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

Bibliografische gegevens
Parent link:Через интеграцию геонаук - к постижению гармонии недр.— 2016.— [5 c.]
Coauteur: 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)
Andere auteurs: Simonov D. A. Dmitry Arturovich, Baranov V. E. Vitaliy Evgenievich, Bukhanov N. V. Nikita Vladimirovich, Beschasova P. A. Polina Anatoljevna
Samenvatting: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
Taal:Russisch
Gepubliceerd in: 2016
Reeks:Exploration & Production in Unconventional Reservoirs
Onderwerpen:
Online toegang:http://dx.doi.org/10.3997/2214-4609.201600093
Formaat: Elektronisch Hoofdstuk
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=650140

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