Objective Part of oil and gas pipelines in China, which have been in operation for a long time, are facing problems such as the lack of specific geographic information and deviation of the pipeline from the designed laying location. However, traditional pipeline localization methods possess limitations of significant cumulative errors and low accuracy.

Methods To enhance the precision of oil and gas pipeline localization, a new method was proposed based on improved Unscented Kalman Filter (UKF) algorithm. The primary equipment, which is an inertial measurement unit consisting of a gyroscope and an accelerometer, supplemented by a wheel odometer and ground markers as auxiliary locator devices was utilized in this method. The attitude, velocity, and position errors of the pipeline detector were taken as state variables, and the speed of the wheel odometer and attitude information obtained from the solution of accelerometer data were taken as observables, to establish a nonlinear error propagation model of strap-down inertial navigation system. An improved UKF algorithm was employed to estimate the error transfer model for reducing the impact of noise on localization accuracy. The angular velocity and acceleration information were corrected by combining forward-backward smoothing filter method and straight and curved pipe identification method, to further reduce cumulative errors in the system solution process.

Results Numerical simulations and physical experiments revealed that the proposed oil and gas pipeline localization system has significantly reduced cumulative errors in locating long-distance pipelines. The maximum error in determining the specific location of oil and gas pipelines was found to be 0.56%. The UKF algorithm, which was proposed in this paper, showed a locating accuracy level of approximately 34.2% higher compared to the traditional Kalman Filter (KF) algorithm and 30.2% higher compared to the UKF algorithm under constant testing conditions.

Conclusion The proposed oil and gas pipeline locating method based on an improved UKF presents high practical value for long-distance pipeline localization as it has lower cumulative errors in the system solution process and higher accuracy in pipeline localization.