## The Performance of Engineered Water Flooding to Enhance High Viscous Oil Recovery
With the help of machine learning methods, other screening criteria were developed by analyzing available data of different successful and unsuccessful experimental studies reported in the literature. [PERSON] et al. reported such an approach to screening required criteria for LSWI in sandstone reservoirs [17]. The authors mentioned that a combination of criteria is needed to achieve the wettability alteration, and the effect of a single parameter is not enough to evaluate the method's performance. A similar data-driven analysis was reported by [PERSON] et al. for carbonate formations [18]. Data from different sources were analyzed to investigate the effect of rock and fluid properties on the active mechanisms of LSWI in carbonates and the success of the approach. They found that parameters such as pH, water salinity, and ion composition are strong parameters to forecast the possible outcome of the LSWI implementation. The effect of oil properties as a screening parameter on the performance of LSWI was also discussed in other sources such as [PERSON] et al. [6] and [PERSON] et al. [7]. It is widely reported that the initial state of wettability is strongly affected by the crude oil properties. Presence of polar components in oil results in a more oil-wet state due to their adsorption to the rock surface. Parameters such as the acid and the base number impact carbonates wettability and, consequently, recovery due to the wettability alteration by LSWI. The higher the acid number, the more oil-wet rock is, which affects the oil extraction by LSWI [19]. Base number variation was also studied by [PERSON] et al. (2008) [20]. Hence, acid and base numbers are other oil properties that should be considered for a successful selection and design of LSWI [21]. The effect of other properties, such as the fraction of heavy polar components in oil, was also investigated by [PERSON] et al. [22; 23]. Even though considering the oil parameters are significant in the LSWI screening and implementation, the effect of physical oil parameters such as oil viscosity and API on the success of LSWI has not been investigated yet. [16]. For example, in 160 core flooding tests analyzed by [PERSON] et al. [18], the viscosity of only 3% of oil samples was higher than 15 cp, which shows the tendency to apply LSWI for light oils. Hence, there is still a question on the performance of LSWI in heavier oil, where other parameters such as acid number are favorable. The application of LSWI in the combination of thermal EOR methods for heavy oil was reported in a few papers in the literature. [PERSON] et al. [23] conducted oil displacement experiments with different oil samples with 1700, 1000, and 700 cp viscosity. Hot water was used in their tests, which combined thermal EOR and LSWI. Their results showed a low recovery for oil samples with 1700 cp viscosity. [PERSON] et al. [24; 25] conducted a similar approach with LSWI and thermal steam injection to a core saturated with a 600 cp oil sample. The core flooding was conducted on a cycled injection scheme. Despite the steam effect here, the injection of LSWI resulted in higher recovery than the standalone steam flooding, which shows the possible activity of LSWI mechanisms for heavy oil. [PERSON] et al. [26] and [PERSON] et al. [27] also used LSWI for 170-190 cp oil combined with chemical EOR methods. Due to the high temperature and presence of chemicals, still, the effect of LSWI is not clear. Similar recovery tests for heavy oil were reported in the papers [28; 29; 30; 31; 32; 33; 34]. Hence, still, the applicability of LSWI as a standalone EOR approach for heavy oil is not clear. Oil viscosity should be another criterion for screening LSWI as an EOR approach. In this study, we will answer these questions by conducting laboratory experiments and collecting data reported in the literature.