Data-Driven Connectionist Models for Performance Prediction of Low Salinity Waterflooding in Sandstone Reservoirs

ACS Omega, 2021

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.1021/acsomega.1c05493
Data confidence 85 high
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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.