Data Assimilation-Based Method for Wellbore Flow State Inversion and Safety Intervention Timing Prediction in Managed Pressure Drilling

In managed pressure drilling (MPD), wellbore flow states cannot be obtained in real time, so kick intervention decisions rely on the empirical judgment of engineers, which introduces a significant lag. The central hypothesis of this study is that fusing a physics-constrained transient two-phase flow model with real-time surface measurements through data assimilation can reconstruct the unobservable downhole flow state and, on this basis, enable quantitative and earlier prediction of the safe intervention timing than empirical judgment alone. To this end, this paper proposes a method for real-time inversion of wellbore flow states and safety intervention timing prediction based on the Ensemble Kalman Filter (EnKF). Using a transient wellbore gas–liquid two-phase flow model as the EnKF model operator, the method continuously assimilates real-time casing pressure, standpipe pressure (SPP), and pit gain data. This process dynamically corrects model prediction bias while maintaining multiphase flow physical constraints. Thus, the method achieves high-precision dynamic inversion of wellbore pressure profiles and gas holdup distributions. On this basis, the authors use the inverted states as initial conditions to calculate safety casing pressure with the multiphase flow model. The method then predicts intervention timing by combining three trigger conditions: safety casing pressure, pit gain, and the density difference between the inlet and outlet. The authors validated the method using kick scenarios from Well L and Well Z in the Shunbei block. The results showed that the mean absolute errors (MAEs) for casing pressure inversion were 0.113 MPa and 0.135 MPa, respectively. The MAEs for SPP were 1.324 MPa and 0.954 MPa. The MAEs for pit gain were 0.174 m3 and 0.114 m3. The inverted spatiotemporal distribution of gas holdup reflected the entire process of gas migration and expansion in the wellbore. Prediction results for intervention timing showed that the method issued early warning signals approximately 53 min and 29 min earlier than actual field operations. This method provides a quantitative decision-making basis with safety redundancy for MPD field operations.

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Journal
Processes
Published
2026-06-30
DOI
https://doi.org/10.3390/pr14132125
Primary Topic
Drilling and Well Engineering
Type
article
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article

Data Assimilation-Based Method for Wellbore Flow State Inversion and Safety Intervention Timing Prediction in Managed Pressure Drilling

Yi Yang, Xiuping Chen, Wei Gao, H Yang et al.
Processes
Drilling and Well Engineering
article

Data Assimilation-Based Method for Wellbore Flow State Inversion and Safety Intervention Timing Prediction in Managed Pressure Drilling

Yi Yang, Xiuping Chen, Wei Gao, H Yang, Zhenyu Long, Jun Li
article en

Abstract

In managed pressure drilling (MPD), wellbore flow states cannot be obtained in real time, so kick intervention decisions rely on the empirical judgment of engineers, which introduces a significant lag. The central hypothesis of this study is that fusing a physics-constrained transient two-phase flow model with real-time surface measurements through data assimilation can reconstruct the unobservable downhole flow state and, on this basis, enable quantitative and earlier prediction of the safe intervention timing than empirical judgment alone. To this end, this paper proposes a method for real-time inversion of wellbore flow states and safety intervention timing prediction based on the Ensemble Kalman Filter (EnKF). Using a transient wellbore gas–liquid two-phase flow model as the EnKF model operator, the method continuously assimilates real-time casing pressure, standpipe pressure (SPP), and pit gain data. This process dynamically corrects model prediction bias while maintaining multiphase flow physical constraints. Thus, the method achieves high-precision dynamic inversion of wellbore pressure profiles and gas holdup distributions. On this basis, the authors use the inverted states as initial conditions to calculate safety casing pressure with the multiphase flow model. The method then predicts intervention timing by combining three trigger conditions: safety casing pressure, pit gain, and the density difference between the inlet and outlet. The authors validated the method using kick scenarios from Well L and Well Z in the Shunbei block. The results showed that the mean absolute errors (MAEs) for casing pressure inversion were 0.113 MPa and 0.135 MPa, respectively. The MAEs for SPP were 1.324 MPa and 0.954 MPa. The MAEs for pit gain were 0.174 m3 and 0.114 m3. The inverted spatiotemporal distribution of gas holdup reflected the entire process of gas migration and expansion in the wellbore. Prediction results for intervention timing showed that the method issued early warning signals approximately 53 min and 29 min earlier than actual field operations. This method provides a quantitative decision-making basis with safety redundancy for MPD field operations.

ProcessesVol. 14(13)
Sinopec (China) (CN), China University of Petroleum, Beijing (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 9%
Drilling and Well Engineering
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