Uncertainty Analysis of Smart Waterflood Recovery Performance in Clastic Reservoirs

In recent years, numerous laboratory studies have documented the benefits of smart waterflooding as an emerging enhanced oil recovery (EOR) process, along with a few successful field applications, notably clastic reservoirs. In most cases, there are undeniable inconsistencies between lab and field results. This process has led to unpredictable outcomes and misleading prediction of smart waterflooding projects. Hence, this work is conducted to evaluate uncertainties in smart waterflooding from laboratory to field-scale. An one-dimensional (1-D) reactive transport model was developed and validated with flooding experiments. Validation shows that combinations of various matching parameters can be used to interpret the experiment. Different realizations lead to different results when extended to 3-D heterogeneous model. The sensitivity of parameters like grid size and heterogeneity in full-field model majorly influences smart waterflooding performance, which is responsible for the inconsistencies. Therefore, these parameters should be considered in field-scale simulation to fully demonstrate the potential of smart waterflooding.