APPLICATION OF UNLABELLED BIG DATA AND DEEP SEMI-SUPERVISED LEARNING TO SIGNIFICANTLY IMPROVE THE LOGGING INTERPRETATION ACCURACY FOR DEEP-SEA GAS HYDRATE-BEARING SEDIMENT RESERVOIRS

Application of unlabelled big data and deep semi-supervised learning to significantly improve the logging interpretation accuracy for deep-sea gas hydrate-bearing sediment reservoirs

Due to the extremely complex reservoirs and strong heterogeneity, deep-sea gas hydrate logging porosity calculations still have problems, which further leads to insufficient resource calculation accuracy.Logging reservoir evaluation methods based on intelligence may be able to provide more reliable prediction results, especially the logging evaluat

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The Effect of April 2019 Flash Flood on the Morphology of the Meandering Confluence of the Dinver River to Gamasiab Using SRH-2D Numeric Model

Understanding the morphodynamics of river junctions is an important part of fluvial geomorphological studies that were provided suitable conditions to measure erosion and sediment changes at the junction of Dinver and Gamasiab rivers by the occurrence of floods in April 2019.Due to the complexity, 3D numerical simulation is not cost-effective, and

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