[go: up one dir, main page]

CN108387205B - Measurement method of drilling tool attitude measurement system based on multi-sensor data fusion - Google Patents

Measurement method of drilling tool attitude measurement system based on multi-sensor data fusion Download PDF

Info

Publication number
CN108387205B
CN108387205B CN201810056220.4A CN201810056220A CN108387205B CN 108387205 B CN108387205 B CN 108387205B CN 201810056220 A CN201810056220 A CN 201810056220A CN 108387205 B CN108387205 B CN 108387205B
Authority
CN
China
Prior art keywords
drilling tool
attitude
state
local
measurement
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201810056220.4A
Other languages
Chinese (zh)
Other versions
CN108387205A (en
Inventor
高怡
毛艳慧
杨�一
陈晨
汪跃龙
程为彬
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xian Shiyou University
Original Assignee
Xian Shiyou University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Xian Shiyou University filed Critical Xian Shiyou University
Priority to CN201810056220.4A priority Critical patent/CN108387205B/en
Publication of CN108387205A publication Critical patent/CN108387205A/en
Application granted granted Critical
Publication of CN108387205B publication Critical patent/CN108387205B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C1/00—Measuring angles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Gyroscopes (AREA)
  • Navigation (AREA)

Abstract

The invention discloses a measuring method of a drilling tool attitude measuring system based on multi-sensor data fusion, wherein the drilling tool dynamic attitude measuring system based on the multi-sensor data fusion comprises a drilling tool, a triaxial accelerometer, a triaxial fluxgate, an angular rate gyroscope and a local filter; the triaxial accelerometer, the triaxial fluxgate and the angular rate gyroscope are all arranged on the drilling tool, and the triaxial accelerometer, the triaxial fluxgate and the angular rate gyroscope are respectively provided with a local filter; the matrix weighted data fusion algorithm provided by the invention does not need to process local state estimation, overcomes the defects of the standard UKF algorithm, and does not need to reset a local filter through global state estimation, thereby having stronger fault tolerance.

