transform in the frequency domain represents the changes in is the base of natural logarithms, approximately equal to 2.71828, is a complex exponential function, which means that at the frequency The rotation factors below are used to transform the time domain signal into the frequency domain;

[0144] For flow and density data:

[0145] Perform trend analysis on flow and density, and fit flow Q and density by least squares method Linear trend over time:

[0146] ;

[0147] in a, b, c and d is the fitting coefficient, t Represents time;

[0148] Pattern recognition includes the following:

[0149] After feature extraction, the system needs to identify patterns in the data in order to make intelligent decisions. This process is achieved through machine learning or statistical models;

[0150] Classification based on Support Vector Machine (SVM):

[0151] By using the classification algorithm to identify normal operations and abnormal situations, assuming that there is a feature vector , the classification decision function of the support vector machine model is:

[0152] ;

[0153] in, and b are the model parameters obtained through training, For labels, is a kernel function (such as a Gaussian kernel) used to calculate the similarity between two feature vectors;

[0154] State estimation based on Kalman filter:

[0155] The real-time data of the sensor is used to estimate the state of the system through the Kalman filter. t (such as mud flow rate, drilling pressure, etc.), the update formula is:

[0156] ;

[0157] in, A is the state transfer matrix, B is the control input matrix, For input, is the process noise.

[0158] Furthermore, intelligent decision-making and parameter optimization specifically include the following steps:

[0159] After processing and analyzing the sensor data, the system makes intelligent decisions and optimizes drilling parameters;

[0160] Based on feedback control theory, the adaptive control module adjusts the drilling pressure according to the data fed back by the sensor. W and drilling speed R , drilling pressure W The formula is:

[0161] ;

[0162] in, is the real-time pressure, is the target pressure, It is the proportional gain, which adjusts the drilling pressure through feedback. It is the gain parameter in the proportional controller. This parameter can be adjusted manually according to the working conditions on site. It is used to adjust the drilling pressure. W In response to the error between the actual pressure and the target pressure.

[0163] Sure The following aspects can be considered:

[0164] (1) By adjusting under different working conditions To obtain the best drilling efficiency and system response speed.

[0165] (2) Use physical models or numerical simulations to establish the relationship between formation response and pressure feedback, and solve the appropriate Based on the above description, those skilled in the art can already know how to solve , so this application will not be repeated here.

[0166] Drilling speed R The adjustment idea is based on drilling pressure W The optimization process is based on the multi-factors of the drill bit, formation feedback (such as pressure, temperature, etc.), drill bit torque and vibration signals. The specific steps are as follows: the sensor monitors the mechanical parameters of the drill bit (torque, vibration) and formation parameters (pressure, density) in real time, and the real-time pressure obtained by the sensor is used to With target pressure The difference between the pressure error and the drilling state error is used to determine whether the current drilling state is ideal. and drilling pressure adjustment, drilling speed RIt automatically adjusts as the error increases or decreases, allowing the drill bit to achieve the optimal drilling state under different formation conditions.

[0167] The formula correlation between pattern recognition and feedback control is mainly reflected in data analysis and modeling, error judgment and dynamic adjustment, and gain adjustment. Specifically, pattern recognition can be used to extract important features or patterns from a large amount of drilling data to help identify the drilling status of different formations. These patterns can provide a basis for feedback control and help optimize parameter adjustment strategies; pattern recognition can help distinguish between normal drilling status and abnormal status. By identifying pattern changes in pressure signals, vibration signals, etc., the system can automatically determine whether the drilling pressure needs to be adjusted. W Or drilling speed R ; The pattern recognition system can dynamically adjust the controller gain parameters , based on different formation conditions and real-time drilling data, adjust the controller's response speed and accuracy.

[0168] Example 3

[0169] like Figure 1-Figure 3 As shown, a mud continuous wave measurement while drilling control system includes: a downhole communication platform I1, a host computer 2, a downhole control platform 3, a rotary valve 4, a pressure sensor 5, a temperature sensor 6, a turbine flowmeter 7, a straight tube density meter 8, a lower computer 9, a downhole communication platform II10, a position encoder 11, a motor 12, a feedback controller 13, a rotary valve 14, a speed sensor 15, a displacement sensor 16, a formation sensor 17, a regulating valve 18, an actuator 19, an embedded processor 20, a data acquisition card 21, an operating computer 22, a wireless communication module 23, a network connection device 24, a drive motor 25, a hydraulic control platform 26, an emergency stop device 27, an explosion-proof device 28, a touch screen controller 29, a monitor 30, and an operation panel 31.

