油气藏评价与开发 ›› 2020, Vol. 10 ›› Issue (4): 107-112.doi: 10.13809/j.cnki.cn32-1825/te.2020.04.017

• 常规油气 • 上一篇    下一篇

基于交替条件期望变换的凝析气藏露点压力预测模型

孙博文1(),郭平1(),伍轶鸣2,汪周华1,周代余2,刘志良2   

  1. 1.西南石油大学油气藏地质及开发工程国家重点实验室,四川 成都 610500
    2.中国石油塔里木油田分公司勘探开发研究院,新疆 库尔勒 841000
  • 收稿日期:2019-05-13 出版日期:2020-08-26 发布日期:2020-08-07
  • 通讯作者: 郭平 E-mail:178558944@qq.com;guopingswpi@vip.sina.com
  • 作者简介:孙博文(1990 —),男,在读博士研究生,主要从事油气相态、气田开发理论与方法研究工作。通讯地址:四川省成都市新都区新都大道8号油气藏地质及开发工程国家重点实验室,邮政编码:610500。E-mail: 178558944@qq.com
  • 基金资助:
    “十三五”国家科技重大专项“塔里木盆地碳酸盐岩油气田提高采收率关键技术示范工程”(2016ZX05053);中国石油天然气股份有限公司重大科技专项“塔里木盆地大油气田增储上产关键技术研究与应用”(2018E-1804)

Dew point pressure prediction model of condensate gas reservoir based on alternating conditional expectation transform

SUN Bowen1(),GUO Ping1(),WU Yiming2,WANG Zhouhua1,ZHOU Daiyu2,LIU Zhiliang2   

  1. 1.State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, Sichuan 610500, China
    2. Research Institute of Exploration and Development, PetroChina Tarim Oilfield Company, Korla, Xinjiang 841000, China
  • Received:2019-05-13 Online:2020-08-26 Published:2020-08-07
  • Contact: GUO Ping E-mail:178558944@qq.com;guopingswpi@vip.sina.com

摘要:

凝析气藏的高效开发需要准确的流体相态性质数据,其中准确预测露点压力是凝析气藏开发过程中的重要问题。针对凝析气藏露点压力传统预测方法精度较低的问题,基于最优化理论和应用统计分析,通过实测数据资料拟合,提出了一种利用交替条件期望变换方法(ACE)确定的凝析气藏露点压力非参数回归模型,获取了具有统计意义的凝析气藏露点压力显式关联式。在皮尔逊(Pearson)关联性分析基础上,该模型自变量选取气藏温度、(C1、C2-C6、C7+)摩尔分数、C7+相对分子质量、C7+相对密度。采用公开发表的27组露点压力数据探索自变量和因变量之间的潜在函数关系,并对9组TLM油田实测露点压力数据进行预测。结果表明:该模型精度较高,具有良好的泛化能力,模型回归的平均绝对相对误差(AARD)为2.16 %,模型预测AARD仅为4.8 %,其中最大绝对相对误差(ARD)为9.21 %,最小ARD为0.34 %,本研究为凝析气藏露点压力预测提供了一种参考方法。

关键词: 交替条件期望变换, 凝析气藏, 露点压力, 预测, 模型

Abstract:

The efficient development of condensate gas reservoirs requires accurate fluid phase properties data, among which accurate prediction of dew point pressure is an important issue in the development of condensate gas reservoirs. In order to solve the problem of low accuracy of traditional prediction methods for dew point pressure of condensate gas reservoirs, based on optimization theory and applied statistical analysis, and by fitting measured data, a non-parametric regression model determined by alternating conditional expectation transformation(ACE) is proposed, and an explicit correlation of dew point pressure with statistical significance is obtained. Based on Pearson correlation analysis, the independent variables of the model are gas reservoir temperature, mole fraction of (C1, C2-C6, C7+), and molecular weight and relative density of C7+. The potential function relation between independent and dependent variables is analyzed by 27 sets of experimental data for published dew point pressure, and 9 groups of measured dew point pressure data of TLM oilfields are predicted. The results show that the model has high precision and good generalization ability. The average absolute relative deviation(AARD) of model regression is 2.16 %, and the predicted AARD is only 4.8 %. The maximum absolute relative deviation(ARD) is 9.21 % and the minimum is 0.34 %. This study provides a reference method for dew point pressure prediction of condensate gas reservoirs.

Key words: alternating conditional expectation, condensate gas reservoir, dew point pressure, prediction, model

中图分类号: 

  • TE319