Accurately and timely measuring water content of the crude oil is of great significance for water injection strategy adjustment, crude oil exploitation capacity assessment, and oil well development lift prediction. However, at present, most of China’s oil fields have entered the mid- or late- development stage with high water content. And the corresponding water content is difficult to measure accurately. Under this circumstance, this paper carried out research on the measurement of water content of the crude oil using near-infrared spectroscopy. Specifically, commonly employed methods for measuring water content of the crude oil were introduced, and advantages and disadvantages of these methods were analyzed. Theoretically, since the near-infrared absorption band of water is significantly different from the absorption of C—H bond in crude oil, according to Lambert-Beer’s law of absorption and linear law of absorbance, there is a strong response difference in the near-infrared spectrum of high water cut crude oil with different water content. Therefore, we proposed to use near-infrared spectroscopy to accurately measure the crude oil with high water content. And then, by analyzing the measured near-infrared spectrum, non-linear mapping between the water content of the testing crude oil and the near-infrared spectrum can be established. With the obtained non-linear mapping model, water content of the crude oil can be accurately calculated. In order to evaluate the performance of this method, we constructed a hardware platform for collecting near-infrared data. In this platform, Incandescent lamp was employed as a light source, and near-infrared spectrometer (Ocean Optics NIR512) was used to collect near-infrared in range 900～1 700 nm with 512 uniformly divided sub bands. The collected data were stored in the computer using the spectrometer supporting software. With the obtained near-infrared data, the raw data preprocessing was performed to reduce the influence of temperature and high frequency random noise, sample unevenness, baseline drift, light scattering, and et al. In this paper, S-G filtering, or first order derivative, or S-G filtering+first order derivative techniques were employed as the preprocessing method; Successive Projection Algorithm (SPA) was used to reduce the dimension of the raw data; Partial Least Square (PLS) and Multiple Linear regression (MLR) were employed to construct the corresponding non-linear mapping model; Root Mean Square Error (RMSE) and Correlation coefficient (R) were used to evaluate the quantitative measuring performance. Experimental results illustrated that: model constructed using S-G filtering+first order derivative as preprocessing method can achieve the best RMSE (RMSE=0.007 0, r=0.998 3); Model constructed with reduced dimensional data using SPA method is better than the one (RMSE=0.083 3, r=0.920 6) constructed by PLS with full band data and the one (RMSE=0.099 9, r=0.967 1) constructed by MLR with full band. Obviously, although the 31 dimensionality-reduced feature bands obtained by SPA method are only 6.05% of the full band data, the corresponding water content measuring accuracy of the crude oil is very promising. In general, we validate the feasibility of using spectroscopy technique to measure water content of the high water content crude oil, and satisfactory accuracy can be achieved. Therefore, it can be said that this paper provides a new method for water content measurement of high water content crude oil, and provides reference for accurately and timely measuring high water content crude oil using near-infrared spectroscopy.