• Journal of Korean Port Research
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• v.13 no.2
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• pp.427-436
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• 1999

Simulation model for diffusion of oil spill is developed. The model can perform real time simulation in the case of oil spill accident in the ocean. The model consists of three dimensional ocean circulation model and model for diffusion of oil spill. Real time flow fields which are used in the calculation of advection of oil spill are obtained in the three dimensional ocean circulation model. The model for diffusion of oil spill includes the evaporation dissolution emulsification and downward diffusion. For the verification of the model it is applied to the oil spill from the accident of Sea Prince. The results shows good agreement.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.105-118
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• 2008

There are many debates on the topic of the relationship between oil prices and economic growth. Through the repeated processes of conformations and contractions on the subject, two main issues are developed; one is how to define and drive oil shocks from oil prices, and the other is how to specify an econometric model to reflect the asymmetric relations between oil prices and output growth. The study, thus, introduces the unobserved component model to pick up the oil shocks and a first-order Markov switching model to reflect the asymmetric features. We finally employ unique oil shock variables from the stochastic trend components of oil prices and adapt four lags of the mean growth Markov Switching model. The results indicate that oil shocks exert more impact to recessionary state than expansionary state and the supply-side oil shocks are more persistent and significant than the demand-side shocks.

• Journal of Ocean Engineering and Technology
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• v.19 no.4 s.65
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• pp.35-41
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• 2005

There has been increasing offshore oil exploration, drilling, and production activities, as well as a huge amount of petroleum being transported by tankers and pipelines through the ocean and costal environment. Assessment must be made of the potential risk of damage resulting from the exploration, development and transportation activities. This is achieved through predictive impact evaluations of the fate of hypothetical or real oil spills. VVhen an oil spill occurs, planning and execution of cleanup measures also require the capability to forecast the short-term and long-term behavior of the spilled oil. A great amount of effort has been spent by government agencies, oil industries, and researchers over the past decade to develop more realistic models for oil spills. Numerous oil spill models have been developed and applied, most of which attempt to predict the oil spill fate and behavior. For an actual contingency planning, the oil fate and behavior model should be combined with an oil spill incident model, an environmental impact and risk model and a contingency planning model. The purpose of this review study is to give an overview of existing oil spill models that deal with the physical, chemical, biological, and socia-economical aspects of the incident, fate, and environmental impact of oil spills. After reviewing the existing models, future research needs are suggested. In the study, available oil spill models are separated into oil spill incident, oil spill fate and behavior, environmental impact and risk, and contingency planning models. The processes of the oil spill fate and behavior are reviewed in detail and the characteristics of existing oil spill fate and behavior models are examined and classified so that an ideal model may be identified. Finally, future research needs are discussed.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.435-437
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• 2003

This study presents work to utilize RADARSAT SAR image for forecast oil slick trajectory movement. The fractal dimension algorithm used to detect oil slick. The Doppler frequency shift and quasi-linear model was used to simulate a current pattern from RADARSAT image. The Fay’s algorithm of oil slick spreading was developed based on a Doppler frequency shift model. Thus, the study shows that fractal dimension algorithm discriminated the oil slick from the surrounding water features. The quasi-linear model shows that the current pattern can be simulated from single RADARSAT image. The oil slick trajectory model shows that after 48 hrs, the oil slick parcels deposited along the coastal waters.

• Journal of the Korean Society of Marine Environment & Safety
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• v.5 no.1
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• pp.9-18
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• 1999

To predict the oil spill dispersion phenomena in the ocean, the oil spill response model, which can be used for strategic purpose on the oil spill site, based on Lagrangian particle-tracking method was formulated and applied to the neighboring area with Pusan port where the oil spill incident occurred when the tanker ship No.1 Youil struck on a small rock near the Namhyungjeto on September 21, 1995. The real-time tidal currents to be required as input data of the oil spill model were obtained by the two-dimensional hydrodynamic model and the tide prediction model. Evaluation of tidal currents using observation data was successful. For wind data, other input data of oil spill model, observed data on the spot were used. To verify the oil spill model, the oil spill modelling results were compared with the field data obtained from the spill site. Compared the modelling results with the observation data, there exist some discrepancies but the general pattern of modelling results was similar to that of field observation. The modelling results on 7 days after spill occurred showed that the 40% of spilled oil is in floating, 36% in evaporated, 23% at shore, and 1% in out of boundary, respectively. According to the evaluation of weighting curves of effective components to the dispersion of oil, the winds make a 37% of contribution to the dispersion of oil, turbulent diffusion 39.5%, and tidal currents 23.5%, respectively. Provided the more accurate wind data are supported, more favorable results might be obtained.

