In order to improve measurement accuracy and widen measurement range for water content in crude oil, a computation method based on the electrical measurement of multiple modes was proposed in this paper.

This paper measured some parameters that affect the measurement of the water content of crude oil at wellhead metering device using the multi-sensor technology and processed these parameters using the K-means clustering,then the prediction models for water content in crude oil based on the methods of BP neural network and CPN networks are presented.

In conventional demulsifier used in the field,dewatering in crude oil is slow,water content of crude oil and oil content in sewage a.

It is hard to measure the water content of crude oil precisely because the dielectric constant of crude oil varies greatly when displacing agent and emulsion breaker are injected.

Application of soft sensor based on SVM on estimation of water cut of crude oil;

According to the research on the measuring method of water cut of crude oil,as well as the nonlinear mapping relationship between the water cut of crude oil and the affecting factor,this paper brought up a forecasting model of water cut of crude oil based on wavelet decomposition and neural network.

Additionally, electric dehydration, oil cut of waste water and suspended solid content were also tested.