It has been known that the productivity of artesian wells is strongly dependent on the rheological properties of crude oils. This work targets two deep artesian wells(>5000 m) that are producing heavy crude oil. Th...It has been known that the productivity of artesian wells is strongly dependent on the rheological properties of crude oils. This work targets two deep artesian wells(>5000 m) that are producing heavy crude oil. The impacts of well conditions including temperature, pressure and shear rate, on the crude oil rheology were comprehensively investigated and correlated using several empirical rheological models. The experimental data indicate that this heavy oil is very sensitive to temperature as result of microstructure change caused by hydrogen bonding. The rheological behavior of the heavy oil is also significantly impacted by the imposed pressure, i.e., the viscosity flow activation energy(Eμ) gently increases with the increasing pressure. The viscosity–shear rate data are well fitted to the power law model at low temperature. However, due to the transition of fluid feature at high temperature(Newtonian fluid), the measured viscosity was found to slightly deviate from the fitting data. Combining the evaluated correlations, the viscosity profile of the heavy crude oil in these two deep artesian wells as a function of well depth was predicted using the oilfield producing data.展开更多
DAS(database as a service)模型数据库中采用加密方案的关键问题之一是针对密文关系的查询处理.DAS模型特有的体系结构和信任模型决定了加密解密操作只能在客户端进行,目前的方案普遍在元组粒度加密的基础上进行查询重写,不可避免地造...DAS(database as a service)模型数据库中采用加密方案的关键问题之一是针对密文关系的查询处理.DAS模型特有的体系结构和信任模型决定了加密解密操作只能在客户端进行,目前的方案普遍在元组粒度加密的基础上进行查询重写,不可避免地造成了加密效率的损失.为此,提出一种支持属性粒度加密方案的查询重写算法,利用关系代数公式对查询语句进行等价变换,将涉及加密属性的条件谓词与其他条件谓词分离,重构查询语句,支持任意层次的相关子查询.实验显示,算法能够降低客户端与服务器间的网络传输数据量,从而有效地缩短加密DAS模型数据库的查询执行时间.展开更多
基金Supported by the National Key Science&Technology Projects during 13th Five-Year Plan(2016ZX05053-003)Young Scholars Development fund of SWPU(201499010121)
文摘It has been known that the productivity of artesian wells is strongly dependent on the rheological properties of crude oils. This work targets two deep artesian wells(>5000 m) that are producing heavy crude oil. The impacts of well conditions including temperature, pressure and shear rate, on the crude oil rheology were comprehensively investigated and correlated using several empirical rheological models. The experimental data indicate that this heavy oil is very sensitive to temperature as result of microstructure change caused by hydrogen bonding. The rheological behavior of the heavy oil is also significantly impacted by the imposed pressure, i.e., the viscosity flow activation energy(Eμ) gently increases with the increasing pressure. The viscosity–shear rate data are well fitted to the power law model at low temperature. However, due to the transition of fluid feature at high temperature(Newtonian fluid), the measured viscosity was found to slightly deviate from the fitting data. Combining the evaluated correlations, the viscosity profile of the heavy crude oil in these two deep artesian wells as a function of well depth was predicted using the oilfield producing data.
文摘DAS(database as a service)模型数据库中采用加密方案的关键问题之一是针对密文关系的查询处理.DAS模型特有的体系结构和信任模型决定了加密解密操作只能在客户端进行,目前的方案普遍在元组粒度加密的基础上进行查询重写,不可避免地造成了加密效率的损失.为此,提出一种支持属性粒度加密方案的查询重写算法,利用关系代数公式对查询语句进行等价变换,将涉及加密属性的条件谓词与其他条件谓词分离,重构查询语句,支持任意层次的相关子查询.实验显示,算法能够降低客户端与服务器间的网络传输数据量,从而有效地缩短加密DAS模型数据库的查询执行时间.
