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具有组分梯度的挥发性油藏组分分布规律
引用本文:李菊花,李相方,刘滨.具有组分梯度的挥发性油藏组分分布规律[J].新疆石油地质,2010,31(1):81-84.
作者姓名:李菊花  李相方  刘滨
作者单位:1.长江大学 a.油气资源与勘探技术教育部重点实验室;b.石油工程学院,湖北 荆州 434023;2.中国石油大学 石油与天然气工程学院,北京 102249;3.中国石油吐哈油田分公司勘探开发研究院,新疆 哈密 839009
基金项目:湖北省教育厅优秀中青年人才基金 
摘    要:根据国内外文献报道统计了组分随深度变化的21组流体组成数据,建立了不同类型油藏流体组分梯度分布图版,初步确定挥发油系统中C7+组分梯度的变化范围为0.01~0.05mol%/m;运用等温组分梯度模型预测挥发性油藏油气界面,轻质、重质摩尔组成,原油的物性参数,展示了流体组分和性质随深度的分布特征和变化规律,显示出组分最大变化率发生在油气界面附近;采用等组分和等温梯度模型预测PVT属性建立实例油藏原油体积系数、溶解气油比与油藏埋深的关系图版估计地质储量范围值。对PB油藏典型流体样品采用考虑组分梯度模拟方法重新估算的地质储量较原计算值高5.38%,溶解气原始地质储量较原计算值高3.9%。

关 键 词:组分梯度  挥发性油藏  地质储量  状态方程  
收稿时间:2009-07-15

Compositional Distribution in Volatile Oil Reservoir with Compositional Gradient
LI Ju-hua,LI Xiang-fang,LIU Bin.Compositional Distribution in Volatile Oil Reservoir with Compositional Gradient[J].Xinjiang Petroleum Geology,2010,31(1):81-84.
Authors:LI Ju-hua  LI Xiang-fang  LIU Bin
Affiliation:1. Yangtze University, a. MOE Key Laboratory of Oil-Gas Resources and Exploration Technologies, b. Institute of Petroleum Engineering, Jingzhou, Hubei 434023, China;2. Institute of Oil and Gas Engineering, China University of Petroleum, Beijing 102249, China;3. Research Institute of Exploration and Development, Tuha Oilfield Company, PetroChina, Hami, Xinjiang 839009, China
Abstract:This paper presents the charts of compositional gradient distribution of different types of reservoir fluids based on the data from 21 groups of fluid compositions that change with depth reported in literatures at home and abroad. It is preliminarily identified that the compositional gradient of C_7~+ in the volatile oil system varies in range of 0.01~0.05 mol%/m. Using the isothermal model of compositional gradient to predict the oil-gas contact, the light and heavy components and the physical parameters of crude oil in volatile oil reservoir, it is shown that the maximum rate of change occurs right near the oil-gas contact, displaying the distribution and variation of the fluid component and property with depth. Using the iso-compositional and isothermal gradient model to predict the PVT attribute, the relation chart of the crude oil volume coefficient and the solution gas-oil ratio with depth of reservoir is established for estimation of the range of geological reserves. For PB reservoir as a case, by using this simulation method, it shows that the re-estimated OOIP and OGIP are 5.38% and 3.9% higher than the original estimation values, respectively.
Keywords:compositional gradient  volatile reservoir  geologic reserve  OOIP  OGIP  state equation
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