Modeling gas dissolution in deepwater oil/gas spills

Zheng, Lianyuan; Yapa, Poojitha D.

doi:10.1016/s0924-7963(01)00067-7

Cited by 87 publications

(72 citation statements)

References 15 publications

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“…The effect of gas-water interface curvature on equilibrium gas pressure is omitted in this model because when using the Thomson (Kelvin) formula it turns out to be negligible for typical bubble radii in oceans and lakes (≥ 1 mm). The exchange coefficient, K i , is dependent on molecular diffusivity in water, bubble radius and its velocity according to empirical formulae from Zheng and Yapa (2002). The bubble velocity is determined assuming equilibrium between buoyancy force and environment resistance given by the quadratic law for small radii (r b < 1.3 mm) and taking into account the bubble surface oscillations for larger sizes (Jamialahmadi et al, 1994).…”

Section: Single Bubble Modelmentioning

confidence: 99%

LAKE 2.0: a model for temperature, methane, carbon dioxide and oxygen dynamics in lakes

et al. 2016

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Abstract. A one-dimensional (1-D) model for an enclosed basin (lake) is presented, which reproduces temperature, horizontal velocities, oxygen, carbon dioxide and methane in the basin. All prognostic variables are treated in a unified manner via a generic 1-D transport equation for horizontally averaged property. A water body interacts with underlying sediments. These sediments are represented by a set of vertical columns with heat, moisture and CH 4 transport inside. The model is validated vs. a comprehensive observational data set gathered at Kuivajärvi Lake (southern Finland), demonstrating a fair agreement. The value of a key calibration constant, regulating the magnitude of methane production in sediments, corresponded well to that obtained from another two lakes. We demonstrated via surface seiche parameterization that the near-bottom turbulence induced by surface seiches is likely to significantly affect CH 4 accumulation there. Furthermore, our results suggest that a gas transfer through thermocline under intense internal seiche motions is a bottleneck in quantifying greenhouse gas dynamics in dimictic lakes, which calls for further research.

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Section: Single Bubble Modelmentioning

confidence: 99%

LAKE 2.0: a model for temperature, methane, carbon dioxide and oxygen dynamics in lakes

et al. 2016

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“…In this study the evolution of the oil/gas plumes through the water column was estimated based on the theory proposed by Chen and Yapa (2004), Fannelop and Sjoen (1980), Friedl and Fanneløp (2000), Yapa et al, (2001), Zheng and Yapa (1998), Zheng and Yapa (2000) and Zheng and Yapa (2002). These studies were used for the elaboration of computational routines that represent the simultaneous transport of oil and natural gas.…”

Section: The Gas_docean Modelmentioning

confidence: 99%

“…In deeper waters, for instance, the gas cannot be treated as an ideal mixture , and new interaction processes among the two means gas and liquid was observed, mainly when the local pressure is very different to the atmospheric pressure. In this new generation of mathematical models, created to represent simultaneously oil and gas plumes in marine environment, two more important physiochemical processes were considered, formation of gas hydrate Topham, 1984) and gas dissolution (Johansen, Varona et al Zheng and Yapa, 2002) in seawater. In shallow waters, the gas dissolution is neglectable (Johansen, 2000).…”

mentioning

confidence: 99%

Influence of underwater hydrodynamics on oil and gas blowouts off Amazon River Mouth

et al. 2018

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RESUMO.O estudo está focado na análise do comportamento das plumas de vazamento de óleo/gás em águas profundas, localizadas na plataforma continental do norte do Brasil. O modelo Regional Ocean Modeling System (ROMS) é utilizado para simular a dinâmica oceânica na região 60.5°-24°W/5°S-16°N com 0.25° de resolução, 32 níveis verticais e considerando as descargas dos rios Amazonas e Pará. A saída do modelo ROMS é comparada com o conjunto de dados SODA (Simple Ocean Data Assimilation). ABSTRACT. This study is focused on analyzing the behavior of oil/gas plumes from blowouts into deepwater, located at the northern Brazil continental shelf. The Regional Ocean Modeling System (ROMS) model is used to simulate ocean dynamics in the region 60.5°-24.0°W/5°S-16°N with 0.25° of resolution, 32 vertical levels and considering the discharges of the Amazon and Pará Rivers. The ROMS output are compared to Simple Ocean Data Assimilation (SODA) dataset. Three points were selected to make the numerical simulations, located at (50°W, 5.25°N), (44.5°W, 0.5°N) and (42.75°W, 1°S). The time step suggested by Lee and Cheung (1990) was adjusted due to the particular oceanographic conditions at each point, in which, the initial velocity tends to zero and the coefficient 0.1 of the original equation was replaced by 0.0250 and 0.0375. All the plumes behaved as type 3. The seasonal current speed was small from the bottom to the surface, usually not exceeding 0.25 ms -1 ; the maximum displacement of the plumes from its point of origin was not greater than 1 m. The mean plumes diameter on the surface ranged 54 -79.7 m and the arrival time to the surface was from 7.25 to 8.05 hours.

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“…Although self-similarity is not strictly valid for multiphase plumes, integral models based on the entrainment hypothesis have been successfully applied to predict multiphase plume dynamics (Milgram, 1983). Two major blowout simulation models are DeepBlow (Johansen, 2003) and Clarkson Deep Oil and Gas (CDOG; Zheng and Yapa, 2002). These models have been carefully validated and can predict the dissolution of gas bubbles (Zheng and Yapa, 2002), usually treating oil droplets as inert.…”

Section: Nearfield Plume Dynamicsmentioning

confidence: 99%

“…Two major blowout simulation models are DeepBlow (Johansen, 2003) and Clarkson Deep Oil and Gas (CDOG; Zheng and Yapa, 2002). These models have been carefully validated and can predict the dissolution of gas bubbles (Zheng and Yapa, 2002), usually treating oil droplets as inert. They run quickly, making them ideal for response and for exploring sensitivity to complex bubble and droplet behavior and chemistry.…”

Section: Nearfield Plume Dynamicsmentioning

confidence: 99%