[0170] The pressure sensor 5, the temperature sensor 6, the turbine flowmeter 7, and the straight tube density meter 8 monitor the relevant parameters of the rotary valve 4 in real time, and take corresponding measures to correct them after the flow area thereof changes.

[0171] A method for using a mud continuous wave measurement while drilling control system is as follows:

[0172] S1: Flow area correction control

[0173] S101: When the flow rate and density of the drilling fluid change, the flow area of ​​the rotary valve 14 cannot be accurately controlled. At this time, the pressure sensor 5, the temperature sensor 6, the turbine flowmeter 7, and the straight tube density meter 8 start to work to monitor the changes in the pressure, temperature, flow rate and density of the rotary valve 4;

[0174] S102: After receiving the data from the monitoring devices such as the pressure sensor 5, the temperature sensor 6, the turbine flowmeter 7, and the straight tube density meter 8, the lower computer 9 processes the data and then transmits it to the downhole communication platform II 10. The downhole communication platform II 10 further processes the data, and after filtering, amplification, and A / D conversion, transmits the data to the downhole communication platform I1 through the transmission mode of radio electromagnetic waves;

[0175] S103: After receiving the data transmitted by the downhole communication platform II10, the downhole communication platform I1 sends it to the upper computer 2 and processes it together with the downhole control platform 3. The downhole control platform 3 timely adjusts the opening of the rotary valve 4 according to the data monitored by many sensors, thereby controlling and optimizing the flow area of ​​the rotary valve 14, and subsequently obtaining a continuous pressure wave signal with better effect;

[0176] S2: Position monitoring control

[0177] S201: When it is necessary to determine whether the motor 12 has completed acceleration, deceleration, and direction change within one rotation, the position and speed of the motor 12 are monitored by the position encoder 11;

[0178] S202: After the speed sensor 15 and the displacement sensor 16 monitor the position and speed of the rotary valve 14, they simultaneously send the rotation data of the motor 12 to the feedback controller 13 for comparison processing, and after comparing with the original position data, feedback control is performed on the motor 12;

[0179] S203: When the feedback controller 13 detects that the position deviation occurs, it will re-adjust the position of the motor 12 through the downhole control platform 3, and the position encoder 11 will monitor the position and speed of the motor 12 again until the position deviation is completely eliminated.

[0180] S3: Adaptive Control Module

[0181] S301: The automated drilling system will be equipped with formation sensors 17, temperature sensors 6, pressure sensors 5, and turbine flowmeters 7, which are used to collect various data involved in the drilling process in real time. The formation sensor 17 can measure the physical properties of the formation, such as rock type, density, strength, etc., to help drilling operators understand the drilling environment and geological conditions. The temperature sensor 6 and the pressure sensor 5 can monitor the temperature and pressure changes in the drilling wellbore to help prevent downhole accidents and optimize drilling parameters. At the same time, the turbine flowmeter 7 can measure the flow and velocity of the drilling fluid and provide real-time fluid dynamics information for the drilling process.

[0182] S302: The sensor system will transmit the collected data to the data processing unit or control system for subsequent data processing and analysis. The data acquisition card 21 can collect data in real time to ensure that all parameters and conditions in the drilling process can be captured and recorded in a timely manner. The collected data will be sent to the data processing unit for real-time analysis and processing through algorithms and models. Data processing includes steps such as data cleaning, feature extraction, and pattern recognition to ensure the accuracy and reliability of the data. The analysis results will be used for subsequent intelligent decision-making and adjustment and optimization of drilling parameters.

[0183] S303: The processed data will be fed back to the control system to provide real-time monitoring and guidance of the drilling process for the drilling operator. Real-time monitoring can help to timely detect abnormal situations in the drilling process and take corresponding measures to deal with them to ensure drilling safety and efficiency.

[0184] Obviously, the above embodiments are merely examples for clear explanation, and are not intended to limit the implementation methods. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived from them are still within the protection scope of the invention.

