Permeability prediction of heterogeneous carbonate gas condensate reservoirs applying group method of data handling

• Published in: Marine and petroleum geology Vol. 139; p. 105597
• Main Authors: Zanganeh Kamali, Masoud, Davoodi, Shadfar, Ghorbani, Hamzeh, Wood, David A., Mohamadian, Nima, Lajmorak, Sahar, Rukavishnikov, Valeriy S., Taherizade, Farzaneh, Band, Shahab S.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.05.2022
• Subjects: Gas-condensate reservoirs; Group method of data handling GMDH; Heterogeneous carbonate reservoirs; Machine learning; Permeability prediction; Specific surface area; Heterogeneous carbonate reservoirs; Gas-condensate reservoirs; Specific surface area; Permeability prediction; Group method of data handling GMDH; Machine learning

Carbonate petroleum reservoirs typically have lower permeabilities and recovery factors than sandstone reservoirs, so the natural fractures they often incorporate have positive impacts on resource recovery and fluid production rates. Quantifying effective permeability, incorporating contributions fr...