Modeling Underwater Oil/Gas Jets and Plumes

Yapa, Poojitha D.; Zheng, Lianyuan; Nakata, Kisaburo

doi:10.1061/(asce)0733-9429(1999)125:5(481)

Cited by 58 publications

(28 citation statements)

References 32 publications

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“…Lately, threedimensional time dependent oil spill modelling has evolved for deepwater (=> 800metre depth) marine scenarios (e.g. Yapa et al 1999, Chen and Yapa 2004, Yapa and Nakata 2004, Xie and Yapa 2006, Chen and Yapa 2007, Yapa et al 2008). …”

Section: Methods Of Oil Spill Modellingmentioning

confidence: 99%

Predicting Oil Slick Migration at a Pipeline River Crossing on the River Niger Using Hydraulic Geometry

et al. 2011

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Understanding oil slick migration in rivers is important for effective spill response because rivers provide essential services for household purposes e.g. fisheries, water supply, transport, sociocultural activities and recreation. Rivers constitute the second most important source of household water supply in Nigeria. Yet, rivers are major receptors of oil pollution. This paper focuses specifically on oil Pipeline River crossing upstream of Lokoja (on the Niger River) to demonstrate likely oil slick migration trend, herein referred to as oil travel time (OTT). An OTT describes the average time it takes lead oil plume to arrive at a downstream destination.The primary objective of this paper is to facilitate timely warning for water and environmental managers through OTT prediction; and, provide valuable information for contingency planning, monitoring and impact assessment. Method applied is the Hydraulic Geometry (HG) model using historic mean daily discharge MDQ (m 3 s -1 ) , hydraulic characteristics: width w (m), mean depth d (d), mean velocity v (m s -1 ) and 3% 'differential oil-water velocity' of wind speed (m s -1 ) at Lokoja.Results suggest that any spilled oil at the pipeline river crossing is likely to hit key receptors (e.g. water reservoir ~34km downstream) in 4 hours during high flow and takes ~9 days to reach Onitsha (~240km downstream) during low flow. This prediction is based on at-a-station HG using logarithmic regression (R 2 = 0.8447). Power regression was also used but had weaker R 2 value of 0.6175; hence the former appears more reliable. The absence of adequate data for other cross-sections downstream of the lower Niger River makes downstream HG less useful in this study. There is urgent need for more data points and systematic survey along the lower Niger to enhance downstream HG OTT prediction.This study represents the first known attempt to predict OTT in Nigerian Rivers using historic intermediate environmental data, though there have been a number of studies on marine/coastal oil spill incidents. This level of analysis is expected in every EIA where oil transport pipeline crosses rivers/streams. It is hoped that the results and the models used in this study would form useful basis for impact assessment in the ongoing efforts to explore oil at the inland river basins of Nigeria known as Nigerian Frontier Inland Sedimentary Basins (NFISB).

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Section: Methods Of Oil Spill Modellingmentioning

confidence: 99%

Predicting Oil Slick Migration at a Pipeline River Crossing on the River Niger Using Hydraulic Geometry

et al. 2011

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“…A atividade de extração petrolífera offshore apresenta aspectos de difícil equacionamento devido à complexidade do processo e o risco de acidentes envolvendo vazamentos, os quais costumam ser de grandes proporções e de difícil quantificação (YAPA et al, 1999). Os métodos existentes de contenção de vazamentos se mostram ineficientes do ponto de vista ambiental e financeiro (HENNING, 1993), uma vez que apenas contemplam a retirada do óleo da água do mar e não a sua recuperação (MIRANDA, 2011).…”

Section: Introductionunclassified

Simulação Do Escoamento Imiscível De Um Jato De Óleo Em Meio Subaquático Para O Interior De Um Reservatório De Coleta

Biehl¹,

Quadri²,

Santos³

et al. 2015

Anais Do XX Congresso Brasileiro De Engenharia Química

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RESUMO -Vazamentos de petróleo no fundo do mar, tanto em situações de explotação como de transporte provocam perdas de natureza econômica, ambiental e social. Para minimizar esses impactos, o desenvolvimento de soluções inovadoras é necessário e devem priorizar a captura do óleo antes da sua ascensão e espalhamento na superfície. Estudos experimentais e de simulação dos fenômenos envolvidos são imprescindíveis até que se possa chegar ao projeto de um equipamento de captura apto a operar em condições de campo. Foram realizadas simulações do escoamento de um jato de óleo através de um bocal de coleta para estudar o comportamento da ascensão do óleo para um dispositivo submerso que o colete e armazene sem os prejuízos do seu espalhamento na superfície Ao se testar diferentes velocidades de injeção do óleo, bem como diferentes diâmetros do bocal de coleta, foi constatada a viabilidade da operação, além de se perceber que é possível minimizar a quantidade de água arrastada pelo jato de óleo que entra no dispositivo.

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“…Once emitted from the source, a fluid undergoes a diffusion process that gives rise to a certain concentration field. One may rely on modeling techniques of the diffusion process in the presence of the underwater currents; however, doing this accurately is an extremely hard task to achieve [25] and the underlying diffusion model is very complex [12]. Furthermore one can construct an estimate of the concentration field which yields the location of the source, based on local measurements of the concentration.…”

Section: Introductionmentioning

confidence: 99%

Stochastic localization of sources using autonomous underwater vehicles

Huck

Hokayem

Chatterjee

et al. 2012

2012 American Control Conference (ACC)

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We propose a new method for locating the source(s) of a fluid that is diffusing into sea water. Our method utilizes multiple Autonomous Underwater Vehicles (AUVs) whose motion is controlled via a discrete-time Markov Chain Monte Carlo (MCMC) algorithm. The MCMC algorithm relies only on local measurements of the concentration of the fluid to construct and estimate of the concentration field over the search domain, and hence localize the source(s). We prove the existence of an invariant measure for the Markov chain that is generated by the closed-loop motion of the vehicles. The convergence rate of the Markov chain is investigated through extensive numerical simulations.

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Modeling Underwater Oil/Gas Jets and Plumes

Cited by 58 publications

References 32 publications

Predicting Oil Slick Migration at a Pipeline River Crossing on the River Niger Using Hydraulic Geometry

Predicting Oil Slick Migration at a Pipeline River Crossing on the River Niger Using Hydraulic Geometry

Simulação Do Escoamento Imiscível De Um Jato De Óleo Em Meio Subaquático Para O Interior De Um Reservatório De Coleta

Stochastic localization of sources using autonomous underwater vehicles

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