Description

Measuring method of drilling tool attitude measuring system based on multi-sensor data fusion
Technical Field
The invention belongs to the technical field of petroleum drilling engineering, and particularly relates to a measuring method of a drilling tool attitude measuring system based on multi-sensor data fusion.
Background
With the continuous development of the petroleum industry and the extremely severe exploitation situation, the existing methods adopt the methods of improving the recovery ratio, exploiting the hard-to-exploit/hard-to-exploit reserves, developing residual petroleum resources, special economic marginal oil reservoirs such as low-permeability, ultrathin, heavy oil and ultra-heavy oil, and scarce resources such as shale gas and coal bed gas; deep stratum and deep sea area are developed by deep/ultra deep well vertical drilling. Guided drilling technology is an important tool to solve the above problems.
Real-time measurement of downhole dynamic attitude parameters (borehole inclination, azimuth and toolface angle) is a prerequisite for enabling real-time steering control of a steerable drilling tool. Therefore, in the drilling engineering, the requirements for real-time performance, accuracy and continuous and dynamic measurement of the downhole attitude parameter are higher and higher. However, the near bit of the downhole drilling tool directly bears the strong vibration generated when the drill bit breaks rock and the rotary vibration of the drill string, so that the output signal of the sensor is mixed with a large amount of interference and noise, and the attitude parameter measurement is inaccurate.
The attitude parameter measurement of home and abroad guiding drilling tools mostly adopts a static measurement method, namely the attitude parameter measurement is carried out under the condition that a drilling tool does not rotate or vibrate. At present, mainly by taking the reference of an inertial measurement technology and a geomagnetic field, a triaxial accelerometer or a triaxial magnetometer is independently used for completion or is simply combined with the triaxial accelerometer or the magnetometer, the three accelerometers measure the gravitational field component of the earth, and the three magnetometers measure the geomagnetic field component of the earth. Although the method can meet the requirement of attitude measurement accuracy, the attitude measurement accuracy is obtained instead of sacrificing cost and drilling time effectiveness, or the inertial measurement technology is used, the sensor is simply combined and measured based on the geomagnetic field or the gyroscope, the influence of a near drill bit is caused, the output error of the sensor is larger, and the measurement is inaccurate or even can not be measured.
Disclosure of Invention
The invention aims to provide a measuring method of a drilling tool attitude measuring system based on multi-sensor data fusion, so as to solve the problems.
In order to achieve the purpose, the invention adopts the following technical scheme:
the measuring method of the drilling tool attitude measuring system based on the multi-sensor data fusion comprises the steps that the drilling tool dynamic attitude measuring system based on the multi-sensor data fusion comprises a drilling tool, a triaxial accelerometer, a triaxial fluxgate, an angular rate gyroscope and a local filter; the triaxial accelerometer, the triaxial fluxgate and the angular rate gyroscope are all arranged on the drilling tool, and the triaxial accelerometer, the triaxial fluxgate and the angular rate gyroscope are respectively provided with a local filter; the measuring method of the drilling tool dynamic attitude measuring system based on multi-sensor data fusion comprises the following steps:
the method comprises the following steps: establishing an ideal orthogonal geographic coordinate system in an attitude measurement system, and according to Euler's theorem, in the underground drilling process, expressing any attitude of the drilling tool in space by a series of rotations relative to the geographic coordinate system, wherein the rotation angles are a well inclination angle, an azimuth angle and a tool face angle; according to the definition of quaternion and Euler's theorem, the three-dimensional space is connected with the four-dimensional space, and the quaternion property and the operation rule of the four-dimensional space are used for researching the rigid body fixed point rotation problem in the three-dimensional space;
step two: installing a triaxial accelerometer, a triaxial fluxgate and an angular rate gyroscope aiming at a drilling tool, realizing the attitude combination measurement of a guiding drilling tool, and jointly establishing a nonlinear mathematical model of a multi-sensor and dynamic measurement system to obtain a nonlinear state equation and a measurement equation;
step three: judging the motion state of the drilling tool according to the characteristic of the near-bit vibration signal, and analyzing the relationship between the motion state of the drilling tool and the vibration acceleration and main interference factors of the vibration of the drilling tool; according to the model and the noise characteristics, local filters are respectively adopted, an unscented Kalman filtering algorithm is used for filtering interference signals, the influence of near-bit strong vibration on attitude parameter measurement is eliminated, global estimation is carried out by adopting a data fusion theory, and then optimal attitude estimation is obtained;
