Classification of Oil-Gas-Water Three-Phase Flow in a Pipeline Based on BP Neural Network Analysis ()
ABSTRACT
The flow
pattern in a pipeline is a very important topic in petroleum exploitation. This
paper is to classify the flow pattern of oil-gas-water flow in a pipeline by using BP neural network. The effects of different
parameter combinations are investigated to find the most important ones. It is shown that BP neural
network can be used in the analysis of the flow pattern of three-phase flow in pipelines. In most cases, the mean square error
is large for the horizontal pipes. The optimized neuron number of the middle layer changes with conditions. So, we must changes the neuron number of the middle
layer in simulation for any
conditions to seek the best results. These conclusions can be taken as references for further study of the flow pattern of oil-gas-water in a pipeline.
Share and Cite:
Lu, W. , Li, P. and Zhang, X. (2022) Classification of Oil-Gas-Water Three-Phase Flow in a Pipeline Based on BP Neural Network Analysis.
Journal of Data Analysis and Information Processing,
10, 185-197. doi:
10.4236/jdaip.2022.104012.
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