Practical content of the elements of petrophysical model of terrigenous sandstones — oil and gas reservoirs in neural networks, deep learning and regression methods

• Datum: 2025
• Hauptverfasser: Vyzhva, Serhiy, Gozhyk, Andriy, Shabatura, Oleksandr, Onyshchuk, Viktor, Onyshchuk, Dmytro, Onyshchuk, Ivan
• Format: Artikel
• Sprache: Ukrainisch
• Veröffentlicht: S. Subbotin Institute of Geophysics of the NAS of Ukraine 2025
• Schlagworte: petrophysics; terrigenous oil and gas reservoirs; multiple regression; machine learning; neural networks
• Online Zugang: https://journals.uran.ua/geofizicheskiy/article/view/309312
• Назва журналу: Geofizicheskiy Zhurnal

An important problem in the search for oil and gas fields is the ability to predict key petrophysical properties such as porosity, permeability, etc. Along with traditional regression analysis, neural network methods and deep learning technologies are becoming increasingly common. All of them requir...