Use of neural networks for studying nontraditional hydrocarbon reservoirs (an example of Visean black shales of the Dnipro-Donets Basin)

• Datum: 2025
• Hauptverfasser: Kurtyi, V.O., Verpakhovska, O.O.
• Format: Artikel
• Sprache: Ukrainisch
• Veröffentlicht: S. Subbotin Institute of Geophysics of the NAS of Ukraine 2025
• Schlagworte: unconventional hydrocarbon reservoirs; Dnieper–Donets Basin; petrophysical properties; organic-matter content (TOC); neural networks
• Online Zugang: https://journals.uran.ua/geofizicheskiy/article/view/341701
• Назва журналу: Geofizicheskiy Zhurnal

The paper presents a study of Visean-stage clay shales of the Dnieper-Donets Basin using a neural network algorithm. The Dnieper-Donets Basin is among Ukraine’s prospective regions for shale gas exploration. Given the need to boost hydrocarbon production from depleted fields through non-traditional...