# Using Low Salinity Waterflooding to Improve Oil Recovery in Naturally Fractured Reservoirs
## 2 Methodology
### Determination of Weighting Factor (WF)  
The weighting factor plays a significant role in determining the salinity of the brine mixture, hence, its properties, as illustrated in Table 1. It controls the dilution process or blending between the \begin{table}
\begin{tabular}{l c c c} \hline \hline
**The Changed Parameters during Low** & **No. of** & **Change \%, (+ Increment, \(-\) Reduction)** \\ \cline{2-4}
**Salinity Waterflooding** & **Samples** & **Minimum** & **Average** & **Maximum** \\ \hline Residual oil saturation (S\({}_{\text{or,a}}\)) & 39 & \(-1.4\) & \(-26.1\) & \(-63.6\) \\ Oil saturation exponent (n\({}_{\text{o,a}}\)) & 9 & \(-11.4\) & \(-28.5\) & \(-33.3\) \\ Water relative permeability (k\({}_{\text{rw,a}}\)) & 3 & \(+9.3\) & \(+32.3\) & \(+48.4\) \\ Water saturation exponent (n\({}_{\text{w,a}}\)) & 9 & \(+12.5\) & \(+36.2\) & \(+56.7\) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Quantitative summary of the impact of the low salinity on the oil recovery through relative permeability parameters which was calculated from the published results of [20; 21; 23; 25; 26]. The Minimum and Maximum parameter values were computed from the references’ results while the average was obtained arithmetically. Figure 1: The generated relative permeability sets for a fractured formation using the calculated ranges in Table 2 for the saturation exponents and saturation endpoints. The black curves represent the original relative permeability set, while the coloured curves represent the relative permeability of the flooded region by low salinity brine for three levels of alterations. high salinity and the injected low salinity water in the mixing zone. [PERSON] [24; 27] has referred to a linear relationship of the weighting factor, as shown in Equation (3):  
\[WF=1-\left(\frac{SC_{mix}-SC_{LoSal}}{SC_{max~{}eff}-SC_{LoSal}}\right) \tag{3}\]  
where: \begin{tabular}{l l} WF & Weighting factor, fraction \\ SC\({}_{\text{mix}}\) & Brine mixture salinity, ppm. \\ SC\({}_{\text{LoSal}}\) & Injected brine salinity, ppm. \\ SC\({}_{\text{maxeff}}\) & Maximum effective salinity, ppm. \\ \end{tabular}   
This linear relationship might be valid when the differences between the minimum salinity and the maximum effective salinity ranges are not very high. However, in a significant salinity contrast, an exponential relationship is more appropriate to represent the salinity increment in the mixing zone. This contrast is applicable in the case of formation water in the petroleum reservoirs, where its salinity can be as high as 200,000 ppm or more (e.g., Nahr Umr reservoir in Iraq has a formation water salinity of 200,000 ppm [28]). In contrast, the salinity of the injected fluid is several thousands of ppm. In this paper, we present an approach to estimate the weighting factor using a one-dimensional model. The model simulated a highly idealised fractional flow displacement process of Buckley-Leverett. The dimensions of the model were (1000 ft \(\times\) 25 ft \(\times\) 50 ft) with 5 ft resolution in the \(x\)-direction. A relative permeability set and capillary pressure data of a fractured formation were used along with a proper fluid model to initialise the simulation model. The model represents an immiscible oil-water system and comprises an injector and a producer at the grid ends. A steady-state displacement was designed using controlled surface rates for both production and injection. A conventional water injection scenario was simulated using a tracer concentration of 3000 for the injected water and a tracer of 100,000 for the formation water. Meanwhile, both injected water and formation water have the same high salinity. The results of the tracer model are illustrated through the profile of tracer concentration in Figure 2A and the profile of water saturation in Figure 2B. The mixing region of the tracer concentration during water injection occurred in a limited interval in the mixing zone.