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dc.date.accessioned2021-09-07T02:02:36Z
dc.date.available2021-09-07T02:02:36Z
dc.date.issued2021-09-07
dc.identifier.urihttps://library.universitaspertamina.ac.id//xmlui/handle/123456789/4362
dc.description.abstractTechnology development give another ways of processing geological data using machine learning. For example, this research will give an example of machine learning application in geology for determining facies distribution using well data and seismic in Volve Field, North Sea. The methods in this research include preleminary research, data selection, data creating, and processing using machine learning. Result of this research is facies interpretation by machine learning classification, confusion matrix of every algorithm, result of survey for determining the best machine learning algorithm by qualitative analysis. Result of procesing indicating that processing effected by several factor, as follows : data preprocessing, type of machine learning algorithm, data distribution. Based on qualitative and quantitative analysis is known the best classification for determining facies distribution using machine learning are LGBM algorithm and XGBoost algorithm. Key words : machine learning, spectral decompsition, facies mapping, seismicen_US
dc.language.isootheren_US
dc.publisherUniversitas Pertaminaen_US
dc.titlePENENTUAN SEBARAN FASIES MENGGUNAKAN MACHINE LEARNING BERDASARKAN METODE ATRIBUT SEISMIK SPECTRAL DECOMPOSITION PADA LAPANGAN VOLVE, NORTH SEAen_US
dc.title.alternativeDetermination of Facies Distribution Using Machine Learning Based on Spectral Decomposition Seismic Attribute Method on Volve Field, North Seaen_US
dc.typeThesisen_US


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