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Effect of preprocessing on performances of machine learning-based mineral composition analysis on gas hydrate sediments, ulleung basin, East Sea

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Petroleum Science 2025年第1期22卷 151-162页

作者： Hongkeun Jin Ju Young Park Sun Young Park Byeong-Kook Son Baehyun Min Kyungbook Lee Department of Geoenvironmental Sciences Kongju National University Tunnel & Underground Facility Division ESCO Consultant & Engineers Company Yellow Sea Institute of Geoenvironmental Sciences Petroleum and Marine Research Division Korea Institute of Geoscience and Mineral Resources Department of Climate and Energy Systems Engineering Ewha Womans University Center for Climate/Environment Change Prediction Research Ewha Womans University

Gas hydrate(GH) is an unconventional resource estimated at 1000-120,000 trillion *** on GH is ongoing to determine its geological and flow characteristics for commercial production. After two large-scale drilling expeditions to study the GH-bearing zone in the ulleung basin, the mineral composition of 488 sediment samples was analyzed using X-ray diffraction(XRD). Because the analysis is costly and dependent on experts, a machine learning model was developed to predict the mineral composition using XRD intensity profiles as input data. However, the model's performance was limited because of improper preprocessing of the intensity profile. Because preprocessing was applied to each feature, the intensity trend was not preserved even though this factor is the most important when analyzing mineral composition. In this study, the profile was preprocessed for each sample using minmax scaling because relative intensity is critical for mineral analysis. For 49 test data among the 488data, the convolutional neural network(CNN) model improved the average absolute error and coefficient of determination by 41% and 46%, respectively, than those of CNN model with feature-based preprocessing. This study confirms that combining preprocessing for each sample with CNN is the most efficient approach for analyzing XRD data. The developed model can be used for the compositional analysis of sediment samples from the ulleung basin and the Korea Plateau. In addition, the overall procedure can be applied to any XRD data of sediments worldwide.

关键词： Sample-based preprocessing X-ray diffraction (XRD) Machine learning Mineral composition Gas hydrate (GH) ulleung basin

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Specific oceanographic characteristics and phytoplankton responses influencing the primary production around the ulleung basin area in spring

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Acta Oceanologica Sinica 2020年第2期39卷 107-122页

作者： Minji Lee Jin Ho Kim Yun-Bae Kim Chan Hong Park Kyoungsoon Shin Seung Ho Baek South Sea Research Institute Korea Institute of Ocean Science and TechnologyGeoje 53201Korea ulleungdo/Dokdo Ocean Science Station Korea Institute of Ocean Science and TechnologyUlleungdo 40205Korea Dokdo Research Center East Sea Research InstituteKorea Institute of Ocean Science and TechnologyUljin 36315Korea

The East Sea(Sea of Japan)is a marginal,semi-closed sea in the northwestern *** ulleung basin area,which is located near the subpolar front of the East Sea,is known to have high primary production and good fisheries in spring *** episodic wind-driven events during the spring of 2017,horizontal and vertical profiles of physical chemical biological factors were investigated at 29 stations located in the ulleung basin *** addition,growth responses of phytoplankton communities to nutrient additions were evaluated by bioassay experiments to understand the fluctuation of phytoplankton *** of strong northwestern wind,phytoplankton biomass was scattered and upwelling phenomenon might be suppressed in this *** phytoplankton abundances in the coastal stations were significantly higher than offshore and island *** contrast,the nutrient and chlorophyll a(Chl a)concentrations and the phytoplankton biomass were quite low in all *** was dominated group(>75.1%for coastal,40.0%for offshore and 43.6%for island stations).In the algal bioassays,the phytoplankton production was stimulated by N *** in vivo Chl a values in the+N and+NP treatments were significantly higher than the values in the control and the+P *** on the field survey,the higher nutrients in coastal waters affected the growth of diatom assemblages,however,little prosperity of phytoplankton was observed in the offshore waters despite the injection of sufficient nutrients in bioassay *** growth of phytoplankton depended on the initial cell *** of results indicated that a dominant northwestern wind led to a limited nutrients condition at euphotic layers,and the low level of biomass supply from the coasts resulted in low primary *** supplying nutrients and introducing phytoplankton through the currents are critical to maintain the high productivity in the ulleung basin area of the East Sea.

关键词： ulleung basin ulleungdo and Dokdo spring phytoplankton blooms episodic windstorm algal bioassays primary production

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