It is of importance to monitor the production status of oil wells. Nowadays, more and more oilfields use chromatographic fingerprint to monitor Single zone productivity contribution. However how to select chromatographic fingerprint is still a problem, the current selection of chromatographic fingerprint relies on professional experts, which leads to a certain degree of subjectivity. So far, to our knowledge no research was done on the choice of chromatographic fingerprints. In order to analyze chromatographic fingerprint, principal component analysis (PCA), linear correlation method and variable importance in random forest are used in this paper. Then, a joint feature selection method, which combines two methods, is proposed. Experimental results with oil from an oil field of South China Sea show that the proposed method achieves very good results.