Claims

1. A mud continuous wave measurement while drilling control system, characterized in that: It comprises a valve monitoring module, a position monitoring module and an adaptive control module; the valve monitoring module and the position monitoring module are two independent monitoring modules, which respectively monitor and correct the flow area of ​​the rotary valve (14) and the rotation position of the motor (12); the valve monitoring module and the position monitoring module are integrated in the adaptive control module, and the adaptive control module dynamically adjusts the valve monitoring module and the position monitoring module according to the data provided by the sensor; The sensors include a formation sensor (17), a pressure sensor (5), a temperature sensor (6), a turbine flowmeter (7) and a straight tube density meter (8), wherein the formation sensor (17) measures physical properties of the formation, the pressure sensor is installed on a mud flow channel close to a rotary valve, the temperature sensor is installed on a portion of a downhole drilling tool close to a drill bit, the turbine flowmeter is installed on a straight pipe section in the middle of a mud flow pipeline, and the straight tube density meter (8) is installed at an upstream position of the mud flow pipeline, close to an inlet of a mud pump; Data fusion is performed based on the data collected by different sensors. The data of multiple sensors are processed through fuzzy logic to eliminate the errors that may be caused by the data of a single sensor. Based on the fused data, the priority of each parameter under different working conditions is set. When the pressure sensor (5) detects that the system pressure exceeds a preset threshold, the opening of the rotary valve (4) is reduced to reduce the pressure; when the flow sensor detects that the flow rate decreases, the valve opening is increased to maintain the flow rate stable; if the data of the temperature or density sensor deviates from the normal range, the valve opening is adjusted slightly to ensure the balance of the system, and the opening of the rotary valve (4) is adjusted in time, so as to control and optimize the flow area of ​​the rotary valve (14), so that a continuous pressure wave signal with better effect can be obtained later; The feedback controller (13) of the position monitoring module dynamically adjusts the drive signal of the motor (12) to perform position correction by increasing or decreasing the rotational torque of the motor (12).

2. A mud continuous wave measurement while drilling control system according to claim 1, characterized in that: The valve monitoring module comprises: a downhole communication platform I (1), an upper computer (2), a downhole control platform (3), a lower computer (9) and a downhole communication platform II (10); the downhole communication platform I (1) and the downhole control platform (3) are both connected to the upper computer (2) by signal; the upper computer (2) is respectively connected to the pressure sensor (5), the temperature sensor (6), the turbine flowmeter (7) and the straight tube density meter (8) by signal through a rotary valve (4); the lower computer (9) is connected to the pressure sensor (5), the temperature sensor (6), the turbine flowmeter (7) and the straight tube density meter (8) by signal; and the lower computer (9) is connected to the downhole communication platform II (10) by signal; The position monitoring module comprises: a position encoder (11), a motor (12) and a feedback controller (13), wherein the motor (12) is connected to the position encoder (11) and the feedback controller (13) respectively, the feedback controller (13) is connected to the position encoder (11) and the rotary valve (14), and the rotary valve (14) is connected to the speed sensor (15) and the displacement sensor (16); The adaptive control module comprises: an operating computer (22), a wireless communication module (23) and a network connection device (24); the operating computer (22) is respectively connected to the wireless communication module (23) and the network connection device (24); the wireless communication module (23) and the network connection device (24) are respectively connected to an operating panel (31); the operating panel (31) is connected to an embedded processor (20), a touch screen controller (29) and a monitor (30); the embedded processor (20), the touch screen controller (29) and the monitor (30) are connected to a hydraulic control platform (26); the hydraulic control platform (26) is connected to an actuator (19) and a drive motor (25); the actuator (19) and the drive motor (25) are connected to a regulating valve (18); the regulating valve (18) is respectively connected to a data acquisition card (21), an emergency stop device (27) and an explosion-proof device (28); the data acquisition card (21) is respectively connected to a formation sensor (17), a pressure sensor (5), a temperature sensor (6) and a turbine flowmeter (7).

3. A mud continuous wave measurement while drilling control system according to claim 2, characterized in that: The pressure sensor (5) senses the change in the pressure of the liquid column of the mud, converts it into an electrical signal, and transmits it to the adaptive control module. The adaptive control module adjusts the rotary valve (14) based on the pressure data and in combination with real-time formation information. The temperature sensor (6) measures the temperature of the mud through a thermosensitive element and transmits the temperature data to the adaptive control module in real time. The adaptive control module adjusts the drilling parameters based on the temperature data. The turbine flowmeter (7) ensures the stability of fluid flow and reduces the interference of turbulence on flow measurement. The turbine flowmeter (7) senses the flow rate of the mud through the rotation of the internal turbine and converts it into an electrical signal, which is transmitted to the valve monitoring module. The flow rate of the mud is calculated according to the rotation speed of the turbine. The adaptive control module dynamically adjusts the valve opening and the mud pump speed according to the flow data; The straight tube density meter (8) measures the density of the mud before it enters the well. The straight tube density meter (8) measures the mud flowing through the straight tube section and uses the principles of buoyancy and gravity to detect the density change of the mud. The measurement data of the straight tube density meter (8) is transmitted to the valve monitoring module through the wireless module, and the adaptive control module automatically adjusts the drilling parameters according to the mud density.

