Modeling chemical EOR processes using IMPEC and fully IMPLICIT reservoir simulators

Fathi Najafabadi, Nariman
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As easy target reservoirs are depleted around the world, the need for intelligent enhanced oil recovery (EOR) methods increases. The first part of this work is focused on modeling aspects of novel chemical EOR methods for naturally fractured reservoirs (NFR) involving wettability modification towards more water wet conditions. The wettability of preferentially oil wet carbonates can be modified to more water wet conditions using alkali and/or surfactant solutions. This helps the oil production by increasing the rate of spontaneous imbibition of water from fractures into the matrix. This novel method cannot be successfully implemented in the field unless all of the mechanisms involved in this process are fully understood. A wettability alteration model is developed and implemented in the chemical flooding simulator, UTCHEM. A combination of laboratory experimental results and modeling is then used to understand the mechanisms involved in this process and their relative importance. The second part of this work is focused on modeling surfactant/polymer floods using a fully implicit scheme. A fully implicit chemical flooding module with comprehensive oil/brine/surfactant phase behavior is developed and implemented in general purpose adaptive simulator, GPAS. GPAS is a fully implicit, parallel EOS compositional reservoir simulator developed at The University of Texas at Austin. The developed chemical flooding module is then validated against UTCHEM.