Crudeoil production estimation based on chromatographic fingerprinting by using ensemble regression analysis

It is more and more important to oilfield Using chromatographic fingerprint estimation single-zone productivity contribution.However how to effectively build a regression model is still an unsolved problem.Previous researchers have proposed many methods to build the regression model.However all these methods are single regression model.Recently,ensemble regression Model has been obtained a great attention.And generalized additive model is a widely used non-linear regression model.In this paper,a method integrating generalized additive model is proposed.The proposed method establishes relationship between the chromatographic fingerprint and the single-zone productivity contribution.Experimental results show that the proposed method outperforms other methods,and provide an effective way to estimate the single-zone productivity contribution.