4. A mud continuous wave measurement while drilling control system according to claim 2, characterized in that: The downhole communication platform I (1) and the downhole control platform (3) are both connected to the upper computer (2) via cables; the upper computer (2) is connected to the rotary valve (4) signal via wireless, the rotary valve (4) and the lower computer (9) are both connected to the pressure sensor (5), the temperature sensor (6), the turbine flowmeter (7), and the straight tube density meter (8) via cables, and the lower computer (9) is connected to the downhole communication platform II (10) via wireless.

5. A mud continuous wave measurement while drilling control system according to claim 2, characterized in that: The motor (12) is connected to the position encoder (11) via a cable, the feedback controller (13) is connected to the motor (12) via a cable, the feedback controller (13) and the position encoder (11) are connected wirelessly, the rotary valve (14) is connected to the feedback controller (13) via a cable, and the speed sensor (15) and the displacement sensor (16) are connected to the rotary valve (14) via a cable.

6. A mud continuous wave measurement while drilling control system according to claim 2, characterized in that: The formation sensor (17) is connected to the regulating valve (18) via a cable, the regulating valve (18) is connected to the actuator (19) via a wireless connection, the actuator (19) is connected to the embedded processor (20) via a cable, the embedded processor (20) is connected to the data acquisition card (21) via a cable, the data acquisition card (21) is connected to the operating computer (22) via a wired connection, the operating computer (22) is connected to the wireless communication module (23) via a wireless connection, the wireless communication module (23) is connected to the network connection device (24) via a wireless connection, the network connection device (24) is connected to the drive motor (25) via a wired connection, the drive motor (25) is connected to the hydraulic control platform (26) via a pipeline, the hydraulic control platform (26) is connected to the emergency stop device (27) and the explosion-proof device (28) via a wired connection, and the touch screen controller (29), the monitor (30), the operation panel (31) and the operating computer (22) are connected via a wired connection.

7. A mud continuous wave measurement while drilling control method, characterized in that: The following steps are involved: S1: Rotary valve (14) flow area correction control: by adding a measuring device at the valve of the rotary valve (14), the changes of external environmental pressure, flow, temperature and density parameters are monitored. After the monitored information is fed back to the control console, the flow area of ​​the rotary valve (14) is controlled and optimized; S2: Motor (12) position monitoring control: The position of the motor (12) can be monitored in real time through the position encoder (11). When the position of the motor (12) deviates, the position of the motor (12) can be corrected in combination with feedback control; S3: Integrated system control: Automatically adjust the drill bit speed and drilling pressure parameters during drilling based on real-time formation feedback information; Step S1 specifically includes: S101: When the flow rate and density of the drilling fluid change, the pressure sensor (5), the temperature sensor (6), the turbine flow meter (7), and the straight tube density meter (8) start to work to monitor the changes in the pressure, temperature, flow rate, and density of the rotary valve (4); S102: After receiving the data from the pressure sensor (5), the temperature sensor (6), the turbine flow meter (7), and the straight tube density meter (8), the lower computer (9) processes the data and then transmits it to the downhole communication platform II (10). The downhole communication platform II (10) filters, amplifies, and performs A / D conversion on the data and then transmits it to the downhole communication platform I (1) via a wireless electromagnetic wave transmission method; S103: After receiving the data transmitted by the downhole communication platform II (10), the downhole communication platform I (1) sends the data to the upper computer (2) and processes the data in conjunction with the downhole control platform (3). The downhole control platform (3) adjusts the opening of the rotary valve (4) according to the data monitored by the multiple sensors, thereby optimizing the flow area of ​​the rotary valve (14); Step S2 specifically includes: S201: When it is necessary to determine whether the motor (12) has completed acceleration, deceleration and direction change within one rotation, the position and rotation speed of the motor (12) are monitored by the position encoder (11); S202: After the speed sensor (15) and the displacement sensor (16) monitor the position and rotation speed of the rotary valve (14), they simultaneously send the rotation data of the motor (12) to the feedback controller (13) for comparison processing, and after comparing with the original position data, feedback control is performed on the motor (12); S203: When the feedback controller (13) detects that a position deviation occurs, the position of the motor (12) is re-adjusted through the downhole control platform (3), and the position encoder (11) monitors the position and speed of rotation of the motor (12) again until the position deviation is completely eliminated.

8. A mud continuous wave measurement while drilling control method according to claim 7, characterized in that: In step S103, data fusion is first performed based on the data collected by different sensors. The data of multiple sensors are processed through fuzzy logic to eliminate the error caused by the data of a single sensor. Based on the fused data, the priority of each parameter under multiple working conditions is set. When the pressure sensor (5) detects that the system pressure exceeds a preset threshold, the opening of the rotary valve (4) is reduced to reduce the pressure; when the flow sensor detects that the flow rate is reduced, the valve opening is increased to maintain the flow rate stable.