step four: and carrying out attitude dynamic calculation on the filtered sensor parameters by utilizing the optimal attitude estimation, thereby obtaining the accurate attitude parameters of the filtered guiding drilling tool.
Further, the step three of eliminating the influence of the strong vibration of the near-bit on the dynamic attitude measurement by local filtering comprises the following steps:
step 1: discretizing a state equation and a measurement equation based on quaternions;
step 2: in the first layer, the triaxial acceleration signal, the triaxial fluxgate signal and the angular rate gyro signal are respectively passed through three local filters, namely a first local filter, a second local filter and a third local filter, and local optimal state estimation values of the three local filters are obtained in a parallel manner
Figure BDA0001553898210000031
And error covariance matrix
Figure BDA0001553898210000032
And step 3: in the second layer, fusing the obtained local state estimation values by applying a matrix weighted data fusion algorithm to obtain the global optimal estimation of the system state; assuming that the state estimates obtained by the first and second local filters are
Figure BDA0001553898210000033
And
Figure BDA0001553898210000034
under the linear minimum variance criterion, the global optimum state of the system state is estimated as
Figure BDA0001553898210000035
At this time, the process of the present invention,
Figure BDA0001553898210000036
error covariance matrix of less than
Figure BDA0001553898210000037
And
Figure BDA0001553898210000038
error covariance matrix of, i.e.
Figure BDA0001553898210000039
The global optimum state of the system state is estimated as
Figure BDA00015538982100000310
Figure BDA00015538982100000311
Local state estimation
Figure BDA00015538982100000312
And
Figure BDA00015538982100000313
cross covariance matrix of each other
Figure BDA00015538982100000314
Having the following recursion forms
Figure BDA00015538982100000315
And 4, step 4: according to the fusion local state estimation value, further obtaining the global optimal state estimation method of the strong vibration rotary drilling tool system; setting the state estimates obtained by N local filters to be respectively
Figure BDA00015538982100000316
Corresponding error covariance matrices are respectively
Figure BDA00015538982100000317
(that is to say
Figure BDA00015538982100000318
)，
Figure BDA00015538982100000319
And
Figure BDA00015538982100000320
the cross covariance matrix of
Figure BDA00015538982100000321
Note the book
Figure BDA00015538982100000322
Figure BDA00015538982100000323
Figure BDA00015538982100000324
Based on matrix weighting, the overall optimal estimation of the state of the multi-sensor system is
Figure BDA00015538982100000325
Wherein, wi(i ═ 1, 2.. times.n) is an optimal weight matrix, and can be calculated by the following formula
Figure BDA00015538982100000326
Further, attitude parameters are dynamically extracted, and in the third layer, after coordinate conversion is carried out from the geographic coordinate system to the drilling tool coordinate system, a well inclination angle theta and a tool face angle phi can be obtained:
Figure BDA0001553898210000041
and (5) resolving the global optimal estimation value obtained after filtering through the drilling tool attitude according to the formula (5) to obtain the dynamic attitude parameter of the guided drilling tool.
Further, the geographic coordinate system is a northeast coordinate system, and the positive rotation direction of the geographic coordinate system is determined by a right-hand rule.
Compared with the prior art, the invention has the following technical effects:
the method is based on modeling of a multi-degree-of-freedom attitude sensor and a matrix weighting multi-sensor data fusion technology, three sensor parameters of a triaxial accelerometer, a triaxial fluxgate and an angular rate gyroscope are firstly adopted for local filtering in a parallel processing mode, and then data fusion is carried out on the multi-sensor measurement parameters to obtain global optimal estimation. The near-bit strong vibration signal characteristic analysis and attitude information extraction technology aims at the influence of a near-bit on dynamic attitude measurement by judging the near-bit motion state of a guiding drilling tool, eliminates interference and realizes accurate extraction of attitude measurement information.
The matrix weighted data fusion algorithm provided by the invention does not need to process local state estimation, overcomes the defects of the standard UKF algorithm, and does not need to reset a local filter through global state estimation, thereby having stronger fault tolerance.
Drawings
FIG. 1 is a structural diagram of a dynamic measurement system of a strong vibration rotary drilling tool based on matrix weighting multi-sensor data fusion.
Fig. 2 is a pose angle in a geographical coordinate system and a tool coordinate system.
In the attached fig. 2: h is the horizontal plane, V is the borehole bending plane, and P represents the drill cross-section. Psi is the azimuth angle, theta is the well angle, and phi is the toolface angle. "E-N-U" stands for "northeast". XYZ is the drill coordinate system.
Detailed Description
The invention is further described below with reference to the accompanying drawings:
referring to fig. 1 and 2, a measuring method of a drilling tool attitude measuring system based on multi-sensor data fusion, wherein the drilling tool dynamic attitude measuring system based on multi-sensor data fusion includes a drilling tool, a triaxial accelerometer, a triaxial fluxgate, an angular rate gyroscope and a local filter; the triaxial accelerometer, the triaxial fluxgate and the angular rate gyroscope are all arranged on the drilling tool, and the triaxial accelerometer, the triaxial fluxgate and the angular rate gyroscope are respectively provided with a local filter; the measuring method of the drilling tool dynamic attitude measuring system based on multi-sensor data fusion comprises the following steps:
