Control-Oriented Drift-Flux Modeling of Single and Two-Phase Flow for Drilling

Aarsnes, Ulf Jakob F.; Meglio, Florent Di; Evje, Steinar; Aamo, Ole Morten

doi:10.1115/dscc2014-6121

Cited by 26 publications

(33 citation statements)

References 27 publications

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“…The simple DFM uses a specific empirical slip law, without flow-regime predictions, but which allows for transition between single and two phase flows. The isothermal simple DFM formulation of the conservation of mass and momentum balance are given by Aarsnes et al (2014a) ∂m ∂t…”

Section: Simplified Drift-flux Modelmentioning

confidence: 99%

“…In the momentum equation (3), the term (m + n)g cos ∆θ represents the gravitational source term, g is the gravitational constant and ∆θ is the mean angle between gravity and the positive flow direction of the well, while − 2f (m+n)vm|vm| D accounts for frictional losses. The closure relations , boundary conditions and discretization schemes for this model can be found in (Aarsnes et al (2014a)). …”

Section: Simplified Drift-flux Modelmentioning

confidence: 99%

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

2015

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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.

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Section: Simplified Drift-flux Modelmentioning

confidence: 99%

Section: Simplified Drift-flux Modelmentioning

confidence: 99%

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

2015

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“…The following analysis is based on numerical results for various test cases and has proved to match the experience of field engineers. It is largely based on Aarsnes et al [2014a]. For each value set of parameters, there are at most 3 physically meaningful solutions to the steady-state equations, one of them being overbalanced.…”

Section: Analysis Of the Steady-statesmentioning

confidence: 99%

“…For more details on the physical modeling, the interested reader is referred to Aarsnes et al [2014a].…”

Section: Physical Modelingmentioning

confidence: 99%

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A distributed parameter systems view of control problems in drilling

Meglio

Aarsnes

2015

IFAC-PapersOnLine

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We give a detailed view of estimation and control problems raised by the drilling process where the distributed nature of the system cannot be ignored. In particular, we focus on the transport phenomena in Managed Pressure Drilling (MPD) and UnderBalanced Operations (UBO), as well as the time-delay mechanisms of the mechanical stick-slip vibrations. These industrial challenges raise increasingly difficult control questions for hyperbolic systems.

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Reduced basis method for managed pressure drilling based on a model with local nonlinearities

Abbasi

Iapichino

Lordejani

et al. 2020

Numerical Meth Engineering

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To circumvent restrictions of conventional drilling methods, such as slow control actions and inability to drill depleted reservoirs, a drilling method called managed pressure drilling (MPD) has been developed. In MPD, single‐phase flow processes can be modeled as a feedback interconnection of a high‐order linear system and a low‐order nonlinear system. These nonlinearities appear locally both inside and at the boundaries of the computational domain. To obtain a fast simulation platform for real‐time purposes (eg, online model‐based controller implementation), model order reduction is required for MPD. However, the local nonlinearities render applying model order reduction techniques challenging. In this study, a new approach is proposed to deal with such nonlinearities within the reduced basis (RB) context and it is successfully tested on a model for MPD. Contrary to the classical RB technique, the proposed approach not only does not generate nonphysical spikes at the locations of these local nonlinearities but also yields high speedup factors. The obtained reduced‐order model can be used for efficient online simulation and controller design for drilling systems with MPD.

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Control-Oriented Drift-Flux Modeling of Single and Two-Phase Flow for Drilling

Cited by 26 publications

References 27 publications

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

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

A distributed parameter systems view of control problems in drilling

Reduced basis method for managed pressure drilling based on a model with local nonlinearities

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