Numerical simulation of a new early gas kick detection method using UKF estimation and GLRT.

Abstract A gas kick may occur when drilling with narrow pressure margin, which can lead to significant non-productive time. This paper proposes an early gas kick detection method applicable to water-based mud (WBM), which integrates a transient pressure and temperature coupling model into an unscented Kalman filter (UKF) algorithm. Three pressure factors and a flow rate factor are estimated with the UKF algorithm using updated measurement data in a detection estimator, and a generalized likelihood ratio test (GLRT) is employed to automatically detect changes in the pressure factors and flow rate factor for prediction of the gas kick. Simulated results show that the estimated pressures and outlet flow rate trace synthetic measurements very well with continuous inversion of the pressure factors and flow rate factor. All of the estimated pressure factors and flow rate factor fluctuate to a little extent around a base value under normal drilling condition, while the pressure factor in annulus and flow rate factor both deviate from the base value when the gas kick occurs. Performances of the proposed method, pit gain monitoring method and delta flow monitoring method are contrasted. The kick detection times are gradually reduced for all the methods with the increase of gas kick rate. Moreover, the proposed method herein shows a much better performance than the pit gain and delta flow monitoring methods, especially at small gas kick rate. Highlights • A new early gas kick detection method is proposed. • Pressure factors and flow rate factor are estimated by unscented Kalman filter. • Temperature effect is considered in the detection method. • Superior performance of the gas kick detection method has been proved. [ABSTRACT FROM AUTHOR]