the method comprises the following steps: establishing an ideal orthogonal geographic coordinate system in an attitude measurement system, and according to Euler's theorem, in the underground drilling process, expressing any attitude of the drilling tool in space by a series of rotations relative to the geographic coordinate system, wherein the rotation angles are a well inclination angle, an azimuth angle and a tool face angle; according to the definition of quaternion and Euler's theorem, the three-dimensional space is connected with the four-dimensional space, and the quaternion property and the operation rule of the four-dimensional space are used for researching the rigid body fixed point rotation problem in the three-dimensional space;
step two: installing a triaxial accelerometer, a triaxial fluxgate and an angular rate gyroscope aiming at a drilling tool, realizing the attitude combination measurement of a guiding drilling tool, and jointly establishing a nonlinear mathematical model of a multi-sensor and dynamic measurement system to obtain a nonlinear state equation and a measurement equation;
step three: judging the motion state of the drilling tool according to the characteristic of the near-bit vibration signal, and analyzing the relationship between the motion state of the drilling tool and the vibration acceleration and main interference factors of the vibration of the drilling tool; according to the model and the noise characteristics, local filters are respectively adopted, an unscented Kalman filtering algorithm is used for filtering interference signals, the influence of near-bit strong vibration on attitude parameter measurement is eliminated, global estimation is carried out by adopting a data fusion theory, and then optimal attitude estimation is obtained;
step four: and carrying out attitude dynamic calculation on the filtered sensor parameters by utilizing the optimal attitude estimation, thereby obtaining the accurate attitude parameters of the filtered guiding drilling tool.
The method for eliminating the influence of the strong vibration of the near-bit on the dynamic attitude measurement by local filtering in the third step comprises the following steps:
step 1: discretizing a state equation and a measurement equation based on quaternions;
step 2: in the first layer, the triaxial acceleration signal, the triaxial fluxgate signal and the angular rate gyro signal are respectively passed through three local filters, namely a first local filter, a second local filter and a third local filter, and local optimal state estimation values of the three local filters are obtained in a parallel manner
Figure BDA0001553898210000051
And error covariance matrix
Figure BDA0001553898210000052
And step 3: in the second layer, fusing the obtained local state estimation values by applying a matrix weighted data fusion algorithm to obtain the global optimal estimation of the system state; assuming that the state estimates obtained by the first and second local filters are
Figure BDA0001553898210000053
And
Figure BDA0001553898210000054
under the linear minimum variance criterion, the global optimum state of the system state is estimated as
Figure BDA0001553898210000055
At this time, the process of the present invention,
Figure BDA0001553898210000056
error covariance matrix of less than
Figure BDA0001553898210000057
And
Figure BDA0001553898210000058
error covariance matrix of, i.e.
Figure BDA0001553898210000059
The global optimum state of the system state is estimated as
Figure BDA0001553898210000061
Figure BDA0001553898210000062
Local state estimation
Figure BDA0001553898210000063
And
Figure BDA0001553898210000064
cross covariance matrix of each other
Figure BDA0001553898210000065
Having the following recursion forms
Figure BDA0001553898210000066
And 4, step 4: according to the fusion local state estimation value, further obtaining the global optimal state estimation method of the strong vibration rotary drilling tool system; setting the state estimates obtained by N local filters to be respectively
Figure BDA0001553898210000067
Corresponding error covariance matrices are respectively
Figure BDA0001553898210000068
(that is to say
Figure BDA0001553898210000069
)，
Figure BDA00015538982100000610
And
Figure BDA00015538982100000611
the cross covariance matrix of
Figure BDA00015538982100000612
Note the book
Figure BDA00015538982100000613
Figure BDA00015538982100000614
Based on matrix weighting, the overall optimal estimation of the state of the multi-sensor system is
Figure BDA00015538982100000615
Wherein, wi(i＝1,2, N) is an optimal weight matrix, which can be calculated by the following formula
Figure BDA00015538982100000616
And dynamically extracting attitude parameters, and in the third layer, performing coordinate conversion from a geographic coordinate system to a drilling tool coordinate system to obtain a well inclination angle theta and a tool face angle phi:
Figure BDA00015538982100000617
and (5) resolving the global optimal estimation value obtained after filtering through the drilling tool attitude according to the formula (5) to obtain the dynamic attitude parameter of the guided drilling tool.
The geographic coordinate system is a northeast coordinate system, and the positive rotation direction of the geographic coordinate system is determined by a right-hand rule.

