Waterflooding as a secondary oil recovery method is still the most commonly used technique for fluid injection since 1865. Recently researchers have discovered that the injected water quality is important and it should be monitored in addition to volume of water injected. This technique is known as low salinity water injection, LoSal®1, Smart Waterflood and Advanced Ion Management.
Evidence from laboratory studies, supported by several field tests, has distinctly shown that injecting low salinity water can have a significant impact on oil recovery. Although there are many LoSal® experimental results reported in the literature, publications on modeling this process are scarce. In this paper, we propose a mechanistic modeling approach for the low salinity water injection. We believe no matter the manner and details of mechanism, it ought to be all about ions. The key objective in this approach is to link the water-rock chemistry to changes in the state of a rock (e.g., wettability). Since geochemical reactions are the basis for this mechanistic modeling, we would need a geochemical engine to handle geochemical reactions in the reservoir for properly modeling LoSal®. Toward this goal, it was decided to couple IPhreeqc, an open source geochemical module available by United States Geological Survey (USGS), with UTCHEM, an in-house research chemical flooding reservoir simulator developed at The University of Texas at Austin. An algorithm is presented for modeling the geochemistry in an IMPEC (implicit in pressure and explicit in concentration) solution algorithm. Finally, we show how apply the integrated tool, UTCHEM-IPhreeqc, to model low salinity water injection.
Geochemical-based models can easily be implemented in this modeling approach and also compared against experimental results for validation. Implementation of several mechanisms can finally reveal the dominant mechanism for the low salinity water injection.