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

Ying Ming Zhou; Qiu Shi Wang; Peng Wang; Li Na Yao

doi:10.4028/www.scientific.net/AMM.170-173.1290

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 170-173Moisture Content of Crude Oil Based on BP Neural...

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

Abstract:

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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Periodical:

Applied Mechanics and Materials (Volumes 170-173)

Pages:

1290-1293

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.170-173.1290

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Online since:

May 2012

Authors:

Ying Ming Zhou, Qiu Shi Wang, Peng Wang, Li Na Yao

Keywords:

BP Neural Network (BPNN), Moisture Content, Predict

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