Motion Aided Inertial Navigation System Calibration for In-Drilling Alignment

Date
2022-01
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Abstract
Azimuth survey accuracy is fundamental to directional drilling operations. Industry standard magnetic surveys are limited by interference, and gyroscopic surveys are time intensive or lose accuracy over time due to measurement drift. Alternative solutions are constantly sought. Inertial navigation system (INS) based technologies are not susceptible to external interference, however measurement errors accumulate leading to uncertainty about the true wellbore trajectory to grow exponentially over time. Periodic calibration methods such as zero-velocity update (ZUPT) reduce the rate of error accumulation in INS but with limited success due to a static error model. This work presents a dynamic INS calibration method for measurement-while-drilling (MWD) known as in-drilling alignment (IDA). This method expands on motion aided INS calibration techniques and makes use of controlled motion while the bottom-hole assembly (BHA) is stationary. During this time, linear and rotary motions are induced on the inertial measurement unit (IMU) by electrical actuators. The induced motion is precisely measured by independent sensors. The measured motions and IMU samples become the input to a two-stage inertial navigation system (INS). First, the coarse alignment stage uses equations of motion and the sensor measurements to update the INS states. Next, the extended Kalman filter (EKF) based fine alignment stage takes the measured actuator motion and coarse alignment results to predict the measurement error states in the INS. This work addresses the limitations in industry standard azimuth survey. A method is presented for overcoming these limitations using IDA. The coarse and fine alignment INS stages are presented including a derivation of a novel error model for the EKF. The behavior of the system is investigated using experimental results from a laboratory scale device.
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Keywords
inertial navigation, extended kalman filter, directional drilling, measurement while drilling, MWD
Citation
Ursenbach, N. K. (2022). Motion aided inertial navigation system calibration for in-drilling alignment (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.