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挥发性原油流体参数校正方法及应用

Correct Method and Application of Fluid Parameters in Volatile Crude Oil
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摘要 原油体积系数、溶解气油比是油气储量评价和油藏工程中十分重要的两个参数。挥发性原油由于中间组分含量较大,室内单次脱气和多次脱气实验测定的挥发性原油体积系数和溶解气油比值和矿场条件下相比均存在偏大的情况。该文通过对比脱气实验过程和数据,分析实验结果存在差异的原因,提出了将脱气实验中损失的井流物中间组分转化为液相的校正方法,并推导了转化公式,通过该方法校正获得的参数消除了中间组分挥发的影响,校正后的体积系数、溶解气油比,更能准确反映油藏流体在矿场生产过程中的实际特征。结果表明,典型黑油实验测得数据可直接用于油藏工程和储量计算,但挥发性原油实验数据必须校正。原油的挥发性越高,校正后体积系数和溶解气油比较实验数据越小,两者计算的地质储量误差达6%~10%。 Volume factor and gas oil ratio are two of the most important parameters in oil reservoir evaluation and engineering.Due to the large intermediate component content of volatile crude oil,volume factor and gas oil ratio measured from single degassing and multiple degassing experiments are larger than those measured under field conditions.This paper compares the processes and data of degassing experiments,and analyses the reasons leading to the differences between experimental results,then proposes a correction method for converting the intermediate components of well fluid lost in degassing experients into liquid phase and builds the conversion formula.The corrected volume factor and gas oil ratio can more accurately reflect the actual characteristics of reservoir fluids in the production process of the mine because the influences caused by the lost of intermediate components is eliminated.The results show that the typical black oil experimental data can be directly used for engineering calculation,but the volatile crude oil data needs to be corrected.The stronger the volatility of crude oil is,the smaller corrected data of comparative experiments is.The calculated geological reserves are 6%to 10%higher than the volume factor measured under laboratory conditions.
作者 潘威 廖恒杰 汪文基 程超 王理 PAN Wei;LIAO Hengjie;WANG Wenji;CHENG Chao;WANG Li(Shanghai Branch,CNOOC(China)Ltd.,Shanghai 200335,China)
出处 《海洋石油》 CAS 2023年第2期29-34,共6页 Offshore Oil
基金 “十三五”国家科技重大专项“东海低渗-致密天然气勘探开发技术”(2016ZX05027-004) 中海石油(中国)有限公司综合科研“西湖凹陷在生产油气田中后期综合调整关键技术研究与实践”(CNOOC-KJ 135 ZDXM 39 SH03)。
关键词 挥发性油藏 体积系数 数据校正 volatile reservoir volume factor data correction
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