Bazhenov Fm Classification Based on Wireline Logs

書誌詳細
Parent link:IOP Conference Series: Earth and Environmental Science
Vol. 33 : Contemporary Issues of Hydrogeology, Engineering Geology and Hydrogeoecology in Eurasia.— 2016.— [012034, 5 p.]
第一著者: Simonov D. A. Dmitry Arturovich
その他の著者: Baranov V. E. Vitaliy Evgenievich, Bukhanov N. V. Nikita Vladimirovich
要約:Title screen
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.
言語:英語
出版事項: 2016
シリーズ:Well drilling
主題:
オンライン・アクセス:http://dx.doi.org/10.1088/1755-1315/33/1/012034
http://earchive.tpu.ru/handle/11683/33992
フォーマット: 電子媒体 図書の章
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=649495