Research on oil-water two-phase water content detection model based on near-infrared spectroscopy

Abstract

Crude oil water content is an important technical indicator in oil extraction, transportation and oil trading. Real-time online testing of crude oil water content is extremely important in estimating crude oil production and evaluating the extraction value of oil wells. At present, most of the wells at home and abroad are in the middle and late stage of development, it is difficult and inaccurate to measure under the high-water content condition of crude oil, so it is necessary to adopt new detection means to improve the detection accuracy. In this paper, a study on the method of water content measurement using infrared spectroscopy was carried out. This study used S-G smoothing and normalization as the method of data pre-processing, selected the characteristic wavelengths using the continuous projection method (SPA) with a root mean square error of 4.4702, and then used partial least squares (PLS) to establish a water content detection model, and obtained a prediction root mean square error of 9.7131 and a correlation coefficient of 0.98527, which obtained a good accuracy. The feasibility of using spectroscopic detection technology to measure the water content of crude oil was demonstrated, providing a new method for oil extraction exploration and production processing.