期刊文献+

低压低产页岩气井智能生产优化方法 被引量:2

Intelligent production optimization method for a low pressure and low productivity shale gas well
下载PDF
导出
摘要 针对页岩气井在生产后期因积液和地层压力不足影响产量的问题,提出一种适用于低压低产页岩气井的智能生产优化方法,以人工智能算法为中心,实现气井的自动生产和运行监测。智能生产优化方法基于长短期记忆神经网络预测单井产量变化,指导气井生产,实现积液预警和自动间歇生产等功能,配合可调式油嘴实现气井控压稳产,延长页岩气井正常生产时间,提高井场自动化水平,实现“一井一策”的精细化生产管理模式。现场试验结果显示,优化后的单井最终可采储量可提高15%。相较于衰竭式开发后立刻采用排采工艺的开发模式,该方法更具有经济性,且增产稳产效果显著,具有较好的应用前景。 Shale gas wells frequently suffer from liquid loading and insufficient formation pressure in the late stage of production.To address this issue,an intelligent production optimization method for low pressure and low productivity shale gas well is proposed.Based on the artificial intelligence algorithms,this method realizes automatic production and monitoring of gas well.The method can forecast the production performance of a single well by using the long short-term memory neural network and then guide gas well production accordingly,to fulfill liquid loading warning and automatic intermittent production.Combined with adjustable nozzle,the method can keep production and pressure of gas wells stable automatically,extend normal production time of shale gas wells,enhance automatic level of well sites,and reach the goal of refined production management by making production regime for each well.Field tests show that wells with production regime optimized by this method increased 15%in estimated ultimate reserve(EUR).Compared with the development mode of drainage after depletion recovery,this method is more economical and can increase and stabilize production effectively,so it has a bright application prospect.
作者 祝启康 林伯韬 杨光 王俐佳 陈满 ZHU Qikang;LIN Botao;YANG Guang;WANG Lijia;CHEN Man(College of Artificial Intelligence,China University of Petroleum,Beijing 102249,China;College of Safety and Ocean Engineering,China University of Petroleum,Beijing 102249,China;College of Information Science and Engineering,China University of Petroleum,Beijing 102249,China;Sichuan Shale Gas Exploration and Development Co.LTD,Neijiang 641100,China;China National Petroleum Corporation Southwest Oil and Gas Field Company Sichuan Changning Natural Gas Development Co.Ltd,Changning 644000,China)
出处 《石油勘探与开发》 SCIE EI CAS CSCD 北大核心 2022年第4期770-777,共8页 Petroleum Exploration and Development
基金 国家科技重大专项“大型油气田及煤层气开发”课题4“页岩气排采工艺技术与应用”(2017ZX05037-004)
关键词 页岩气 低压低产气井 生产优化 人工智能 长短期记忆神经网络 可调式油嘴 shale gas low pressure and low productivity gas well production optimization artificial intelligence long short-term memory neural network adjustable nozzle
  • 相关文献

参考文献11

二级参考文献146

共引文献399

同被引文献24

引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部