Comparison of Seismic Traces Clustering Efficiency of Different Unsupervised Machine Learning Algorithms in Forward Seismic Models / I. I. Churochkin [et al.]
Язык: английский.Страна: .Серия: AI/Digitalization for Interpretation - Various ApplicationРезюме или реферат: In this study, it is proposed to build geological model based on proportions of fluvial deposits outcrop. Then forward seismic model is constructed and clustering of seismic traces by using different unsupervised algorithms (k-means, DBSCAN and Agglomerative clustering) is performed. Results are compared with ground truth, which in our case is NTG map of interval of interest in geological model. Finally the optimal settings of the algorithms and the most accurate clustering method are identified..Аудитория: .Тематика: электронный ресурс | труды учёных ТПУ | сейсмические трассы | неконтролируемые процессы Ресурсы он-лайн:Щелкните здесь для доступа в онлайнНет реальных экземпляров для этой записи
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In this study, it is proposed to build geological model based on proportions of fluvial deposits outcrop. Then forward seismic model is constructed and clustering of seismic traces by using different unsupervised algorithms (k-means, DBSCAN and Agglomerative clustering) is performed. Results are compared with ground truth, which in our case is NTG map of interval of interest in geological model. Finally the optimal settings of the algorithms and the most accurate clustering method are identified.
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