LOW SALINITY WATER FLOODING SIMULATION STUDY

Low salinity water flooding(LSWF) is a recent enhanced oil recovery (EOR) method which is applied by injecting water with a lower salinity than initial connate water. Although a lot of laboratory experiments and tests have shown LSWF’s potential in EOR, There have not been done many modelling studies on this field. Moreover, there is lack of economic analysis to justify the application of LSWF for most of the simulation studies. Several hypotheses have proposed as LSWF mechanisms, namely electrical double layer effect, pH effect, fines migration and multicomponent ion exchange (MIE). However, there is still no definite theory that supports LSWF effects. Thus, the main objective of this research is to evaluate the effects of salinity in LSWF on oil recovery.
In this study, effects of salinity in LSWF are investigated through simulations of a 3 dimensional synthetic reservoir model by ECLIPSE 100 software. The model is lateral heterogeneous with only oil and water phase. Moreover, only one type of salt is assumed to be present in the water. There are 2 base cases in the first phase of study. The first base case uses high salinity(HS) water flooding technique by injecting 35000ppm of brine from the starting to the end of production, totally 10 years or 3650 days. The other case uses low salinity water flooding technique by injecting 1000ppm of brine continuously for the same production life, in order to compare the effect of salinity with the HS base case. Large wettability sensitivity was observed, showing that oil/water relative permeability and saturation are the main variables during simulations when BRINE option is activated. Findings obtained after injection of brines with different salinities indicated oil recovery improves with a decrease in salinity of the injected brines. Then, the second phase of the study will be comparing the oil recovery by alternating the LS and HS injection days. HS will be the first phase of injection followed by LS. Different cases will be simulated in this phase and evaluated through economic analysis. The best LSWF case will be selected after considering its economic feasibility.