scholarly journals Error Correction Method of Crude Oil Moisture Content Detection Based on BP Neural Network

2020 ◽  
Vol 558 ◽  
pp. 022005
Author(s):  
Pengmin Dong ◽  
Xianghu Zeng ◽  
Chengcai Duan ◽  
Tianqi Wang ◽  
Shichong Luo ◽  
...  
Keyword(s):  
Neural Network ◽  
Moisture Content ◽  
Crude Oil ◽  
Error Correction ◽  
Bp Neural Network ◽  
Correction Method ◽  
Error Correction Method

An Application of BP Neural Network Model to Predict the Moisture Content of Crude Oil

2012 ◽  
Vol 524-527 ◽  
pp. 1327-1330 ◽  
Author(s):  
Ying Ming Zhou ◽  
Shu Wei Wang ◽  
Lin Lin
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Moisture Content ◽  
Crude Oil ◽  
Heavy Oil ◽  
Bp Neural Network ◽  
Prediction Error ◽  
Neural Network Prediction ◽  
Network Prediction ◽  
Bp Neural Network Model

With the constant expansion of super heavy oil SAGD conversion development, the accurate testing of the crude oil in the high moisture content range is particularly important. In this paper, against the characteristics of Adopting SAGD technology exploiting heavy oil, BP neural network prediction model and calculation method has been adopted to predict the moisture content of crude oil. Through the study, the experimental data of the model were verified by the maximum prediction error is less than 3%, the accuracy of the forecast moisture content of crude oil to meet the site requirements. Through this study, the experimental data to the model was validated by the maximum prediction error is less than3%, the prediction accuracy of which to moisture content of crude oil is able to meet the requirements of the project site.

Moisture Content of Crude Oil Based on BP Neural Network Algorithm to Predict in Oilfield

2012 ◽  
Vol 170-173 ◽  
pp. 1290-1293 ◽  
Author(s):  
Ying Ming Zhou ◽  
Qiu Shi Wang ◽  
Peng Wang ◽  
Li Na Yao
Keyword(s):  
Neural Network ◽  
Moisture Content ◽  
Crude Oil ◽  
Neural Network Model ◽  
Bp Neural Network ◽  
Implementation Process ◽  
Evaluation Index ◽  
Precision Control ◽  
Neural Network Algorithm ◽  
Bp Neural Network Model

This paper proposed new method of testing a moisture content of the crude oil which is based on BP neural network. It describes the principle of BP neural network model and calculation method to predict the moisture content of crude oil. The normalization of evaluation index and the implementation process of this method in computers. In the end, an application example of this method used in the process of practice and precision control requirements.

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