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Initial guess estimation and fast solving of petroleum complex molecular reconstruction model
AIChE Journal ( IF 3.7 ) Pub Date : 2022-05-25 , DOI: 10.1002/aic.17782
Dong Guan 1 , Linzhou Zhang 1
Affiliation  

We proposed a fast method to solve the petroleum molecular reconstruction problem via initial guess estimation coupled with local optimization algorithm. A virtual oil database was constructed. After inputting the bulk properties of the target oil, several virtual oils with similar bulk properties were selected and their model parameters were used as the initial guesses. Subsequently, we proved that by using a local optimization method, the optimal model parameters can be rapidly obtained. The diesel and vacuum gas oil compositional models were exemplified as case studies. The results show that the proposed method presented faster computational time, which is within the range of 20–50 times that of frequently used global algorithms. Moreover, the optimal solution of the proposed method exhibited higher accuracy. In addition, the effect of the number of virtual oils and the parallel computation performance were also investigated.

中文翻译:

石油络合物分子重建模型的初始猜测估计与快速求解

我们提出了一种通过初始猜测估计结合局部优化算法来解决石油分子重建问题的快速方法。建立了虚拟石油数据库。输入目标油的体积特性后,选择几种体积特性相似的虚拟油,并以其模型参数作为初始猜测。随后,我们证明了通过使用局部优化方法,可以快速获得最优模型参数。柴油和真空瓦斯油成分模型作为案例研究进行了举例说明。结果表明,该方法具有更快的计算时间,是常用全局算法的20-50倍。此外,该方法的最优解表现出更高的精度。此外,
更新日期:2022-05-25
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