Single Well Casing Loss Prediction Method Based on Machine Learning

The role of single-well casing loss prediction in the normal production of oilfield is very important, but there is the problem of inaccurate prediction of results. The neural network cannot solve the problem of single well casing loss prediction in the normal production of oilfield, and the prediction is unreasonable. Therefore, this paper proposes a machine learning method for single-well casing loss prediction analysis. Firstly, the prediction theory is used to predict the casing loss of a single well, and the index is divided according to the prediction requirements of the casing loss of a single well to reduce it Interference factors in single well casing loss prediction. Then, the prediction theory predicts the casing loss of a single well, forms a single well casing loss prediction scheme, and predicts the result of the casing loss of a single well Conduct a comprehensive analysis. «The American Economic Review» shows that machine learning pairs under certain prediction criteria The prediction accuracy of single well casing loss and the prediction time of single well casing loss are better than that of neural network.