• Geosystem Engineering
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• v.21 no.6
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• pp.335-343
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• 2018

Alkali-surfactant polymer flooding has become an important technique to improve oil recovery following the development of oil fields while the function of emulsification in enhanced oil recovery is rarely considered in the existing mathematical model for numerical simulation. In this paper, the mechanism of improving the recovery of the emulsification was analyzed in ASP flooding, and a relatively perfect mathematical model with deep filtration-theory was established, in which oil-water volume equation, saturation equation, viscosity equation, and permeability reduction equation are included. The new model is used to simulate the actual block of an oil field; the simulated results of the new model and an old model without considering the emulsification are compared with the actual well history. It is found that new model which is easy to be realized in numerical simulation has a high precision fitting, and the effect of adding oil and decreasing water is obvious. The sensitivity of emulsification was analyzed, and the results show that the water reducing funnel becomes wider and the rate of water cut decreases rapidly with the increase of emulsifying capacity, and then the rate of recovery slows down. The effect of increasing oil and decreasing water is better, and the degree of recovery increases. The emulsification of the ASP flooding is maintained at a moderate level, which corresponds to ${\Phi}=0.2$ in the new model, and the emulsification is applied to realize the general mathematical quantitative description, so as to better guide the oilfield development.

• Korea Trade Review
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• v.44 no.1
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• pp.75-86
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• 2019

This study performs a factor analysis that affects the bunker oil price using the Co-integration model and Vector Error Correction Model (VECM). For this purpose, we use data from Clarkson and the analysis results show 17.6% decrease in bunker oil price when the amount of crude oil production increases at 1.0%, 10.3% increase in bunker oil price when the seaborne trade volume increases at 1.0%, 1.0% decrease in bunker oil price when total volume of vessels increases at 1.0%, and 0.003% increase in bunker oil price when 1.0% increase in world GDP, respectively. This study is meaningful in that this study estimates the speed of convergence to long-term equilibrium and identifies the price adjust mechanism which naturally exists in bunker oil market. And it is expected that the future study can provide statistically more meaningful econometric results if it can obtain data during more long-periods and use more various kinds of explanatory variables.

• Journal of Ocean Engineering and Technology
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• v.32 no.6
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• pp.474-484
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• 2018

In this study, a new numerical modeling system was proposed to predict oil spills, which increasingly occur at sea as a result of abnormal weather conditions such as global warming. The hydrodynamic conditions such as the flow velocity needed to calculate oil dispersion were estimated using a three dimensional hydrodynamic model based on the Navier-Stokes equation, which considered all of the physical variations in the vertical direction. This improved the accuracy compared to those estimated by the conventional shallow water equation. The advection-diffusion model for the spilled oil was combined with the hydrodynamic model to predict the movement and fate of the oil. The effects of absorption, weathering, and wind were also considered in the calculation process. The combined model developed in this study was then applied to various test cases to identify the characteristics of oil dispersion over time. It is expected that the developed model will help to establish initial response and disaster prevention plans in the event of a nearshore oil spill.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.12-17
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• 2010

The oil tanker ship over 150GRT must equip oil content meter which satisfy requirements of revised MARPOL 73/78. Online measurement of oil content in complex samples is required to have fast response, continuous measurement, and satisfaction of ${\pm}10ppm$ or ${\pm}10%$ error in this field. The research of this paper is to develop oil content measurement system using analysis of light transmission and scattering among turbidity measurement methods. Light transmission and scattering are analytical methods commonly used in instrumentation for online turbidity measurement of oil in water. Gasoline is experimented as a sample and the oil content approximately ranged from 14ppm to 600ppm. TSK Fuzzy Model may be suitable to associate variously derived spectral signals with specific content of oil having various interfering factors. Proposed Parallel TSK Fuzzy Model is reasonably used to classify oil content in comparison with other models. Those measurement methods would be effectively applied and commercialized to oil content meter that is key components of oil discharge monitoring control equipment.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.63-71
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• 2020

In this paper, we propose the new time-varying coefficient GARCH-in-Mean model. The benefit of our model is to allow the risk-return parameter in the mean equation to vary over time. At the end of 2019 to the beginning of 2020, the world witnessed two shocking events: COVID-19 pandemic and 2020 oil price war. So, we decide to use the daily data from December 2, 2019 to May 29, 2020, which cover these two major events. The purpose of this study is to find the dynamic movement between risk and return in four major oil markets: Brent, West Texas Intermediate, Dubai, and Singapore Exchange, during COVID-19 pandemic and 2020 oil price war. For the European oil market, our model found a significant and positive risk-return relationship in Brent during March 26-April 21, 2020. For the North America oil market, our model found a significant positive risk return relationship in West Texas Intermediate (WTI) during March 12-May 8, 2020. For the Middle East oil market, we found a significant and positive risk-return relationship in Dubai during March 12-April 14, 2020. Lastly, for the South East Asia oil market, we found a significant positive risk return relationship in Singapore Exchange (SGX) from March 9-May 29, 2020.