石油化工安全环保技术 ›› 2024, Vol. 40 ›› Issue (2): 39-42.

• 清洁生产与综合治理 • 上一篇    下一篇

基于智能分析的油水井生产预警技术研究

朱元伟   

  1. 西安石油大学,陕西 西安710065
  • 收稿日期:2024-03-19 接受日期:2024-03-15 出版日期:2024-04-20 发布日期:2024-04-24
  • 作者简介:朱元伟,男,西安石油大学石油工程学院资源与环境专业在读研究生。

Research on Oil and Water Well Production Early Warning Technology Based on Intelligent Analysis

Zhu Yuanwei   

  1. Xi’an Shiyou University,Xi’an,Shaaxi,710065
  • Received:2024-03-19 Accepted:2024-03-15 Online:2024-04-20 Published:2024-04-24

摘要: 利用油水井勘探开发过程中的海量数据,分析并识别出生产异常的油水井,对异常变化深入查探,据此提出针对性措施,对维持油田稳定开采、产量高效保持,实现最大化生产效益具有重要意义。通过大数据分析与神经网络预测方法,利用措施数据库进行机器学习、训练模型,建立不同增产措施的神经网络模型,形成基于静态油藏数据、动态生产数据和措施方案参数的增产效果预测评价系统。

关键词: 油水井生产, 生产预警, 智能分析, 措施效果评价, 神经网络, 大数据

Abstract: Utilize the massive data in the oil and water well exploration and development process to analyze and identify oil and water wells with abnormal production, conduct in-depth exploration of abnormal changes, and propose targeted measures based on this to maintain stable oil field exploitation, efficient production, and maximize production benefits. of great significance. This paper uses big data analysis and neural network prediction methods, uses the measure database to perform machine learning and model training, and establishes neural network models for different production stimulation measures to form a production stimulation effect prediction and evaluation system based on static reservoir data, dynamic production data and measure plan parameters.

Key words: oil and water well production, production early warning, intelligent analysis, measure effect evaluation, neural network, big data