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机构地区:[1]西安石油大学石油工程学院 [2]中国石油大学石油工程教育部重点实验室.北京
出 处:《钻采工艺》2009年第5期40-41,126,共2页Drilling & Production Technology
摘 要:在智能井系统中,传感器信息的正确分析是进行油藏优化控制的基础。目前测得的各信息中,温度和压力是最基础的数据也是比较敏感的因素。利用能量守恒定律建立了双分支水平智能井的温度与含水率的关系模型,通过对温度变化的研究定量分析了不同流入单元的各自含水变化情况。利用节点分析和数值模拟,结合双分支水平井的油藏,分析了压力分布和变化与油藏参数以及产量、含水变化的关系。通过分析一口双分支智能井前后两个阶段温度剖面的变化对比情况,得到了各自含水的定量变化。发现一个分支已进入含水快速增长期,需要对其采取限产、控水措施并给出了具体值。同时利用压力信息得到了较准确的表皮因子,结合数值模拟优化了各分支配产与生产压差。信息分析研究为接下来的各分支优化控制以提高采收率和经济效益提供了信息基础。Correct analysis of sensor information is the key to optimizing and controlling reservoir in smart well systems.Of the all factors measured at present,temperature and pressure are the basic and relatively sensitive ones.A model on the temperature and water ratio relationship in bi-lateral intelligent horizontal well was developed by using the principle of conservation of energy.The relationship between the distribution and variation of pressure and reservoir parameter,producing rate and water ratio was analyzed by using nodal analysis and numerical simulation.Temperature profiles of two producing phases of a bi-lateral intelligent well were compared.Based on that,water ratio of the two laterals was quantitatively gotten.Results showed that one lateral was already at the phase of rapid water buildup and needed to adopt water controlling measures while the other was still maintaining low water ratio.Pressure information was used to get a more accurate skin factor.Further allocation and drawdown pressure of each lateral was optimized.These analyses provided useful information basic for the following lateral optimization to enhance recovery and economic benefits.
分 类 号:TE323[石油与天然气工程—油气田开发工程]
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