Characterization of droplet sizes in large scale oil–water flow downstream from a globe valve

Paolinelli, L.D.; Rashedi, Ahmadreza; Yao, J.

doi:10.1016/j.ijmultiphaseflow.2017.09.014

Cited by 18 publications

(14 citation statements)

References 38 publications

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“…In practical uses, the theoretical analysis must be verified by the stability of emulsion samples in field conditions. Recently, Paolinelli et al (2018) examined the correlation of water droplet size distribution with different fluid parameters (flow rate, pressure drop, oil types, and fraction of water) after a globe valve on a pipe flow loop and compared with theoretical analysis, and gave some reasonable hints for the control of water droplets in flow conditions. In this way, before the settlement of water droplets or the formation of water layer at pipeline bottom, corrosion could be totally retarded during the long-distance transportation of oil-water emulsion and a fast transportation could shorten the time from wellhead to treatment station , beneficial for reducing the corrosion risk.…”

Section: Oil-water Mixturesmentioning

confidence: 99%

Corrosion Control in CO2 Enhanced Oil Recovery From a Perspective of Multiphase Fluids

2019

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Carbon capture and storage (CCS) combined with CO 2-enhanced oil recovery (EOR), has been recently viewed as an economical and effective method for the reduction of carbon emissions. However, corrosion is a challenging issue in the whole chain process of CO 2-EOR production if water presents and mild steel pipeline is used. In this paper, the corrosion risk of pipeline at different stages of CO 2-EOR production is systematically assessed based on a detailed analysis of the fluid characteristics. According to the fluid state of CO 2 , water and crude oil, current understandings on the corrosion behavior of steel materials in multiphase flow conditions are reviewed. Furthermore, the intermittent water wetting phenomena and the fluid behavior of water droplets or clusters in an electrolyte/non-electrolyte emulsion are correlated with the steel corrosion performance, providing new insights into the corrosion phenomena. Besides application of corrosion resistant materials and corrosion inhibitors, tailoring of processing parameters, such as enhancing the water entrainment, shortening the water contact time, and reducing the solution corrosivity, is highly recommended as an effective method for corrosion control in aggressive CO 2-EOR production conditions. Based on these, some important future research topics on the corrosion in multiphase fluids are suggested.

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Section: Oil-water Mixturesmentioning

confidence: 99%

Corrosion Control in CO2 Enhanced Oil Recovery From a Perspective of Multiphase Fluids

2019

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“…This model was proposed for diluted dispersed systems. Clay's experimental tests were performed with dispersions in which the dispersed phase concentration was in the range from 0.9% to 4.8% (Paolinelli and Yao, 2017). Hinze (1955) suggests that, when dispersed phase viscosity cannot be neglected, a viscosity group can be added to the model (l Sleicher (1962) argued that the viscosity group suggested by Hinze is related to the natural frequency of vibration of droplets, and that this group is small and not relevant.…”

Section: Break Up In a Turbulent Flowmentioning

confidence: 99%

“…In order to be valid, inertial turbulent break-up models based in Hinze theory indicate that the d max obtained must be higher than the Kolmogorov length scale (k K ), defined by equation 13(where m c is the kinematic viscosity of continuous phase), and below the higher eddies that are present in the flow (k max ), equivalent to 10% of the pipe diameter (Paolinelli and Yao, 2017):…”

Section: Break Up In a Turbulent Flowmentioning

confidence: 99%

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Experimental study of water droplet break up in water in oil dispersions using an apparatus that produces localized pressure drops

Silva¹,

Medronho²,

Barca³

2019

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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Oil production facilities have choke/control valves to control production and protect downstream equipment against over pressurization. This process is responsible for droplets break up and the formation of emulsions which are difficult to treat. An experimental study of water in oil dispersion droplets break up in localized pressure drop is presented. To accomplish that, an apparatus simulating a gate valve was constructed. Droplet Size Distribution (DSD) was measured by laser light scattering. Oil physical properties were controlled and three different break up models were compared with the experimental results. All experimental maximum diameters (dmax) were above Kolmogorov length scale. The results show that dmax decreases with increase of energy dissipation rate (ε) according to the relation dmax ∝ ε−0.42. The Hinze (1955, AIChE J.1, 3, 289–295) model failed to predict the experimental results, although, it was able to adjust reasonably well those points when the original proportional constant was changed. It was observed that increasing the dispersed phase concentration increases dmax due to turbulence suppression and/or coalescence phenomenon. Turbulent viscous break up model gave fairly good prediction.

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“…The applications can be found in the field of pedestrian surveillance [1], vehicle detection in aerial images [2], cell or bacterial colony counting in medical images [3][4][5], oil droplet characterization in petroleum engineering [6] and bubble counting in bubble columns or nuclear reactors. In bubble column or nuclear reactor applications, accurate separation and reconstruction of bubble shape have equal importance to the number counting, since bubble shape contains important geometrical information for the study of mass, momentum and energy transport in these systems [6,7]. The demand for bubble shape acquisition introduces additional challenges for algorithm development and benchmarking in this field.…”

Section: Introductionmentioning

confidence: 99%

BubGAN: Bubble generative adversarial networks for synthesizing realistic bubbly flow images

Liu

2019

Chemical Engineering Science

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Bubble segmentation and size detection algorithms have been developed in recent years for their high efficiency and accuracy in measuring bubbly two-phase flows. In this work, we proposed an architecture called bubble generative adversarial networks (BubGAN) for the generation of realistic synthetic images which could be further used as training or benchmarking data for the development of advanced image processing algorithms. The BubGAN is trained initially on a labeled bubble dataset consisting of ten thousand images. By learning the distribution of these bubbles, the BubGAN can generate more realistic bubbles compared to the conventional models used in the literature. The trained BubGAN is conditioned on bubble feature parameters and has full control of bubble properties in terms of aspect ratio, rotation angle, circularity and edge ratio. A million bubble dataset is pre-generated using the trained BubGAN. One can then assemble realistic bubbly flow images using this dataset and associated image processing tool. These images contain detailed bubble information, therefore do not require additional manual labeling. This is more useful compared with the conventional GAN which generates images without labeling information. The tool could be used to provide benchmarking and training data for existing image processing algorithms and to guide the future development of bubble detecting algorithms.

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Characterization of droplet sizes in large scale oil–water flow downstream from a globe valve

Cited by 18 publications

References 38 publications

Corrosion Control in CO2 Enhanced Oil Recovery From a Perspective of Multiphase Fluids

Corrosion Control in CO2 Enhanced Oil Recovery From a Perspective of Multiphase Fluids

Experimental study of water droplet break up in water in oil dispersions using an apparatus that produces localized pressure drops

BubGAN: Bubble generative adversarial networks for synthesizing realistic bubbly flow images

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