A Robust Mag/INS-Based Orientation Estimation Algorithm for Measurement While Drilling
In order to obtain an optimal orientation of the bottom hole assembly while drilling, a novel robust Mag/INS-based orientation estimation algorithm, designed to support a magnetic/ inertial-based measurement while drilling (MWD) surveying system, is proposed and assessed. First, a magnetic/inertial-...
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| Vydané v: | IEEE sensors journal Ročník 17; číslo 23; s. 7971 - 7980 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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New York
IEEE
01.12.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1530-437X, 1558-1748 |
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| Abstract | In order to obtain an optimal orientation of the bottom hole assembly while drilling, a novel robust Mag/INS-based orientation estimation algorithm, designed to support a magnetic/ inertial-based measurement while drilling (MWD) surveying system, is proposed and assessed. First, a magnetic/inertial-based MWD surveying system has been designed by employing triaxial accelerometers, triaxial magnetometers, and triaxial gyroscopes. Second, in the Kalman filter framework the orientation-dependent components, i.e., the Earth's gravity field and the Earth's magnetic field, are decoupled from the vibration and magnetic disturbances respectively based on Coriolis transfer equation. Third, in the federal Kalman filter framework, the extracted gravity and magnetic field measurements are robustly fused together with angular velocity readings from the gyroscopes by employing the failure detection and inter(FDI) technique. Semi-physical simulation and actual drilling experiments show that the proposed novel robust Mag/INS-based orientation algorithm adapts well to the severe conditions of the drilling environment and can effectively improve measurement precision and reduce errors produced by drillstring vibration and magnetic disturbances. |
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| AbstractList | In order to obtain an optimal orientation of the bottom hole assembly while drilling, a novel robust Mag/INS-based orientation estimation algorithm, designed to support a magnetic/inertial-based measurement while drilling (MWD) surveying system, is proposed and assessed. First, a magnetic/inertial-based MWD surveying system has been designed by employing triaxial accelerometers, triaxial magnetometers, and triaxial gyroscopes. Second, in the Kalman filter framework the orientation-dependent components, i.e., the Earth’s gravity field and the Earth’s magnetic field, are decoupled from the vibration and magnetic disturbances respectively based on Coriolis transfer equation. Third, in the federal Kalman filter framework, the extracted gravity and magnetic field measurements are robustly fused together with angular velocity readings from the gyroscopes by employing the failure detection and inter(FDI) technique. Semi-physical simulation and actual drilling experiments show that the proposed novel robust Mag/INS-based orientation algorithm adapts well to the severe conditions of the drilling environment and can effectively improve measurement precision and reduce errors produced by drillstring vibration and magnetic disturbances. |
| Author | Jinbao Jiang Chuang Yang Jinxian Yang |
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| Cites_doi | 10.1109/TIM.2015.2479096 10.3390/mi6121467 10.1109/TIM.2007.903641 10.1109/TIM.2010.2064631 10.1109/TIM.2012.2210331 10.3390/s16030371 10.3390/s16081186 10.1109/CSO.2011.63 10.1007/978-3-642-29390-0_99 10.1109/MIM.2013.6704968 10.1109/PLANS.2006.1650582 10.1109/TIM.2007.904485 |
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| SubjectTerms | Accelerometers Algorithms Angular velocity Computer simulation Coriolis force Drilling Earth gravitation Estimation Failure detection Gravitation Gyroscopes Kalman filters magnetic and inertial measurement Magnetic disturbances Magnetic field measurement Magnetic fields Magnetic separation Magnetometers Measurement while drilling Orientation Physical simulation robust orientation estimation algorithm Robustness signal extraction of the geographical field Surveying Vibration measurement |
| Title | A Robust Mag/INS-Based Orientation Estimation Algorithm for Measurement While Drilling |
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