Due to the limitation of actual shale gas reservoir conditions and fracturing technologies,artificial fracture networks are different greatly even in the same or similar stimulated reservoir volume.Deviations and even...Due to the limitation of actual shale gas reservoir conditions and fracturing technologies,artificial fracture networks are different greatly even in the same or similar stimulated reservoir volume.Deviations and even faults occur in evaluation and cognition if only the stimulated reservoir volume(SRV)is used to characterize and evaluate the effect of stimulation.In this paper,the spatial distribution of artificial fractures and natural fractures and the internal pressure state and degree of reserve recovery of stimulated shale gas reservoirs were studied by means of artificial fracture propagation numerical simulation and production numerical simulation.And three concepts were proposed,i.e.,shale gas fracture network,ideal fracture network and appropriate-stimulation degree of fracture network.The study results indicate that,at the end of reservoir development,target zones can be classified into three types(i.e.,relatively appropriate stimulation zone,transitional stimulation zone,and uncompleted stimulation zone)according to the recovery degree and production time of stimulated reservoirs;and that the final morphologic parameter of fracture networks and the reservoir characteristic are two main factors affecting the appropriate-stimulation degree of fracture networks.As for a specific gas reservoir,the orientation,length,conduction,height and spatial location of its fracture network are the main factors influencing its appropriate-stimulation degree if the well trajectory is set.The proposal of the theory on the appropriate-stimulation degree of hydraulic fracture networks in shale gas reservoir enriches the theoretical system of shale reservoir stimulation technology,and it can be used as the reference for characterizing the fracture systems in other unconventional reservoirs,such as tight oil and gas reservoirs.展开更多
为实现储能电池全生命周期下的电池状态动态评估,提高复杂工况下锂离子电池模型的自适应性与状态估计的准确性,提出基于改进逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)-模糊贝叶斯...为实现储能电池全生命周期下的电池状态动态评估,提高复杂工况下锂离子电池模型的自适应性与状态估计的准确性,提出基于改进逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)-模糊贝叶斯网络的电池荷电状态(state of charge,SOC)和健康状态(state of health,SOH)联合估计方法。应用多阶电阻-电容电路(resistor-capacitance circuit,RC)模型、使用节点-支路框架构建电池的等效电路模型,通过基尔霍夫定律与欧姆定律对二阶RC电池等效电路模型中的并联回路进行电气特性分析,构建空间状态方程及等效输出方程;对构建的状态方程进行离散化处理,分别定义并联独立回路离散化零输入响应、零状态响应,分析离散化电池模型状态空间方程;将专家打分法引入TOPSIS算法中进行电池SOC量化估计,结合融入模糊尺度的贝叶斯网络,在相同时间分布尺度下通过电池SOH值计算电池观测样本中对应的SOC值,实现电池SOH与SOC联合估计。实验结果表明:所提方法可有效估计不同离散空间尺度下的电池SOC和SOH结果,估计方法具有良好的准确性与较高的精度。展开更多
文摘为提高双点渐进成形(double-side incremental sheet forming,DSIF)制件的成形精度,以方锥盒制件作为试验制件,以刀具直径、层间距、成形角、板厚和成形深度等工艺参数为影响因素,以底部回弹值和侧壁鼓凸最小值作为优化目标设计正交试验,利用Abaqus数值仿真计算出试验结果数据,通过建立多输入和多输出的BP(back propagation)神经网络预测模型,结合带精英策略的非支配排序遗传算法(non-dominated sorting genetic algorithm,NAGA-Ⅱ)求解双点渐进成形工艺参数多目标优化问题,基于熵权逼近理想解排序法(technique for order preference by similarity to ideal solution,TOPSIS)从Pareto解集中决策出一组最优工艺参数组合以提高优化结果的精确度,通过优化和筛选得到的最佳工艺参数组合进行对应试验。结果表明,经实测得到制件的底部回弹值为0.693 mm,侧壁鼓凸值为0.934 mm,筛选出的目标值误差分别为6.31%和2.09%。由此可见,建立的多目标优化流程具有可行性,为双点渐进成形制件的回弹减少提供了有效的优化方案。
文摘Due to the limitation of actual shale gas reservoir conditions and fracturing technologies,artificial fracture networks are different greatly even in the same or similar stimulated reservoir volume.Deviations and even faults occur in evaluation and cognition if only the stimulated reservoir volume(SRV)is used to characterize and evaluate the effect of stimulation.In this paper,the spatial distribution of artificial fractures and natural fractures and the internal pressure state and degree of reserve recovery of stimulated shale gas reservoirs were studied by means of artificial fracture propagation numerical simulation and production numerical simulation.And three concepts were proposed,i.e.,shale gas fracture network,ideal fracture network and appropriate-stimulation degree of fracture network.The study results indicate that,at the end of reservoir development,target zones can be classified into three types(i.e.,relatively appropriate stimulation zone,transitional stimulation zone,and uncompleted stimulation zone)according to the recovery degree and production time of stimulated reservoirs;and that the final morphologic parameter of fracture networks and the reservoir characteristic are two main factors affecting the appropriate-stimulation degree of fracture networks.As for a specific gas reservoir,the orientation,length,conduction,height and spatial location of its fracture network are the main factors influencing its appropriate-stimulation degree if the well trajectory is set.The proposal of the theory on the appropriate-stimulation degree of hydraulic fracture networks in shale gas reservoir enriches the theoretical system of shale reservoir stimulation technology,and it can be used as the reference for characterizing the fracture systems in other unconventional reservoirs,such as tight oil and gas reservoirs.
文摘为实现储能电池全生命周期下的电池状态动态评估,提高复杂工况下锂离子电池模型的自适应性与状态估计的准确性,提出基于改进逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)-模糊贝叶斯网络的电池荷电状态(state of charge,SOC)和健康状态(state of health,SOH)联合估计方法。应用多阶电阻-电容电路(resistor-capacitance circuit,RC)模型、使用节点-支路框架构建电池的等效电路模型,通过基尔霍夫定律与欧姆定律对二阶RC电池等效电路模型中的并联回路进行电气特性分析,构建空间状态方程及等效输出方程;对构建的状态方程进行离散化处理,分别定义并联独立回路离散化零输入响应、零状态响应,分析离散化电池模型状态空间方程;将专家打分法引入TOPSIS算法中进行电池SOC量化估计,结合融入模糊尺度的贝叶斯网络,在相同时间分布尺度下通过电池SOH值计算电池观测样本中对应的SOC值,实现电池SOH与SOC联合估计。实验结果表明:所提方法可有效估计不同离散空间尺度下的电池SOC和SOH结果,估计方法具有良好的准确性与较高的精度。
