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基于PatchTST模型的天然气井间歇生产产量预测

王铃鑫 党随虎 葛兰

西安石油大学学报(自然科学版)2026,Vol.41Issue(2):74-80,7.
西安石油大学学报(自然科学版)2026,Vol.41Issue(2):74-80,7.DOI:10.3969/j.issn.1673-064X.2026.02.009

基于PatchTST模型的天然气井间歇生产产量预测

Intermittent Production Yield Prediction of Natural Gas Wells Based on PatchTST Model

王铃鑫 1党随虎 2葛兰1

作者信息

  • 1. 中国石化 重庆涪陵页岩气勘探开发有限公司,重庆 408100
  • 2. 长江师范学院 电子信息工程学院,重庆 408100
  • 折叠

摘要

Abstract

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.

关键词

天然气井产量预测/PatchTST模型/间歇生产井/时间序列/页岩气

Key words

natural gas well production prediction/PatchTST model/intermittent production well/time series/shale gas

分类

能源科技

引用本文复制引用

王铃鑫,党随虎,葛兰..基于PatchTST模型的天然气井间歇生产产量预测[J].西安石油大学学报(自然科学版),2026,41(2):74-80,7.

基金项目

在渝高校与中科院所属院所合作项目"智慧气田感知技术研究及创新平台建设"(HZ2021014) (HZ2021014)

西安石油大学学报(自然科学版)

1673-064X

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