The spectral analysis method of oilwater mixture has become a research hotspot of current oilwater twophase flow measurement. However, in traditional oilwater mixture spectral analysis, the spectral feature extraction is generally achieved with the dimensionality reduction techniques, such as principal component analysis, successive projection algorithm and etc. The number of extracted spectra is mostly more than 10, which makes the oilwater two phase measurement fiber optic sensor expensive to manufacture and difficult to implement. In order to improve the practicability of the oilwater twophase measurement fiberoptic sensor based on spectral analysis, it is necessary to realize the ultrasparse representation of the oilwater twophase infrared spectrum. In order to achieve this goal, a spectral ultrasparse representation method with oilwater mixture spectral selfcross correlation (SCC) is proposed. In order to verify the effectiveness of the method, an experiment device for measuring the water content of oilwater mixture using infrared spectrum technique was established. From the 6 bands selected with the SCC algorithm, the bands of 1 050 nm and 1 650 nm were selected according to actual production process, and the dynamic experiments were carried out. The experiment results show that bands of 1 050 nm and 1 650 nm respond well to the mixed flow pattern of oil and water, and the two bands exhibit significant crosscorrelation. Obviously, this study will help improve the service performance of industrial fiberoptic sensors.