Abstract
The abnormality of gas well annulus pressure is one of the main risks that threaten the safety of gas wells and affect their production efficiency. In order to further improve the level of Gas Well Annulus Pressure management, this study introduced the time sequence prediction method. Through the design of multiple variable gray prediction algorithms and neural network prediction algorithm design, the effectiveness of the model was verified by the comparison of the prediction results and the actual measurement data. The research results verify the feasibility of the time sequence predictive algorithm on the dynamic prediction of the gas well annulus pressure, which provides theoretical support for the early diagnosis and active prevention of the gas well annulus pressure.
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