Because compressed gas is a scarce and expensive resource, allocating an optimal amount of gas injection to a group of wells to increase the oil production rate is an important optimization problem in the gas lift operation. In this article, a particle swarm optimization algorithm is employed to assign an optimum gas injection rate for each individual well. Also, a new gas lift performance curve-fit that can reduce the time and volume of the computation is suggested. Finally, the algorithm is tested on five wells in an Iranian oil field.

Using captured CO2 as a chemical feedstock is widely considered toward establishing low carbon technologies to mitigate climate change. Process systems engineering analyses can help increase the chances of success by identifying attractive targets at early stages. Here, a comparative techno-economic and environmental analysis of three thermocatalytic CO2-based plants individually producing liquid hydrocarbon transportation fuels (LHTF), methanol, and 1-propanol is introduced. While the 1-propanol plant generates a remarkable profit, the LHTF and methanol plants are not economically viable, mainly due to the CO2 and H2 input cost. Sensitivity analysis shows that the feedstock prices need to drop by 80% for these two plants to break even. A tax structure is not a sensible option since it would be more than 4 times the highest carbon tax currently implemented in the country. In terms of the environmental performance, the CO2 utilization efficiencies are 45.5, 60.1, and −33.8% for LHTF, methanol, and 1-propanol syntheses, respectively. The negative utilization efficiency in the 1-propanol plant highlights the need of a greener production of its raw material ethylene. When the entire life cycles of the products are considered, these emerging plants emit 85.9, 77.4, and 35.9% less CO2 than their conventional counterparts for the same output. Our study provides the first evaluation of CO2-based 1-propanol synthesis, highlighting its potential, underscores gaps in the CO2-based LHTF, methanol, and 1-propanol by comparing them on a uniform common basis, and sets future research directions.

Nitrogen rejection processes are usually needed for two natural gas sources: sub-quality natural gas reserves and produced gas from enhanced oil/gas recovery technologies. The nitrogen content of natural gas in the former is usually constant during the project lifetime, but it varies from 5 to 70% during enhanced oil/gas recovery programs. This variation leads to different process flowsheets for nitrogen removal: single-column, double-column, three-column, and two-column processes. In order to determine which configuration is more suitable for a particular nitrogen content in a feed stream, we must minimize the energy requirement for each process. In this study, we merge all the four configurations into two categories: single-column and multicolumn processes and then use the Particle Swarm Optimization algorithm to optimize process parameters for each process with the objective of energy consumption minimization. Finally, we use the exergy concept to analyze theoretically these different processes.

Helium is regarded as a vital gas to various industries such as medicine, aircraft manufacturing, electronics and fiber optics fabrication. Currently, natural gas reserves are considered the only viable resource for this rare element. When processing (helium-rich) natural gas, helium is generally recovered in the most downstream stage in conjunction with the nitrogen rejection unit (NRU). The feed to this unit is a nitrogen rich stream, and the product is either crude helium (50-70 mol% purity) or purified helium (99.99 mol% purity). Currently, the cryogenic distillation method is a common technology for a crude helium extraction unit (HeXU). The alternative method for this purpose is a membrane gas separation system, which is successfully used in other applications. This study aims to propose an energy-integrated scheme for each of the two helium separation technologies with a single-column NRU and to evaluate and compare them for different applications. Matlab programming has been used to model the membrane system and incorporate it into Aspen Hysys, which is used to simulate the rest of the process flowsheet. Next, the energy consumption of the systems was optimized using the particle swarm optimization method. An economic analysis was adopted to compare the two technologies for different applications in order to suggest a comprehensive map for HeXU technology selection.

Power-to-liquid production via methanol synthesis has a high potential for emission reduction and carbon-neutral fuel production. However, the low equilibrium conversion of methanol synthesis via CO2 hydrogenation is identified as an important impediment in the further development of the technology. The latter necessitates a more innovative reactor design like membrane reactors to enhance the reaction conversion. In this article, a rigorous and customizable model for membrane reactors is developed using an equation-oriented flowsheet approach. The module requires no analytical correlations for thermodynamic properties, which often fail to reflect the system behavior accurately, or simplifying assumptions such as isobaric and isothermal operation conditions. The model was applied to the synthetic methanol production to determine to what extent a conceptual water-selective membrane reactor improves the reaction’s conversion and selectivity. We propose the process conditions at which a membrane reactor enhances these two key metrics, given the module’s heat transfer mode. This conceptual modeling serves as a guiding benchmark for future innovative reactor designs and facilitates the prospective process development and optimization due to the possible exportation and incorporation into the standard flowsheet simulators such as HYSYS or Aspen Plus.