Surfactant adsorption in porous media is one of the major criteria which decide the economic viability of surfactant flooding in chemical enhance oil recovery applications (CEOR). In this study, the static adsorption of a novel in-house synthesized anionic surfactant was investigated onto crushed Berea sandstone. The point of zero (PZC) charge for Berea sandstone and critical micelle concentration (CMC) of anionic surfactant are also reported in this paper. The investigated PZC for Berea core was at pH 8.0 and the maximum adsorption of anionic surfactant was 0.96 mg/g. Furthermore, the effects of alkali, salinity and temperature on static adsorption of anionic surfactant were investigated at variable conditions. It was concluded that the anionic surfactant performs better at higher pH, higher temperature and lower salt concentration. An effective control of all these parameters can lead to the situation which helps in minimizing the surfactant loss and improved economic efficiency of CEOR process.

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The fluctuations in the heating value of an underground coal gasification (UCG) process limit its application in electricity generation, where a desired composition of the combustible gases is required to operate gas turbines efficiently. This shortcoming can be addressed by designing a robust control scheme for the process. In the current research work, a model-based, chattering-free sliding mode control (CFSMC) algorithm is developed to maintain a desired heating value trajectory of the syngas mixture. Besides robustness, CFSMC yields reduced chattering due to continuous control law, and the tracking error also converges in finite time. To estimate the unmeasurable states required for the controller synthesis, a state-dependent Kalman filter (SDKF) based on the quasi-linear decomposition of the nonlinear model is employed. The simulation results demonstrate that despite the external disturbance and measurement noise, the control methodology yields good tracking performance. A comparative analysis is also made between CFSMC, a conventional SMC, and an already designed dynamic integral SMC (DISMC), which shows that CFSMC yields 71.2% and 69.9% improvement in the root mean squared tracking error with respect to SMC and DISMC, respectively. Moreover, CFSMC consumes 97% and 23.2% less control energy as compared to SMC and DISMC, respectively.

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