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Process system analysis on oil processing facility and economic viability from oil well-to-tank

kazmi Bilal, Taqvi Syed Ali Ammar, Naqvi Muhammad Raza, Ilyas Suhaib Umer, Moshin Ali, Inamullah Farah, Naqvi Salman R.

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Year 2021
Type of Item Peer-Reviewed Journal Publication
Bibliographic Citation B. kazmi, S. A. A. Taqvi, M. Naqvi, S. U. Ilyas, A. Moshin, F. Inamullah and S. R. Naqvi, “Process system analysis on oil processing facility and economic viability from oil well-to-tank,” SN Appl. Sci., vol. 3, no. 7, June 2021, doi: 10.1007/s42452-021-04635-z.
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Hydrocarbon processing from extraction to the final product is an important aspect that needs an optimised technology for consumption-led market growth. This study investigated real data from the oil processing facility and analysed the simulation model for the entire crude oil processing unit based on the process system engineering aspect using Aspen HYSYS. The study mainly emphasises the process optimisation in processing the hydrocarbon for the maximum yield of the product with less energy consumption. The investigation also includes a thorough economic analysis of the processing facility. The datasets for oil properties are obtained from a modern petroleum refinery. The investigation comprises of varying transient conditions, such as well shutdowns using three oil reservoirs (low, intermediate, and heavy oil). The impact of various conditions, including process heating, well shutdown, oil combinations, presence of water on the production, is analysed. The results indicate that the factors involving crude oil processing are significantly affected by the process conditions, such as pressure, volume, and temperature. The vapour recovery unit is integrated with the oil processing model to recover the separator's gas. The optimisation analysis is performed to maximise the liquid recovery with Reid vapour pressure of 7 and minimum water content in oil around 0.5%. Economic analysis provided an overall capital cost of $ 9.7 × 106 and an operating cost of $2.1 × 106 for the process configuration. The model results further investigate the constraints that maximise the overall energy consumption of the process and reduce the operational cost.

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