Claims (3)

1.基于多传感器数据融合的钻具姿态测量系统的测量方法，其特征在于，基于多传感器数据融合的钻具动态姿态测量系统包括钻具、三轴加速度计、三轴磁通门、角速率陀螺仪和滤波器；三轴加速度计、三轴磁通门、角速率陀螺仪和滤波器均安装在钻具上，三轴加速度计、三轴磁通门和角速率陀螺仪分别连接各自对应的滤波器；基于多传感器数据融合的钻具动态姿态测量系统的测量方法包括以下步骤：1. the measurement method of the drilling tool attitude measurement system based on multi-sensor data fusion, is characterized in that, the drilling tool dynamic attitude measurement system based on multi-sensor data fusion comprises drilling tool, three-axis accelerometer, three-axis fluxgate, angular rate Gyroscope and filter; the three-axis accelerometer, three-axis fluxgate, angular rate gyroscope and filter are all installed on the drilling tool, and the three-axis accelerometer, three-axis fluxgate and angular rate gyroscope are respectively connected to their corresponding The measurement method of the drilling tool dynamic attitude measurement system based on multi-sensor data fusion includes the following steps: 步骤一：在姿态测量系统中建立理想正交的地理坐标系，根据欧拉定理，井下钻进过程中，钻具在空间的任一姿态可以用相对于地理坐标系的一系列旋转来表示，旋转的角度为井斜角、方位角和工具面角；根据四元数的定义和欧拉定理，把三维空间和四维空间联系起来，用四维空间的四元数性质和运算规则研究三维空间中的刚体定点转动问题；Step 1: Establish an ideal orthogonal geographic coordinate system in the attitude measurement system. According to Euler's theorem, during the downhole drilling process, any attitude of the drilling tool in space can be represented by a series of rotations relative to the geographic coordinate system. The angles of rotation are inclination angle, azimuth angle and tool face angle; according to the definition of quaternion and Euler's theorem, the three-dimensional space and the four-dimensional space are connected, and the quaternion properties and operation rules of the four-dimensional space are used to study the three-dimensional space. The rigid body fixed point rotation problem; 步骤二：针对钻具安装三轴加速度计、三轴磁通门和角速率陀螺仪，实现导向钻井工具姿态组合测量，联合建立多传感器、动态测量系统的非线性数学模型，得到非线性状态方程和量测方程；Step 2: Install a three-axis accelerometer, a three-axis fluxgate and an angular rate gyroscope for the drilling tool to realize combined measurement of the attitude of the steerable drilling tool, jointly establish a nonlinear mathematical model of a multi-sensor and dynamic measurement system, and obtain a nonlinear state equation and the measurement equation; 步骤三：根据近钻头振动信号特性，判断钻具运动状态，分析钻具运动状态与振动加速度之间的关系以及钻具振动的主要干扰因素；根据模型及噪声特性，分别采用局部滤波器，利用无迹卡尔曼滤波算法对干扰信号进行滤除，消除近钻头强振动对姿态参数测量的影响，采用矩阵加权数据融合理论进行全局估计，进而得到最优姿态估计；Step 3: According to the characteristics of the near-bit vibration signal, determine the motion state of the drilling tool, analyze the relationship between the motion state of the drilling tool and the vibration acceleration, and the main interference factors of the drilling tool vibration; The unscented Kalman filter algorithm filters out the interference signal and eliminates the influence of strong vibration near the drill bit on the attitude parameter measurement. The matrix weighted data fusion theory is used for global estimation, and then the optimal attitude estimation is obtained; 步骤四：利用最优姿态估计，将滤波后的传感器参数进行姿态动态解算，从而得到滤波后的导向钻井工具精确的姿态参数；Step 4: Use the optimal attitude estimation to dynamically calculate the attitude of the filtered sensor parameters, so as to obtain the precise attitude parameters of the filtered steerable drilling tool; 步骤三中局部滤波消除近钻头强振动对动态姿态测量的影响包括以下步骤：In step 3, the local filtering to eliminate the influence of near-bit strong vibration on dynamic attitude measurement includes the following steps: 步骤1：对基于四元数的状态方程和量测方程进行离散化；Step 1: Discretize the quaternion-based state equation and measurement equation; 步骤2：在第一层中，三轴加速度信号、三轴磁通门信号和角速率陀螺信号分别通过三个局部滤波器，分别为第一局部滤波器、第二局部滤波器和第三局部滤波器，以并行的方式获得其局部最优状态估计值
Figure FDA0002786453000000011
及误差协方差阵
Figure FDA0002786453000000012
Step 2: In the first layer, the three-axis acceleration signal, the three-axis fluxgate signal and the angular rate gyro signal pass through three local filters, respectively the first local filter, the second local filter and the third local filter filters to obtain their locally optimal state estimates in parallel
Figure FDA0002786453000000011
and the error covariance matrix
Figure FDA0002786453000000012
 步骤3：在第二层中，应用矩阵加权数据融合算法对得到的局部状态估计值进行融合，获得系统状态的全局最优估计；假设第一局部滤波器和第二局部滤波器得到的局部最优状态估计值为
Figure FDA0002786453000000013
与
Figure FDA0002786453000000014
在线性最小方差准则下，系统状态的全局最优状态估计为
Figure FDA0002786453000000021
此时，
Figure FDA0002786453000000022
的误差协方差阵小于等于
Figure FDA0002786453000000023
和
Figure FDA0002786453000000024
