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Hyperspectral remote sensing identification of marine oil emulsions based on the fusion of spatial and spectral features

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Acta Oceanologica Sinica 2024年第3期43卷 139-154页

作者： Xinyue Huang Yi Ma Zongchen Jiang Junfang Yang School of Geography and Marine Science Nanjing UniversityNanjing 210023China First Institute of Oceanography Ministry of Natural ResourcesQingdao 266061China Marine Telemetry Technology Innovation Center Ministry of Natural ResourcesQingdao 266061China Harbin Institute of Technology Harbin 150001China China University of Petroleum(East China) Qingdao 266061China

Marine oil spill emulsions are difficult to recover,and the damage to the environment is not easy to *** use of remote sensing to accurately identify oil spill emulsions is highly important for the protection of marine ***,the spectrum of oil emulsions changes due to different water *** remote sensing and deep learning can use spectral and spatial information to identify different types of oil ***,hyperspectral data can also cause information redundancy,reducing classification accuracy and efficiency,and even overfitting in machine learning *** address these problems,an oil emulsion deep-learning identification model with spatial-spectral feature fusion is established,and feature bands that can distinguish between crude oil,seawater,water-in-oil emulsion(WO),and oil-in-water emulsion(OW)are filtered based on a standard deviation threshold–mutual information *** oil spill airborne hyperspectral data,we conducted identification experiments on oil emulsions in different background waters and under different spatial and temporal conditions,analyzed the transferability of the model,and explored the effects of feature band selection and spectral resolution on the identification of oil *** results show the following.(1)The standard deviation–mutual information feature selection method is able to effectively extract feature bands that can distinguish between WO,OW,oil slick,and *** number of bands was reduced from 224 to 134 after feature selection on the Airborne Visible Infrared Imaging Spectrometer(AVIRIS)data and from 126 to 100 on the S185 data.(2)With feature selection,the overall accuracy and Kappa of the identification results for the training area are 91.80%and 0.86,respectively,improved by 2.62%and 0.04,and the overall accuracy and Kappa of the identification results for the migration area are 86.53%and 0.80,respectively,improved by 3.45%and 0.05.(3)The oil emulsion id

关键词： oil emulsions identification hyperspectral remote sensing feature selection convolutional neural network(CNN) spatial-temporal transferability

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oil emulsions in naturally fractured Porous Media

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Petroleum 2019年第3期5卷 215-226页

作者： A.Paulina Gomora-Figueroa Rodolfo G.Camacho-Velazquez Jose Guadarrama-Cetina T.Ivan Guerrero-Sarabi División de Ingeniería en Ciencias de la Tierra Facultad de IngenieríaUniversidad Nacional Autónoma de MéxicoCircuito ExteriorCiudad Universitaria04510Ciudad de MéxicoMexico Instituto de Alta Investigación Universidad de TarapacáAntofagastaCasilla 7D AricaChile

Most of the studies regarding the formation and stability of emulsions focus on the conditioning and management of crude oil on surface *** a great deal of the crude oil produced is in the form of stable emulsions,it is often claimed that these emulsions are formed through chokes and other flow constrictions in oil field ***,emulsions are produced in wells,which not only lack these constrictions but also are produced at low flow rates,demonstrating the fact that emulsions can be formed within the well *** present work reviews the literature regarding the formation and properties of heavy and extra-heavy oil emulsions in naturally fractured porous media due to the current relevance that these types of crude oil exploitation take,satisfying the hydrocarbon energy ***,emulsions have received more attention recently since they can be formed in-situ and improve oil *** understand the flow mechanics of emulsions in porous media,different models to describe their transportation are ***,the formation of emulsions in the reservoir for enhanced oil recovery purposes,including the use of nanoparticlestabilized emulsions is discussed.

关键词： oil emulsions Naturally fractured Porous media Heavy and extra-heavy oil Transportation Enhanced recovery

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