9. A mud continuous wave measurement while drilling control method according to claim 7, characterized in that: The comparison process of step S202 is specifically as follows: the feedback controller (13) synchronizes and filters the received real-time rotation data, compares the real-time rotation position with the preset target position, and calculates the position error. The position error is represented by the difference between the current actual position and the target position, and the error value = real-time position - target position; The feedback controller (13) analyzes the size and direction of the error value. If the error value is positive, it indicates that the position of the motor (12) is ahead; if the error value is negative, it indicates that the position of the motor (12) is lagging. The error change trend is analyzed to determine whether there is a systematic deviation or a temporary deviation in the movement of the motor (12).

10. The mud continuous wave measurement while drilling control method according to claim 7, characterized in that: Step S3 specifically includes: S301: Installing a formation sensor (17), a temperature sensor (6), a pressure sensor (5) and a turbine flow meter (7) to collect data related to the drilling process in real time, wherein the formation sensor (17) measures physical properties of the formation, the temperature sensor (6) and the pressure sensor (5) monitor temperature and pressure changes in the drilling wellbore, and the turbine flow meter (7) measures the flow rate and velocity of the drilling fluid; S302: The multiple sensors transmit the collected data to the data processing unit in the feedback controller (13) for subsequent data processing and analysis; the data acquisition card (21) performs real-time data acquisition, and the collected data is sent to the data processing unit for real-time processing and analysis. The data processing includes data cleaning, feature extraction, and pattern recognition steps. The analysis results are used for subsequent intelligent decision-making and adjustment and optimization of drilling parameters; S303: The processed data is fed back to the control system in the feedback controller (13) to provide real-time drilling process monitoring and guidance for the drilling operator.

11. A mud continuous wave measurement while drilling control method according to claim 10, characterized in that: The data processing in S302 is specifically as follows: Data cleaning: Assume that the original data set collected is , i=1,2,…, m , m is the number of data, For the i-th data collected by the corresponding sensor, the cleaning process uses a filtering algorithm to perform mean filtering, and uses a sliding window to smooth the sensor data. The formula is: ； in, is the window size, Represents the filtered i data, Represents the filtered j individual data; Feature extraction: After cleaning the data, extract features from the sensor data; For pressure sensor (5) data: Extract the statistical characteristics of pressure fluctuations, including the mean and variance ; ； in The first p The first i data points, n Represents the length of each piece of data; For temperature sensor (6) data: The frequency domain features are extracted by Fourier transform to analyze the periodic changes of temperature. The formula is: ； in For time t Temperature data on is the frequency, It is the temperature data The Fourier transform in the frequency domain represents the changes in is the base of natural logarithms, is a complex exponential function, which means that at frequency The rotation factor below is used to transform the time domain signal into the frequency domain; For flow and density data: Perform trend analysis on flow and density, and fit flow Q and density by least squares method Linear trend over time: ； in a, b, c and d is the fitting coefficient, t Represents time; Pattern recognition: After feature extraction, the system needs to identify patterns in the data, which is achieved through machine learning or statistical models; Classification based on support vector machine: Identify normal operation and abnormal situation through classification algorithm, assuming that there is a feature vector , the classification decision function of the support vector machine model is: ； in, and b are the model parameters obtained through training, For labels, is the kernel function, which is used to calculate the similarity between two feature vectors; State estimation based on Kalman filter: The real-time data of the sensor is estimated, and the state x of the system is estimated through the Kalman filter. t , and its update formula is: ； in, A is the state transfer matrix, B is the control input matrix, For input, is the process noise.

12. A mud continuous wave measurement while drilling control method according to claim 11, characterized in that: The intelligent decision-making and parameter optimization in S302 include the following steps: After processing and analyzing the sensor data, the system makes intelligent decisions and optimizes drilling parameters; Based on feedback control theory, the adaptive control module adjusts the drilling pressure according to the data fed back by the sensor. W and drilling speed R , drilling pressure W The formula is: ； in, is the real-time pressure, is the target pressure, It is the proportional gain, which adjusts the drilling pressure through feedback; Drilling speed R The adjustment idea is: the sensor monitors the mechanical parameters of the drill bit and the formation parameters in real time, and the real-time pressure obtained by the sensor With target pressure The difference between the pressure error and the drilling state error is used to determine whether the current drilling state is ideal. and drilling pressure W Adjustment of drilling speed R It automatically adjusts as the error increases or decreases, allowing the drill bit to achieve the optimal drilling state under different formation conditions.

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