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Novel Correlation for Calculating Water Saturation in Shaly Sandstone Reservoirs Using Artificial Intelligence: Case Study from Egyptian Oil Fields

Reda Abdel Azim, Ghareb Hamada

2022ACS Omega16 citationsDOIOpen Access PDF

Abstract

) of 0.973, lowest mean-square error (MSE) of 0.048, lowest average absolute percent relative error (AAPRE) of 0.042, and standard deviation (SD) of 0.24. To the best of our knowledge, the current study and the proposed ANN model establish a novel base in the estimation of formation water saturation.

Topics & Concepts

Water saturationSaturation (graph theory)Artificial neural networkMean squared errorSoil sciencePetroleum engineeringApproximation errorWell loggingPorosityGeologyMineralogyGeotechnical engineeringMathematicsApplied mathematicsComputer scienceStatisticsMachine learningCombinatoricsHydrocarbon exploration and reservoir analysisReservoir Engineering and Simulation MethodsHydraulic Fracturing and Reservoir Analysis
Novel Correlation for Calculating Water Saturation in Shaly Sandstone Reservoirs Using Artificial Intelligence: Case Study from Egyptian Oil Fields | Litcius