的误差协方差阵，即就是
Figure FDA0002786453000000025
Step 3: In the second layer, apply the matrix weighted data fusion algorithm to fuse the obtained local state estimates to obtain the global optimal estimate of the system state; it is assumed that the local optimal values obtained by the first local filter and the second local filter are The optimal state estimate is
Figure FDA0002786453000000013
and
Figure FDA0002786453000000014
Under the linear minimum variance criterion, the global optimal state of the system state is estimated as
Figure FDA0002786453000000021
at this time,
Figure FDA0002786453000000022
The error covariance matrix of is less than or equal to
Figure FDA0002786453000000023
and
Figure FDA0002786453000000024
The error covariance matrix of , that is,
Figure FDA0002786453000000025
 系统状态的全局最优状态估计为
Figure FDA0002786453000000026
The global optimal state of the system state is estimated as
Figure FDA0002786453000000026
Figure FDA0002786453000000027
Figure FDA0002786453000000027
 局部最优状态估计值
Figure FDA0002786453000000028
和
Figure FDA0002786453000000029
间的互协方差矩阵
Figure FDA00027864530000000210
具有以下递推形式Local optimal state estimate
Figure FDA0002786453000000028
and
Figure FDA0002786453000000029
cross-covariance matrix between
Figure FDA00027864530000000210
has the following recursive form
Figure FDA00027864530000000211
Figure FDA00027864530000000211
 步骤4：根据融合局部状态估值，进而求取强振动旋转钻具系统全局最优状态估计的方法；设N个局部滤波器得到的状态估值分别为
Figure FDA00027864530000000212
对应的误差协方差矩阵分别为
Figure FDA00027864530000000213
Figure FDA00027864530000000214
和
Figure FDA00027864530000000215
间的互协方差矩阵为
Figure FDA00027864530000000216
记
Figure FDA00027864530000000217
Figure FDA00027864530000000218
基于矩阵加权多传感器系统状态全局最优估计为Step 4: According to the fusion of the local state estimates, the method of obtaining the global optimal state estimation of the strong vibration rotary drilling tool system is obtained; the state estimates obtained by the N local filters are respectively:
Figure FDA00027864530000000212
The corresponding error covariance matrices are
Figure FDA00027864530000000213
Figure FDA00027864530000000214
and
Figure FDA00027864530000000215
The cross-covariance matrix between is
Figure FDA00027864530000000216
remember
Figure FDA00027864530000000217
Figure FDA00027864530000000218
The global optimal estimation of the state of a multi-sensor system based on matrix weighting is
Figure FDA00027864530000000219
Figure FDA00027864530000000219
 其中，wi(i＝1,2,...,N)为最优权值矩阵，可通过下式计算Among them, w i (i=1,2,...,N) is the optimal weight matrix, which can be calculated by the following formula
Figure FDA00027864530000000220
Figure FDA00027864530000000220
 2.根据权利要求1所述的基于多传感器数据融合的钻具姿态测量系统的测量方法，其特征在于，姿态参数动态提取，在第三层中，根据地理坐标系到钻具坐标系进行坐标转换后，将得到的矩阵加权多传感器系统状态全局最优估计进行钻具姿态解算；可得井斜角θ和工具面角φ：2. The measurement method of the drilling tool attitude measurement system based on multi-sensor data fusion according to claim 1, is characterized in that, the attitude parameter is dynamically extracted, and in the third layer, coordinates are carried out according to the geographic coordinate system to the drilling tool coordinate system After conversion, the obtained global optimal estimation of the state of the matrix-weighted multi-sensor system is used to calculate the attitude of the drilling tool; the well inclination angle θ and the tool face angle φ can be obtained:
Figure FDA00027864530000000221
Figure FDA00027864530000000221
 根据式(5)，将滤波后得到的全局最优估计值通过钻具姿态解算，得到导向钻井工具动态姿态参数。According to equation (5), the global optimal estimated value obtained after filtering is calculated by the attitude of the drilling tool, and the dynamic attitude parameters of the steerable drilling tool are obtained. 3.根据权利要求1所述的基于多传感器数据融合的钻具姿态测量系统的测量方法，其特征在于，所述地理坐标系为东北天坐标系，其旋转正方向由右手定则决定。3 . The method for measuring a drilling tool attitude measurement system based on multi-sensor data fusion according to claim 1 , wherein the geographic coordinate system is a northeast celestial coordinate system, and the positive rotation direction thereof is determined by the right-hand rule. 4 .
CN201810056220.4A 2018-01-20 2018-01-20 Measurement method of drilling tool attitude measurement system based on multi-sensor data fusion Active CN108387205B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810056220.4A CN108387205B (en) 2018-01-20 2018-01-20 Measurement method of drilling tool attitude measurement system based on multi-sensor data fusion

