摘要
针对非常规气井产量递减与EUR(预测最终采收率)结果差别大、准确率不高的问题,对Wattenbarger线性流法、PLE幂指数递减模型法、SEPD扩展指数递减模型法等各种方法的理论基础和优缺点进行对比分析,评价各种方法的使用对象、所需数据和适用条件。同时,通过对PLE、SEPD、Duong、LGM 4种模型在线性流阶段和拟边界流阶段的预测结果与数值模拟井的预测结果进行对比,并进行实际应用。结果表明:各种常用的非常规气井产量递减方法均适用于不同的地层流态;Wattenbarger线性流、拟恒定流动压力、水平井多级压裂模型3种方法更适用于变产量、变井底流压的流动状况;PLE和Duong模型在生产时间为2 a内预测比较准确。该研究为非常规气井产量预测提供了借鉴。
In view of the problems of production decline of unconventional gas wells,large differences and low accuracy in the EUR(predicted ultimate recovery factor)results,the theoretical basis and advantages and disadvantages of the various methods such as Wattenbarger linear flow method,PLE power exponential decline model method,and SEPD extended exponential decline model method were compared and analyzed to evaluate the objects of use,required data and applicable conditions of various methods.At the same time,the prediction results of the four models of PLE,SEPD,Duong and LGM in the linear flow stage and the quasi-boundary flow stage were compared with the prediction results of the numerical simulation well,and practical applications were carried out.The research result shows:Various commonly used production decline methods for unconventional gas wells are suitable for different formation flow regimes;Wattenbarger linear flow,quasi-constant flow pressure,and horizontal well multi-stage fracturing model are more suitable for flow conditions with variable production and variable bottom-hole pressure.PLE and Duong models are more accurate for prediction within 2 a.This study provides a reference for production prediction of unconventional gas wells.
作者
崔英敏
郭红霞
陆建峰
杨勇
张金柏
刘伟
靳广兴
赵开良
Cui Yingmin;Guo Hongxia;Lu Jianfeng;Yang Yong;Zhang Jinbai;Liu Wei;Jin Guangxing;Zhao Kailiang(Changqing Industrial Group Co.,Ltd.,Xi'an,Shaanxi 710018;Xi'an Jinjiang Energy Technology Co.,Ltd.,Xi'an,Shaanxi 710018)
出处
《特种油气藏》
CAS
CSCD
北大核心
2022年第6期119-126,共8页
Special Oil & Gas Reservoirs
基金
国家“十三五”重大科技攻关项目“页岩气开发规模预测及开发模式研究”(2016ZX05037-006)。
关键词
非常规气井
产量递减
EUR预测方法
页岩气
unconventional gas well
production decline
EUR prediction method
shale gas