2021
DOI: 10.1016/j.petrol.2021.109103
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An effective procedure for wax formation modeling using multi-solid approach and PC-SAFT EOS for petroleum fluids with PNA characterization

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Cited by 5 publications
(1 citation statement)
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“…Sulaimon and Falade developed a two-phase multicomponent thermodynamic model based on continuous thermodynamic phase equilibrium, used a three-parameter gamma distribution function to predict WAT and wax precipitation, and proposed a generalized three-phase multicomponent thermodynamic model (EOS) based on regular solution theory. Assareh et al , distinguished crude oil fractions by paraffins, naphthenes, and aromatics, and developed a prediction model for WAT and wax precipitation using the perturbed chain statistical associative fluid theory (PC-SAFT) equation of state, adjusting the binary interaction coefficients and heat capacity differences between solids and liquids to minimize the bias due to the use of averaging relations for hydrocarbon cutting properties, which is a considerable improvement compared with previous models. With the rapid development of intelligent algorithms, artificial neural networks can be used as an effective means to simulate complex systems in the petroleum field.…”
Section: Wax: Structures and Thermodynamic And Phase Behaviorsmentioning
confidence: 99%
“…Sulaimon and Falade developed a two-phase multicomponent thermodynamic model based on continuous thermodynamic phase equilibrium, used a three-parameter gamma distribution function to predict WAT and wax precipitation, and proposed a generalized three-phase multicomponent thermodynamic model (EOS) based on regular solution theory. Assareh et al , distinguished crude oil fractions by paraffins, naphthenes, and aromatics, and developed a prediction model for WAT and wax precipitation using the perturbed chain statistical associative fluid theory (PC-SAFT) equation of state, adjusting the binary interaction coefficients and heat capacity differences between solids and liquids to minimize the bias due to the use of averaging relations for hydrocarbon cutting properties, which is a considerable improvement compared with previous models. With the rapid development of intelligent algorithms, artificial neural networks can be used as an effective means to simulate complex systems in the petroleum field.…”
Section: Wax: Structures and Thermodynamic And Phase Behaviorsmentioning
confidence: 99%