西南石油大学学报(自然科学版) ›› 2012, Vol. 34 ›› Issue (5): 119-124.

• 石油与天然气工程 • 上一篇    下一篇

欠饱和煤层气藏的生产动态预测方法

胡素明1,李相方2,胡小虎3,任维娜2,尹邦堂2   

  1. 1. 中国石油塔里木油田分公司勘探开发研究院,新疆库尔勒8410002. 中国石油大学(北京)石油工程教育部重点实验室,北京昌平1022493. 中国石化石油勘探开发研究院,北京海淀100083
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2012-10-01 发布日期:2012-10-01

Production Performance Prediction Method for UndersaturatedCBM Reservoirs

Hu Suming1, Li Xiangfang2, Hu Xiaohu3, Ren Weina2, YIN Bangtang2   

  1. 1. Research Institute of Petroleum Exploration and Development,Tarim Oilfield Company,CNPC,Korla,Xinjiang 841000,China2. MOE Key Laboratory of Petroleum Engineering,China University of Petroleum(Beijing),Changping,Beijing 102249,China3. Research Institute of Petroleum Exploration and Development,SINOPEC,Haidian,Beijing 100083,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2012-10-01 Published:2012-10-01

摘要: 将煤层气藏的物质平衡方程和产能方程相结合可建立生产动态预测方法,但目前人们没有考虑原始煤层的吸
附饱和度,所建立的动态储量评价和生产动态预测方法仅适用于饱和或超饱和的煤层气藏。在考虑吸附饱和度的基
础上重新推导物质平衡方程,然后建立了生产动态预测方法,使得该法可用于欠饱和的煤层气藏。通过验证表明,当
煤层气井处于排水降压期时,该法预测的日产水量平均相对误差为8%,当煤层气井进入产气期时,该法预测的日产气
量平均误差为–13%,基本满足工程应用的精度要求。

关键词: 煤层气, 物质平衡, 生产动态, 产量, 预测

Abstract:

The prediction method for CBM reservoir production performance could be developed by combining the material
balance equation and productivity equation. When this method was developed by previous researchers,the initial adsorbing
saturation of CBM reservoir is neglected,making the previous method applicable to only the saturated or supersaturated CBM
reservoir. In this paper,the material balance equation is re-derived by taking initial adsorbing saturation into consideration,
and then the production predicting method was established,applicable to under-statured CBM reservoir. It is demonstrated
that during water drainage period,this method can predict water rate with an average relative error of 8%,and then during
gas production period,it can predict gas rate with an error of –13%,which can meet the accuracy requirement of production
engineering.

Key words: coalbed methane, material balance, production performance, production rate, prediction