The elimination of severe slugging—experiments and modeling

Jansen, Fieke; Shoham, Ovadia; Taitel, Yehuda

doi:10.1016/0301-9322(96)00027-4

Cited by 113 publications

(59 citation statements)

References 6 publications

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“…Early studies [15], [16] showed that reducing the opening of the production choke could stabilize the flow, thus eliminating slugging. Storkaas [6] identified this behavior as a Hopf bifurcation: as one reduces the choke opening, the unstable poles of the system cross the imaginary axis and become stable.…”

Section: A Slug Flowmentioning

confidence: 99%

Model-based control of slugging flow: An experimental case study

Meglio

Kaasa

Petit

et al. 2010

Proceedings of the 2010 American Control Conference

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Model-based control of slugging flow: an experimental case study Florent Di Meglio, Glenn-Ole Kaasa, Nicolas Petit, Vidar Alstad Abstract-In this paper, we compare two solutions for suppressing slug flow in pipes conveying a diphasic fluid by active feedback control of the outlet (production) choke. Conventionnaly, a non-collocated PI controller is used to stabilize the measured inlet pressure. Unfortunately, this method lacks robustness to changes in operating conditions and reveals difficult to calibrate. In this work, we propose a model-based approach to design a nonlinear state-feedback control law based on a first principles model of the slugging phenomenon. A theoretical proof of convergence of the closed-loop model is provided, as well as an experimental validation of these results on a mid-scale testbench.

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Section: A Slug Flowmentioning

confidence: 99%

Model-based control of slugging flow: An experimental case study

Meglio

Kaasa

Petit

et al. 2010

Proceedings of the 2010 American Control Conference

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“…The artificially injected gas diminishes the density of the well fluid, which, in turn, makes possible its extraction with the created difference in pressure. Stabilization techniques which tackle these oscillatory behaviors in multiphase flows are necessary and have been designed by experts in academia and industry [25,19,29,32,14,12]. These methods are usually based on the stabilization of the downhole pressure through choke actuators on the gas-lift flow rate and the well production.…”

Section: Introductionmentioning

confidence: 99%

Echo State Networks for data-driven downhole pressure estimation in gas-lift oil wells

Antonelo¹,

Camponogara²,

Foss

2017

Neural Networks

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Process measurements are of vital importance for monitoring and control of industrial plants. When we consider offshore oil production platforms, wells that require gas-lift technology to yield oil production from low pressure oil reservoirs can become unstable under some conditions. This undesirable phenomenon is usually called slugging flow, and can be identified by an oscillatory behavior of the downhole pressure measurement. Given the importance of this measurement and the unreliability of the related sensor, this work aims at designing data-driven soft-sensors for downhole pressure estimation in two contexts: one for speeding up first-principle model simulation of a vertical riser model; and another for estimating the downhole pressure using real-world data from an oil well from Petrobras based only on topside platform measurements. Both tasks are tackled by employing Echo State Networks (ESN) as an efficient technique for training Recurrent Neural Networks. We show that a single ESN is capable of robustly modeling both the slugging flow behavior and a steady state based only on a square wave input signal representing the production choke opening in the vertical riser. Besides, we compare the performance of a standard network to the performance of a multiple timescale hierarchical architecture in the second task and show that the latter architecture performs better in modeling both large irregular transients and more commonly occurring small oscillations.

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“…This flow pattern may arise in horizontal and slightly inclined pipes from stratified flow because of the growth of instabilities: small perturbations appear on the liquid surface, and then, some may grow into larger waves to fill the pipe completely due to the well-known Kelvin-Helmholtz instability [4][5][6]. Slug flow can also be established due to pipe slope changes, i.e., when the pipe inclination, initially horizontal or downward, turns upward: in this case, the liquid accumulates because of gravity, and the liquid volume fraction increases until the stratified-slug flow transition occurs [7].…”

Section: Introductionmentioning

confidence: 99%

Simplified 1D Incompressible Two-Fluid Model with Artificial Diffusion for Slug Flow Capturing in Horizontal and Nearly Horizontal Pipes

2017

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This article proposes a numerical resolution of a one-dimensional (1D), transient, simplified two-fluid model regularized with an artificial diffusion term for modeling stratified, wavy and slug flow in horizontal and nearly horizontal pipes. Artificial diffusion is introduced to prevent the unbounded growth of instabilities where the 1D two-fluid model is ill-posed. We propose a method to set the artificial diffusion case by case to obtain the desired cut-off at short wavelengths by combining the choice of the spatial discretisation and the amplification factors obtained by the linear stability analysis of the model. A proper criterion to simulate two-phase to single-phase flow transition, which occurs during slug formation, is also developed. Flow pattern transitions have been numerically computed and compared against theoretical transition boundaries and experimental observations. Moreover, we showed that the developed code computes slug initiation and slug characteristics, in a reasonably accurate way considering the simplicity of the model, comparing numerical results with well-known empirical correlations and experimental data. Furthermore, the model simplicity leads to a computationally-inexpensive numerical resolution; this can be useful in engineering applications where obtaining fast numerical results is fundamental, such as applications involving automated control for two-phase flows.

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The elimination of severe slugging—experiments and modeling

Cited by 113 publications

References 6 publications

Model-based control of slugging flow: An experimental case study

Model-based control of slugging flow: An experimental case study

Echo State Networks for data-driven downhole pressure estimation in gas-lift oil wells

Simplified 1D Incompressible Two-Fluid Model with Artificial Diffusion for Slug Flow Capturing in Horizontal and Nearly Horizontal Pipes

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