Bazhenov Fm Classification Based on Wireline Logs / D. A. Simonov, V. E. Baranov, N. V. Bukhanov
Уровень набора: (RuTPU)RU\TPU\network\2499, IOP Conference Series: Earth and Environmental ScienceЯзык: английский.Страна: .Серия: Well drillingРезюме или реферат: This paper considers the main aspects of Bazhenov Formation interpretation and application of machine learning algorithms for the Kolpashev type section of the Bazhenov Formation, application of automatic classification algorithms that would change the scale of research from small to large. Machine learning algorithms help interpret the Bazhenov Formation in a reference well and in other wells. During this study, unsupervised and supervised machine learning algorithms were applied to interpret lithology and reservoir properties. This greatly simplifies the routine problem of manual interpretation and has an economic effect on the cost of laboratory analysis..Примечания о наличии в документе библиографии/указателя: [References: 4 tit.].Тематика: электронный ресурс | труды учёных ТПУ | каротажные диаграммы | баженовская свита | машинное обучение | скважины | лабораторный анализ Ресурсы он-лайн:Щелкните здесь для доступа в онлайн | Щелкните здесь для доступа в онлайнTitle screen
[References: 4 tit.]
This paper considers the main aspects of Bazhenov Formation interpretation and application of machine learning algorithms for the Kolpashev type section of the Bazhenov Formation, application of automatic classification algorithms that would change the scale of research from small to large. Machine learning algorithms help interpret the Bazhenov Formation in a reference well and in other wells. During this study, unsupervised and supervised machine learning algorithms were applied to interpret lithology and reservoir properties. This greatly simplifies the routine problem of manual interpretation and has an economic effect on the cost of laboratory analysis.
Для данного заглавия нет комментариев.