Prediction of Gas Well Annulus Pressure Based on Neural Network

Authors

  • Man Pu
  • Jialong Xie
  • Miaomiao Cheng
  • Xin Yi

DOI:

https://doi.org/10.54097/ajst.v3i3.2825

Keywords:

Production safety, Annulus pressure, Grey system theory, Multivariate grey model.

Abstract

Abnormal pressure in the annulus is one of the main risks that threaten the safe production of gas wells and affect their production efficiency. To further improve the gas well annulus pressure management level based on the gray system theory and new information priority ideology, this study introduced a new perspective. First, we considered the influence of various factors related to the change of the gas well annulus pressure and performed a grey correlation analysis. Next, we established a multivariable grey prediction model of gas well annular pressure with the associated metabolic function. The measured data of high-pressure and high-yield gas wells in Northwestern Sichuan for 12 consecutive hours in a day, was used as a case study. The effectiveness of this proposed model was verified by comparing the predicted results with the measured data. The research results verify the feasibility of the gray system theory for the dynamic prediction of gas well annulus pressure and provide theoretical support for the early diagnosis and active prevention of continuous annulus pressure.

References

Zhu Dajiang. Study on Annular Pressure Mechanism of Gas Wells [D]. Southwest Petroleum University, 2014.

Zhang Ke. Research on Matrix Grey Correlation Analysis Modeling Technology [D]. Nanjing University of Aeronautics and Astronautics, 2010.

Deng Ju-Long.Control problems of grey systems[J].Systems and Control Letters,1982,Vol.1: 288-294.

Su Bianping, Cao Yanping, Wang Ting. Grey prediction model of multi factor time series [J]. Journal of Xi'an University of Architecture and Technology (Natural Science Edition), 2007, Volume 39 (2): 289-292.

Chen Xiangdong, Wang Bin. Multi factor Grey Prediction Model and Its Application [J]. Mathematical Practice and Understanding, 2012, (1): 80-83.

Liu Sifeng, Guo Tianbang. Grey system theory and its application [M]. Kaifeng: Henan University Press, 1991.

Zeng Bo, Yin Xiaoyong, Meng Wei. Practical Grey Prediction Modeling Method and Its MATLAB Program Implementation [M]. Beijing: Science Press, 2018.

Liu Sifeng, et al. Grey System Theory and Its Application 8th Edition [M]. Beijing: Science Press, 2017.

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Published

16 November 2022

How to Cite

Pu, M., Xie, J., Cheng, M., & Yi, X. (2022). Prediction of Gas Well Annulus Pressure Based on Neural Network. Academic Journal of Science and Technology, 3(3), 85–88. https://doi.org/10.54097/ajst.v3i3.2825

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Section

Articles