UB Paderborn / Katalog / Suche / in CDI

Sortiert nach

Einfacher Volltextzugriff von (fast) überall

Installieren Sie die LibKey Nomad-Browsererweiterung und erhalten Sie von vielen Webseiten einfachen Zugriff auf lizenzierte Volltexte oder Open Access Publikationen. Mehr erfahren...

Data-Driven Signal–Noise Classification for Microseismic Data Using Machine Learning

Energies (Basel), 2021-03, Vol.14 (5), p.1499

2021

Volltextzugriff (PDF)

Improved prediction of shale gas productivity in the Marcellus shale using geostatistically generated well-log data and ensemble machine learning

Computers & geosciences, 2023-12, Vol.181, p.105452, Article 105452

2023

Volltextzugriff (PDF)

Spatiotemporal interpretation of three-phase saturation behaviors in gas hydrate formation and dissociation through deep learning modeling

Geoenergy Science and Engineering, 2023-02, Vol.221, p.111219, Article 111219

2023

Volltextzugriff (PDF)

Productivity prediction in the Wolfcamp A and B using weighted voting ensemble machine learning method

Gas Science and Engineering, 2023-03, Vol.111, p.204916, Article 204916

2023

Volltextzugriff (PDF)

Synergistic enhancement of productivity prediction using machine learning and integrated data from six shale basins of the USA

Geoenergy Science and Engineering, 2023-10, Vol.229, p.212068, Article 212068

2023

Volltextzugriff (PDF)

Modeling and prediction of slug characteristics utilizing data-driven machine-learning methodology

Journal of petroleum science & engineering, 2020-12, Vol.195, p.107712, Article 107712

2020

Volltextzugriff (PDF)

Evaluation of saturation changes during gas hydrate dissociation core experiment using deep learning with data augmentation

Journal of petroleum science & engineering, 2022-02, Vol.209, p.109820, Article 109820

2022

Volltextzugriff (PDF)

Classification and Application of Digital Oil Field System

Journal of the Korean Society of Mineral and Energy Resources Engineers, 2014-10, Vol.51 (5), p.750-756

2014

Volltextzugriff (PDF)

Productivity Prediction in the Upper Wolfcamp Formation Using Weighted Voting Ensemble Machine Learning Method

SSRN Electronic Journal

Volltextzugriff (PDF)

Spatiotemporal Interpretation of Three-Phase Saturation Behaviors in Gas Hydrate Formation and Dissociation Through Deep Learning Modeling

SSRN Electronic Journal

Volltextzugriff (PDF)

1 – 10 von 10

Suche als RSS-Feed

Suchergebnisse filtern

Filter anzeigen

Nur zeigen

Geprüft (Peer-Review)
(5)
Mit Volltextzugriff
(7)

Publikationsform

Artikel
(10)

Sprache

Englisch
(10)

Erscheinungsjahr

n.n

Kollektion

Menü

Weitere Dienste

Einstellungen

Data-Driven Signal–Noise Classification for Microseismic Data Using Machine Learning

Improved prediction of shale gas productivity in the Marcellus shale using geostatistically generated well-log data and ensemble machine learning

Spatiotemporal interpretation of three-phase saturation behaviors in gas hydrate formation and dissociation through deep learning modeling

Productivity prediction in the Wolfcamp A and B using weighted voting ensemble machine learning method

Synergistic enhancement of productivity prediction using machine learning and integrated data from six shale basins of the USA

Modeling and prediction of slug characteristics utilizing data-driven machine-learning methodology

Evaluation of saturation changes during gas hydrate dissociation core experiment using deep learning with data augmentation

Classification and Application of Digital Oil Field System

Productivity Prediction in the Upper Wolfcamp Formation Using Weighted Voting Ensemble Machine Learning Method

Spatiotemporal Interpretation of Three-Phase Saturation Behaviors in Gas Hydrate Formation and Dissociation Through Deep Learning Modeling

Suchergebnisse filtern