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810056220.4A CN108387205B (en) 2018-01-20 2018-01-20 Measurement method of drilling tool attitude measurement system based on multi-sensor data fusion

Publications (2)

Publication Number Publication Date
CN108387205A CN108387205A (en) 2018-08-10
CN108387205B true CN108387205B (en) 2021-01-01

Family

ID=63077053

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810056220.4A Active CN108387205B (en) 2018-01-20 2018-01-20 Measurement method of drilling tool attitude measurement system based on multi-sensor data fusion

Country Status (1)

Country Link
CN (1) CN108387205B (en)

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110308300B (en) * 2019-06-27 2021-09-21 厦门盈趣科技股份有限公司 Rotating speed measuring method and device fusing multiple characteristic data
CN110440746A (en) * 2019-08-05 2019-11-12 桂林电子科技大学 A kind of no-dig technique subterranean drill bit posture fusion method based on the decline of quaternary number gradient
CN112302536B (en) * 2020-10-16 2023-03-24 安徽中勘钻探工程有限公司 Intelligent directional drilling system and directional drilling method thereof
CN112963093B (en) * 2021-01-26 2023-04-18 长江大学 Attitude dynamic measurement and calculation method of rotary steering drilling tool
CN113153270A (en) * 2021-04-27 2021-07-23 西南石油大学 Measurement-while-drilling method for near-bit dynamic well inclination angle and tool face angle
CN113255577B (en) * 2021-06-18 2021-12-14 中铁大桥科学研究院有限公司 Active control intelligent data processing method for construction vibration parameters of cable-stayed bridge
CN113464050B (en) * 2021-06-24 2023-08-08 成都理工大学 Gas drilling method and robot system for intelligent mine
CN117514146B (en) * 2024-01-04 2024-03-22 陕西太合智能钻探有限公司 Logging system and logging method

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101187567A (en) * 2007-12-18 2008-05-28 哈尔滨工程大学 Determination of Initial Attitude of Fiber Optic Gyro Strapdown Inertial Navigation System Based on Doppler
CN101982732A (en) * 2010-09-14 2011-03-02 北京航空航天大学 Micro-satellite attitude determination method based on ESOQPF (estimar of quaternion particle filter ) and UKF (unscented kalman filter) master-slave filtering
EP2904353A1 (en) * 2012-10-01 2015-08-12 SNECMA Services Multi-sensor measuring system method and system
CN105136145A (en) * 2015-08-11 2015-12-09 哈尔滨工业大学 Kalman filtering based quadrotor unmanned aerial vehicle attitude data fusion method
CN105607106A (en) * 2015-12-18 2016-05-25 重庆邮电大学 Low-cost high-precision BD/MEMS integration attitude measurement method
CN107192387A (en) * 2017-05-23 2017-09-22 北京理工大学 A kind of combined positioning method based on Unscented kalman filtering
CN107515001A (en) * 2017-09-05 2017-12-26 中国石油大学(华东) Method and device for dynamic measurement of gravity tool face angle of rotary steerable platform

