(343b) Optimization Based Modeling and Analysis of Osmotically Assisted Reverse Osmosis for Application in Shale Oil and Gas Produced Water Treatment

Substantial amount of water is required for hydraulic fracturing and large volume of water, known as produced water, with relatively high total dissolved solids (TDS), is produced during unconventional oil and gas production. Being costly and difficult to treat, hypersaline brines could contaminate surface freshwater resources and ground water reservoirs. Desalination technologies offer a promising way to treat the produced water and provide pure water. Having higher energy efficiency in comparison to thermally driven desalination processes, reverse osmosis (RO) is one of the most widespread desalination technologies worldwide. RO is a pressure driven separation process utilizing hydraulic pressure to force the solvent to move through a semipermeable membrane from higher solute concentration to lower concentration. However, RO is incapable of treating hypersaline produced water with high osmotic pressure, since the applied hydraulic pressure is limited by the maximum pressure that RO membranes could withstand. Osmotically assisted reverse osmosis (OARO) systems are emerging RO configurations that enable the pressure driven membranes to treat hypersaline solutions. OARO overcomes the problem of excessive hydraulic pressures by introducing a saline solution stream on the low-pressure side of the membrane leading to reduction in transmembrane osmotic pressure difference.

Systematic design and optimization of the OARO technology and operating conditions is required to assess the energetic and economic feasibility of this technology for produced water treatment. This work presents module scale optimization-based modeling and analysis of several OARO configurations. Specifically, brine-reflux OARO (BR-OARO), cascading osmotically mediated reverse osmosis (COMRO), consecutive loop OARO, and split feed counterflow RO configurations are modeled and studied in detail. The BR-OARO configuration is found to be superior to other configurations in terms of stage count, treatment cost, membrane area, and energy consumption. Additionally, sensitivity analysis is performed to determine the effect of input parameters such as feed salinity and pressure on the performance of each configuration.