文献
J-GLOBAL ID:202202213793542758
整理番号:22A0805926
坑井検層データおよび多変量分析,機械学習,および地球化学的分析の統合法を用いた全有機炭素の根源岩ポテンシャルと予測の評価【JST・京大機械翻訳】
Evaluation of Source Rock Potentiality and Prediction of Total Organic Carbon Using Well Log Data and Integrated Methods of Multivariate Analysis, Machine Learning, and Geochemical Analysis
著者 (8件):
Nyakilla Edwin E.
(Department of Petroleum Engineering, School of Earth Resources, China University of Geosciences, Wuhan, China)
,
Silingi Selemani N.
(Department of Petroleum Engineering, School of Earth Resources, China University of Geosciences, Wuhan, China)
,
Silingi Selemani N.
(Department of Geology, Earth Sciences Institute of Shinyanga, ESIS, Shinyanga, Tanzania)
,
Shen Chuanbo
(Department of Petroleum Engineering, School of Earth Resources, China University of Geosciences, Wuhan, China)
,
Shen Chuanbo
(Department of Petroleum Geology School of Earth Resources, China University of Geosciences, Wuhan, China)
,
Jun Gu
(Department of Petroleum Engineering, School of Earth Resources, China University of Geosciences, Wuhan, China)
,
Mulashani Alvin K.
(Department of Petroleum Engineering, School of Earth Resources, China University of Geosciences, Wuhan, China)
,
Chibura Patrick E.
(Department of Petroleum Engineering, School of Earth Resources, China University of Geosciences, Wuhan, China)
資料名:
Natural Resources Research
(Natural Resources Research)
巻:
31
号:
1
ページ:
619-641
発行年:
2022年
JST資料番号:
W0688A
ISSN:
1520-7439
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
ドイツ (DEU)
言語:
英語 (EN)