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101187567A (en) * 2007-12-18 2008-05-28 哈尔滨工程大学 Determination of Initial Attitude of Fiber Optic Gyro Strapdown Inertial Navigation System Based on Doppler
CN101982732A (en) * 2010-09-14 2011-03-02 北京航空航天大学 Micro-satellite attitude determination method based on ESOQPF (estimar of quaternion particle filter ) and UKF (unscented kalman filter) master-slave filtering
EP2904353A1 (en) * 2012-10-01 2015-08-12 SNECMA Services Multi-sensor measuring system method and system
CN105136145A (en) * 2015-08-11 2015-12-09 哈尔滨工业大学 Kalman filtering based quadrotor unmanned aerial vehicle attitude data fusion method
CN105607106A (en) * 2015-12-18 2016-05-25 重庆邮电大学 Low-cost high-precision BD/MEMS integration attitude measurement method
CN107192387A (en) * 2017-05-23 2017-09-22 北京理工大学 A kind of combined positioning method based on Unscented kalman filtering
CN107515001A (en) * 2017-09-05 2017-12-26 中国石油大学(华东) Method and device for dynamic measurement of gravity tool face angle of rotary steerable platform

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
MAVs多源信息融合无迹姿态估计方法;吴中红 等;《第四届中国指挥控制大会论文集》;20160704;第390-394页 *
基于Kalman滤波方法的多传感器信息融合滤波器;梁佐江;《中国优秀硕士学位论文全文数据库信息科技辑》;20051215(第8期);第I140-59页 *
矿用随钻轨迹测量系统的研究;梁晓军;《中国优秀硕士学位论文全文数据库工程科技I辑》;20160415(第4期);第B021-7页 *
随钻姿态传感器刻度系统研究;胡毅;《中国优秀硕士学位论文全文数据库基础科学辑》;20130315(第3期);全文 *
面向煤矿井下探测的多节履带式机器人及其关键技术研究;韩震峰;《中国优秀博士学位论文全文数据库信息科技辑》;20140115(第1期);全文 *

Also Published As

Publication number Publication date
CN108387205A (en) 2018-08-10

Similar Documents

Publication Publication Date Title
CN108387205B (en) Measurement method of drilling tool attitude measurement system based on multi-sensor data fusion
US10584575B2 (en) Utilization of dynamic downhole surveying measurements
CN102536207B (en) Gyro inclinometer attitude measurement solving method applicable to measurement of low well deviation angle
CN106246168B (en) A near-bit drilling tool attitude measurement device and measurement method while drilling
US9273547B2 (en) Dynamic borehole azimuth measurements
CN106907142B (en) A kind of nearly bit orientation dynamic measurement device and measurement method
CN110792430B (en) A method and device for measuring inclination while drilling based on multi-sensor data fusion
CN206158732U (en) Nearly drill bit drilling tool gesture is along with boring measuring device
GB2383448A (en) Method for estimating a position in a wellbore
CN107228664A (en) Mining gyrolevel SINS attitude algorithm and zero speed correcting method
CN113671263B (en) Method and system for detecting downhole magnetic interference for measurement while drilling operations
US20160003028A1 (en) Automatic Wellbore Survey Evaluation
Jurkov et al. Experimental feasibility of the in-drilling alignment method for inertial navigation in measurement-while-drilling
CN116427909B (en) Well deviation azimuth measuring method based on vertical drilling system
US11002131B2 (en) Directional control of wellbore trajectories
Gao et al. Random weighting adaptive estimation of model errors on attitude measurement for rotary steerable system
Yang et al. Research on drilling bit positioning strategy based on SINS MWD system
US11549362B2 (en) Azimuth determination while rotating
NO20220931A1 (en) System and method for using a magnetometer in a gyro-while-drilling survey tool
US11573139B2 (en) Estimation of downhole torque based on directional measurements
Yang et al. Research on dynamic measurement method of drilling tool attitude near bit based on suppression of heavy-tailed measurement noise
CN105507884A (en) Downhole multi-sensor measuring system and method
Liu et al. Intelligent wellbore path estimation using multiple integrated MEMS sensors
Liu et al. Intelligent filter for accurate subsurface heading estimation using multiple integrated mems sensors
Xue et al. Dynamic Measurement of Spatial Attitude at the Bottom Rotating Drillstring

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant