Abstract
Summary
Equilibrium ratios play a fundamental role in the understanding of phase behavior of hydrocarbon mixtures. They are important in predicting compositional changes under varying temperature and pressure in reservoirs, surface separators, and production and transportation facilities. In particular, they are critical for reliable and successful compositional reservoir simulation. This paper presents a new approach for predicting K values with neural networks (NN's). The method is applied to binary and multicomponent mixtures, and K-value prediction accuracy is on the order of the traditional methods. However, computing speed is significantly faster.
Publisher
Society of Petroleum Engineers (SPE)
Subject
Process Chemistry and Technology
Cited by
13 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献