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Evaluation of Lyapunov-based Adaptive Observer using Low-Order Lumped Model for Estimation of Production Index in Under-balanced Drilling

机译:基于低阶集总模型的基于Lyapunov的自适应观测器评估欠平衡钻井中的生产指数

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A distributed drift-flux model and a low-order lumped model describing a multiphase (gas-liquid) flow in the well during Under-Balanced Drilling (UBD) has been presented. This paper presents a novel nonlinear adaptive observer to estimate the total mass of gas and liquid in the annulus and production constant of gas and liquid from the reservoir into the well during UBD operations. Furthermore, it describes a joint unscented Kalman filter to estimate parameters and states for both the distributed drift-flux and lumped model by using real-time measurements of the choke and the bottom-hole pressures. The performance of the adaptive observers are evaluated for typical drilling scenarios. The results show that all adaptive observers are capable of identifying the production index, although the adaptive observers based on the low-order lumped model achieves better convergence rate than adaptive observer based on the drift-flux model. The results show that the LOL model is sufficient for the purpose of estimating the production parameters.
机译:提出了一种分布式漂移通量模型和一个低阶集总模型,该模型描述了欠平衡钻井(UBD)期间井中的多相(气液)流动。本文提出了一种新颖的非线性自适应观测器,用于估算在UBD作业过程中,环空中气液的总质量以及从储层进入井中的气液的生产常数。此外,它描述了一种联合无味卡尔曼滤波器,可以通过使用节流阀和井底压力的实时测量来估计分布式漂移通量和集总模型的参数和状态。针对典型的钻井方案评估了自适应观测器的性能。结果表明,尽管基于低阶集总模型的自适应观测器比基于漂移-通量模型的自适应观测器具有更好的收敛速度,但是所有自适应观测器都能够识别生产指数。结果表明,LOL模型足以估算生产参数。

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