Reservoir Quality Prediction of Gas-Bearing Carbonate Sediments in the Qadirpur Field: Insights from Advanced Machine Learning Approaches of SOM and Cluster Analysis

• Published in: Minerals (Basel) Vol. 13; no. 1; p. 29
• Main Authors: Rashid, Muhammad, Luo, Miao, Ashraf, Umar, Hussain, Wakeel, Ali, Nafees, Rahman, Nosheen, Hussain, Sartaj, Aleksandrovich Martyushev, Dmitriy, Vo Thanh, Hung, Anees, Aqsa
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2023
• Subjects: Artificial intelligence; Basins; Carbonate sediments; Carbonates; Cluster analysis; Clustering; Data compression; Datasets; Effective porosity; Eocene; Fault lines; Gas wells; Geology; Hydrocarbons; Limestone; lithological identification; Lithology; Machine learning; Neural networks; Oil wells; Parameters; Permeability; Porosity; reservoir quality prediction; Reservoirs; Rocks; Saturation; Sedimentary rocks; Sedimentation & deposition; Sediments; Self organizing maps; Shale; Shales; SOM; Indus Valley; Pakistan; Gondwana
• ISSN: 2075-163X; 2075-163X
• DOI: 10.3390/min13010029

The detailed reservoir characterization was examined for the Central Indus Basin (CIB), Pakistan, across Qadirpur Field Eocene rock units. Various petrophysical parameters were analyzed with the integration of various cross-plots, complex water saturation, shale volume, effective porosity, total porosity, hydrocarbon saturation, neutron porosity and sonic concepts, gas effects, and lithology. In total, 8–14% of high effective porosity and 45–62% of hydrocarbon saturation are superbly found in the reservoirs of the Eocene. The Sui Upper Limestone is one of the poorest reservoirs among all these reservoirs. However, this reservoir has few intervals of rich hydrocarbons with highly effective porosity values. The shale volume ranges from 30 to 43%. The reservoir is filled with effective and total porosities along with secondary porosities. Fracture–vuggy, chalky, and intracrystalline reservoirs are the main contributors of porosity. The reservoirs produce hydrocarbon without water and gas-emitting carbonates with an irreducible water saturation rate of 38–55%. In order to evaluate lithotypes, including axial changes in reservoir characterization, self-organizing maps, isoparametersetric maps of the petrophysical parameters, and litho-saturation cross-plots were constructed. Estimating the petrophysical parameters of gas wells and understanding reservoir prospects were both feasible with the methods employed in this study, and could be applied in the Central Indus Basin and anywhere else with comparable basins.