水驱气藏水侵动态储量损失实验研究

发布时间：2018-05-01 08:33

本文选题：水驱气藏 + 动态储量损失　；参考：《特种油气藏》2017年05期

【摘要】：针对水驱气藏水侵动态储量损失规律认识不清的问题,通过水驱气实验研究了水驱气藏水侵动态储量损失规律,并借助核磁共振技术,研究了水封气微观分布特征。结果表明:单个岩样的水侵动态储量损失率随地层径向驱替压力梯度的增大呈先减小后增大的趋势,总体上水侵动态储量损失率随岩样渗透率的增大而减小;水封气量随孔隙半径增大呈先增大后减小的趋势,水封气主要分布在原本含气而孔隙半径相对较小的孔隙中。研究认为,对于水驱气藏的开发,应通过室内实验确定合理生产压差,尽可能减小水侵动态储量损失,从而改善水驱气藏开发效果。该实验研究成果对于制订水驱气藏控水、治水技术政策和气藏开发后期确定潜力区域具有重要的指导意义。
[Abstract]:In view of the lack of clear understanding of the law of water invasion dynamic reserve loss in water drive gas reservoirs, the law of water invasion dynamic reserves loss in water drive gas reservoirs is studied by water drive gas experiment, and the microscopic distribution characteristics of water seal gas are studied by means of nuclear magnetic resonance (NMR) technology. The results show that the loss rate of water invasion dynamic reserves of a single rock sample decreases first and then increases with the increase of radial displacement pressure gradient, and the overall loss rate of water invasion dynamic reserves decreases with the increase of rock sample permeability. With the increase of pore radius, the water seal gas volume increases first and then decreases, and the water seal gas mainly distributes in the pores which contain gas and the pore radius is relatively small. It is considered that for the development of water drive gas reservoir, reasonable production pressure difference should be determined through laboratory experiments, and the loss of water invasion dynamic reserves should be reduced as much as possible so as to improve the development effect of water drive gas reservoir. The experimental results are of great significance to the formulation of water control policy for water drive gas reservoirs and the determination of potential areas in the later stage of gas reservoir development.
【作者单位】：复杂油气田勘探开发重庆市重点实验室;重庆科技学院;中海石油(中国)有限公司湛江分公司;
【基金】：“十三五”国家科技重大专项子项目“深层礁滩相储层气水两相渗流特征研究”(2016ZX05017-001-HZ02) 国家自然科学基金“裂缝性底水凝析气藏水侵机理研究”(51374296) 重庆市研究生科研创新项目“水驱气藏动态储量损失规律及损失储量再动用研究”(CYS16226) 重庆科技学院研究生科技创新项目“普光气田产水气井产能预测数学模型研究”(YKJCX1620106)
【分类号】：TE377

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