Data-Driven Connectionist Models for Performance Prediction of Low Salinity Waterflooding in Sandstone Reservoirs
Afshin Tatar, Ingkar A. Askarova, Ali Shafiei, Mahsheed Rayhani
Abstract
. The CMIS model proposed here can be applied with a high degree of confidence to predict the performance of LSWF in sandstone reservoirs. The database assembled for the purpose of this research work is so far the largest and most comprehensive of its kind, and it can be used to further delineate mechanisms behind LSWF and optimization of this EOR process in sandstone reservoirs.
Topics & Concepts
Support vector machineFeature selectionMean squared errorMultilayer perceptronComputer scienceData miningOutlierArtificial intelligenceMachine learningArtificial neural networkMathematicsStatisticsEnhanced Oil Recovery TechniquesReservoir Engineering and Simulation MethodsHydraulic Fracturing and Reservoir Analysis