Classification of the Bazhenov Formation Using Well Logs (R Field)

Classification of the Bazhenov Formation Using Well Logs (R Field)

Bibliographic Details
Parent link:Через интеграцию геонаук - к постижению гармонии недр: материалы 7-ой Международной геолого-геофизической конференции, Санкт-Петербург, 11-14 апреля, 2016 г.. [5 c.].— , 2016
Corporate Author: Национальный исследовательский Томский политехнический университет (ТПУ) Институт природных ресурсов (ИПР) Центр подготовки и переподготовки специалистов нефтегазового дела (ЦППС НД) Лаборатория геологии месторождений нефти и газа (ЛГМНГ)
Other Authors: Simonov D. A. Dmitry Arturovich, Baranov V. E. Vitaliy Evgenievich, Bukhanov N. V. Nikita Vladimirovich, Beschasova P. A. Polina Anatoljevna
Summary:Title screen
This paper consider the main aspects of the Bazhenov formation interpretation and applying of machine learning algorithms in cases a of Kolpashev type section of the Bazhenov formation. Application of automatic algorithms of classification which would transfer the scale of research from small to large. Machine learning algorithms help to interpret the Bazhenov formation in reference well and in the other wells. During this work the unsupervised and supervised machine learning algorithms were applied to interpret the lithology and reservoir properties. This greatly simplifies the routine problem which deals with manual interpretation and has an economic effect deal with cost of laboratory analysis.
Режим доступа: по договору с организацией-держателем ресурса
Published: 2016
Series:Exploration & Production in Unconventional Reservoirs
Subjects:
электронный ресурс
труды учёных ТПУ
Online Access:http://dx.doi.org/10.3997/2214-4609.201600093
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=650140

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