摘要
原油含水率是油田开发状况的重要参数指标。由于原油含水率的测量受到多种因素的影响,且与其影响因素具有复杂的非线性关系,测量精度很难取得令人满意的效果。采用BP神经网络对原油含水率的测量数据进行处理,建立了原油含水率预测模型,使原油含水率的测量精度得到了改善。
The water content of crude oil in the production of crude oil is an important parameters.As crude oil water measurement affected by many factors,and their impact on the element of the complex nonlinear relationship,it＇s very difficult to achieve an accuracy and satisfactory results.In this paper,the measurement data of crude oil procesed, by BP neural network,a moisture content of crude oil model is forecasted,so that the moisture content of crude measurement accuracy has improved.
出处
《石油化工应用》
CAS
2009年第4期35-37,共3页
Petrochemical Industry Application
关键词
BP神经网络
原油
含水率
BP neural network
crude oil
water content
