This paper presents detailed measurements on gas-liquid flows in horizontal and slightly inclined pipes. The mixture velocities, liquid fractions and pipe inclinations used in the experiments are in a range that is commonly used in transportation of unprocessed gas in offshore oil and gas industry. The experimental activities were performed using the multiphase flow loop at Telemark University College, Porsgrunn, Norway. The experiments were conducted in a 15 m long, 56 mm diameter, inclinable steel pipe using Exxsol D60 oil (density 793 kg/m3 and viscosity 1.3 mPa·s), water (density 999 kg/m3 and viscosity 0.89 mPa·s) and air (density 1.22 kg/m3 and viscosity 0.018 mPa·s) as test fluids. Mixture velocities of 5, 10 and 15 m/s, liquid fractions of 0.0010, 0.0025, 0.0050, 0.0075 and 0.0100 and pipe inclinations of -5°, -1°, 0, +1° and +5° from horizontal were investigated. The time-averaged crosssectional distributions of gas and liquid phases were measured using a singlebeam gamma densitometer. The characterization of flow patterns and identification of their boundaries were performed using high-speed videos, still pictures and live observations. Seven different flow patterns were identified for gas liquid flow in horizontal and slightly inclined pipes. The pressure drop and liquid hold-up measurements were also reported.
Subsea gas releases can have catastrophic impacts on human life, offshore assets, and the environment. As a result of major accidents that occurred recently, government regulations and company policies enforce a formal assessment of risks related to subsea gas releases. The main objective of subsea gas dispersion modelling is to predict the properties such as plume width, gas volume fraction and mean velocities at the sea surface in order to provide input data for risk models quantifying the topside risk exposure on offshore installations. This requires a comprehensive understanding of the dynamics of underwater releases of natural gas. This paper presents a comparison of different drag models applied for subsea gas dispersion modelling. ANSYS Fluent is used as the Computational Fluid Dynamics (CFD) modelling framework of the subsea gas plume hydrodynamics, while the changes of bubble's density and size is included as an external user defined functions (UDFs) hooked to the Fluent's main code structure. Four different drag models are compared, namely spherical drag law, modified spherical drag law, Xia's drag law and Tomiyama's drag law. The drag models are also incorporated into the main code structure as external UDFs. A combination of the two methods-Eulerian-Eulerian and Lagrangian-is used to model the bubbling behaviour of the subsea gas dispersion. The predicted results are validated against the experimental data presented by Engebretsen back in 1997. It is observed that the drag model in the CFD simulations seems to be a factor that could affect underwater plume physics. The predicted results show that the drag models including bubble shape show better agreement than the ones without including bubble shape in general.
Oil recovery can be enhanced by maximizing the well-reservoir contact using advanced wells. The successful design of such wells requires an appropriate integrated dynamic model of the oil field, well, and production network. In this study, the model of advanced wells developed in the dynamic multiphase flow simulator OLGA® is linked to a reservoir model to develop transient fully-coupled well-reservoir models for the simulation of oil recovery through advanced wells. The obtained results from the developed models in OLGA are compared with the results from the widely used MultiSegment Well (MSW) model. Flow Control Devices (FCDs) are the key component of advanced wells and the functionality of the main types of FCDs is investigated. According to the obtained results, by employing advanced wells with an appropriate completion design, the production of unwanted fluids (water and/or gas) can be highly reduced while the oil recovery is slightly increased compared to using conventional wells. Besides, by comparing the performance of the OLGA and MSW models, it can be concluded that OLGA is a robust tool for conducting an accurate simulation of oil recovery through advanced wells. However, running such simulations with OLGA is relatively slow and may face convergence problems.
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