Natural gas plant operations contribute hugely to the economies of many developed nations that depend on hydrocarbon resources. The plant operation is usually subjected to continuous variations in upstream conditions, such as flow rate, composition, temperature and pressure, which propagate through the plant and affect its stable operations. As a result, decision making for optimal operating conditions of an in-operation plant is a complex problem and it is exacerbated with the changing product specifications and variations in energy supplies. This work presents a new solution method to the problem, which is based on chance constrained optimization. A deterministic model is initially developed from process simulation using Aspen HYSYS and later converted to a chance constrained model. The probabilistic model is then relaxed to its equivalent deterministic form and solved for optimum solution using GAMS. The optimum solution is determined probabilistically using chance constraints that are held at a user-defined confidence level. Optimal solution is represented graphically as a trade-off between reliability of holding the process constraints and profitability of the plant. Two case studies are presented to demonstrate the new method. Optimization results show that uncertainty of plant parameters significantly affect the economic performance of the plant operation. The solution approach developed in this work is able to increase the reliability of maintaining the profit by more than 95% confidence level. As a result, the risk of constraints violation is reduced from more than 50% using the typical deterministic optimization to less than 5% with the developed chance constrained optimization model. In addition, the results from this study indicate that the variation of material flow from the plant inlet has greater impact by more than 86% on profit change compared to variation from the plant outlet, which is less than 2%. Sensitivity analysis results show on how to reduce the effect of N2, CO2 and C5+ by holding the corresponding constraint at a certain confidence level. The developed solution method can aid as guidelines to flexible plant operation decision making for the in-operating plant by satisfying all the process constraints at certain confidence level.
The present study describes elaborately the isolation of a potential biosurfactant producing and crude oil degrading (1-5%) strains isolated from the Assam oil reservoir field. The produced biosurfactant was chemically characterized for its applicability for the enhanced oil recovery applications in terms of wetting, interfacial tension (IFT) and oil washing. From the seven isolated strains, Bacillus tequilensis MK 729017 was chosen based on the better surface active properties as it reduced the surface tension to 30 ± 2 mN/m along with a moderate emulsification index of 66 ± 2 %. The produced biosurfactant was chemically identified to be lipopeptide, surfactin with a lower critical micelle concentration value of 90 mg/L. The carbon source and environmental parameters were optimized for the maximum concentration of the biosurfactant using RSM-CCD. The maximum biosurfactant concentration was measured to be 7.46 ± 0.39 g/L and Y_PS was determined as 0.45. The specific growth rate of the isolate was 0.15 ± 0.01 h-1 and Y_XS was estimated as 0.1. The produced biosurfactant was also found to be thermal and colloidal stable. The biosurfactant solutions altered wettability of hydrophobic rock surface from 90 ± 1o to 26 ± 1o indicating a better interfacial interaction. The IFT of the produced biosurfactant was found to be 0.32 ± 0.02 mN/m. The oil washing efficiency (80 ± 2 %) of the produced surfactin was comparable with chemical surfactants and the process involved two-steps: initial a faster (surface) washing followed by a slower (internal) washing. The first process was dependent on micelle sizes, while the later was dependent on water-oil emulsion size. The lower emulsion size of surfactin contributed to a greater internal washing as compared to chemical surfactants. These observations endorse the potential of the isolated strain towards biosurfactant production and its application in microbial enhanced oil recovery process.
Biomolecules are the building block of life. Cell which is known as the building of body is made up of these biomolecules. These biomolecules are further made up of inorganic compounds. C, H, N, O is the four major inorganic compounds which make the 94% of the cell. S, P makes 3% of the cell. Biomolecules also called as biological molecule, which are produced by cells and living organisms. The four major types of biomolecules are carbohydrates, lipids, nucleic acids, and proteins.
