An Attitude Improvement Method of FOG-Based Measurement-While-Drilling Utilizing Backtracking Navigation Algorithm

Abstract

Directional drilling utilizes the measurement-while-drilling (MWD) to provide attitude for drilling bit. A traditional MWD system, consisting of magnetometers and accelerometers, relies on expensive and huge nonmagnetic drill collar (NMDC) to shield from magnetic interference to obtain accurate attitude angles. A fiber optic gyroscope-based MWD (FOG-based MWD) that is based on inertial navigation is an alternative survey scheme. But, random vibration environment of underground introduces high-amplitude random noise to the FOGs. Besides, the auxiliary measuring equipment [such as global position system (GPS)] will not be available in underground environments, which will bring massive attitude error under pure inertial navigation. Therefore, combined with the engineering application conditions, this article proposes a modified attitude precision improvement approach of the FOG-based MWD. First, an autoregressive moving average (ARMA) error model for FOG is established to restrain the random vibration environment interference of underground. Second, combined with the FOG error model, a continuous backtracking navigation error model is developed to improve the azimuth accuracy. Moreover, the continuous backtracking algorithm frame is designed to estimate the attitude. Finally, a semi-physical experiment and a drilling test verify that the error model has an obvious effect on reducing the amplitude of FOG random noise. The proposed backtracking algorithm make the azimuth angle achieve a high-level estimation in short time. The result of the drilling test shows that the azimuth has an improvement of 48.79%, as compared with the traditional zero velocity update (ZUPT).