Mechanistic modeling of low salinity water flooding

Low salinity waterflood (LSW) has become an attractive enhanced oil recovery (EOR) method as it shows more advantages than conventional chemical EOR methods in terms of chemical costs, environmental impact, and field process implementation. Extensive laboratory studies in the past two decades have proposed several pore-scale mechanisms of oil displacement during LSW flooding, which are still open for discussion. However, the capability of reservoir simulators to model accurately this process is very limited. This paper provides a critical review of the state of the art in research and field applications of LSW. The focus is on a widely agreed mechanism that is the wettability alteration from preferential oil wetness to water wetness of formation rock surfaces. Ion exchange and geochemical reactions have been experimentally found to be important in oil mobilization due to enhanced water spreading at low salinity. To evaluate the significance of this surface wetting mechanism, a comprehensive ion exchange model with geochemical processes has been developed and coupled to the multi-phase multi-component flow equations in an equation-of-state compositional simulator. This new model captures most of the important physical and chemical phenomena that occur in LSW, including intra-aqueous reactions, mineral dissolution/precipitation, ion exchange and wettability alteration. The proposed LSW model is tested using the low-salinity core-flood experiments reported by Fjelde et al. (2012) for a North Sea reservoir and the low-salinity and high-salinity heterogeneous core-flood experiments by Rivet (2009) for a Texas reservoir. Excellent agreements between the model and the experiments in terms of effluent ion concentrations, effluent pH, and oil recovery were achieved. In addition, the model was also proved to be highly comparable with the ion-exchange model of the geochemistry software PHREEQC for both low salinity and high salinity (Appelo, 1994). Important observations in laboratory and field tests such as a local pH increase, a decrease in divalent effluent concentration, mineralogy contributions, and the influence of connate water and injected brine compositions can be reproduced with the proposed LSW model. Built in a robust reservoir simulator, it serves as a powerful tool for LSW design and the interpretation of process performance in field tests. Although the advantages of LSW have been reported, none of the systematic approaches has addressed the issues of modeling and predicting LSW field-scale performance. The new modeling approach introduced in this research can effectively capture the critical effects of geology in the LSW process. This integrated modeling approach involves the use of geological software, a reservoir simulator, and a robust optimizer in a closed loop for sensitivity analysis, history matching, optimization, and uncertainty assessment. The field-scale benefits of secondary and tertiary LSW are then addressed. (C) 2016 Elsevier B.V. All rights reserved.