基于PatchTST模型的天然气井间歇生产产量预测OA

To solve the problem of large fluctuation and difficult prediction of the yield of intermittent shale gas production wells,based on the production situation of Fuling shale gas field,the production of intermittent production wells is predicted using PatchTST model.This model is based on Transformer encoder to model time series,by segmenting them into multiple segments and processing each seg-ment with Transformer modules,thus capturing the dependency relationships between time series.At the same time,the accuracy of model prediction can be improved by introducing production factors that are related to output and have time series,such as oil pressure and casing pressure.The application result on the test set shows that the PatchTST model has an average prediction error of only 2 496.61 m3 per hour,indicating that it can well capture the production variation pattern of intermittent production wells.The compara-tive experiment with LSTM model proves the superiority of PatchTST model in long sequence yield prediction.This study provides a ref-erence for the application of large models in predicting natural gas well production.