近年来,提出了一些求解约束优化分布控制问题的方法,其中最常用的方法是先离散偏微分方程,然后求解离散得到的线性方程组.文献中提出了一些Krylov子空间预处理方法用来求解该线性方程组.通过分析张晓莹等提出的块对角预处理矩阵(Zhang X...近年来,提出了一些求解约束优化分布控制问题的方法,其中最常用的方法是先离散偏微分方程,然后求解离散得到的线性方程组.文献中提出了一些Krylov子空间预处理方法用来求解该线性方程组.通过分析张晓莹等提出的块对角预处理矩阵(Zhang X Y,Yan H Y.Huang Y M.On preconditionedMINRES method for solving the distributed control problems.Commun Appl Math Comput,2014,28:128-132.),构造了一个含参数的块对角预处理线性方程组,并运用含参数预处理最小残量方法求解该线性方程组.预处理矩阵的谱分析表明当参数大于1时,含参预处理线性方程组的谱分布更加集中.数值实验结果验证了含参数的预处理最小残量方法对于求解分布式控制问题是有效的.展开更多
Under single-satellite observation,the parameter estimation of the boost phase of high-precision space noncooperative targets requires prior information.To improve the accuracy without prior information,we propose a p...Under single-satellite observation,the parameter estimation of the boost phase of high-precision space noncooperative targets requires prior information.To improve the accuracy without prior information,we propose a parameter estimation model of the boost phase based on trajectory plane parametric cutting.The use of the plane passing through the geo-center and the cutting sequence line of sight(LOS)generates the trajectory-cutting plane.With the coefficient of the trajectory cutting plane directly used as the parameter to be estimated,a motion parameter estimation model in space non-cooperative targets is established,and the Gauss-Newton iteration method is used to solve the flight parameters.The experimental results show that the estimation algorithm proposed in this paper weakly relies on prior information and has higher estimation accuracy,providing a practical new idea and method for the parameter estimation of space non-cooperative targets under single-satellite warning.展开更多
This is a case study of the application of pre-stack inverted elastic parameters to tight-sand reservoir prediction. With the development of oil and gas exploration, pre-stack data and inversion results are increasing...This is a case study of the application of pre-stack inverted elastic parameters to tight-sand reservoir prediction. With the development of oil and gas exploration, pre-stack data and inversion results are increasingly used for production objectives. The pre-stack seismic property studies include not only amplitude verse offset （AVO） but also the characteristics of other elastic property changes. In this paper, we analyze the elastic property parameters characteristics of gas- and wet-sands using data from four gas-sand core types. We found that some special elastic property parameters or combinations can be used to identify gas sands from water saturated sand. Thus, we can do reservoir interpretation and description using different elastic property data from the pre-stack seismic inversion processing. The pre- stack inversion method is based on the simplified Aki-Richard linear equation. The initial model can be generated from well log data and seismic and geologic interpreted horizons in the study area. The input seismic data is angle gathers generated from the common reflection gathers used in pre-stack time or depth migration. The inversion results are elastic property parameters or their combinations. We use a field data example to examine which elastic property parameters or combinations of parameters can most easily discriminate gas sands from background geology and which are most sensitive to pore-fluid content. Comparing the inversion results to well data, we found that it is useful to predict gas reservoirs using λ, λρ, λ/μ, and K/μ properties, which indicate the gas characteristics in the study reservoir.展开更多
基金Project supported by the National Natural Science Foundation of China(11571156)
文摘近年来,提出了一些求解约束优化分布控制问题的方法,其中最常用的方法是先离散偏微分方程,然后求解离散得到的线性方程组.文献中提出了一些Krylov子空间预处理方法用来求解该线性方程组.通过分析张晓莹等提出的块对角预处理矩阵(Zhang X Y,Yan H Y.Huang Y M.On preconditionedMINRES method for solving the distributed control problems.Commun Appl Math Comput,2014,28:128-132.),构造了一个含参数的块对角预处理线性方程组,并运用含参数预处理最小残量方法求解该线性方程组.预处理矩阵的谱分析表明当参数大于1时,含参预处理线性方程组的谱分布更加集中.数值实验结果验证了含参数的预处理最小残量方法对于求解分布式控制问题是有效的.
基金supported in part by the National Natural Science Foundation of China(Nos.42271448,41701531)the Key Laboratory of Land Satellite Remote Sensing Application,Ministry of Natural Resources of the People’s Republic of China(No.KLSMNRG202317)。
文摘Under single-satellite observation,the parameter estimation of the boost phase of high-precision space noncooperative targets requires prior information.To improve the accuracy without prior information,we propose a parameter estimation model of the boost phase based on trajectory plane parametric cutting.The use of the plane passing through the geo-center and the cutting sequence line of sight(LOS)generates the trajectory-cutting plane.With the coefficient of the trajectory cutting plane directly used as the parameter to be estimated,a motion parameter estimation model in space non-cooperative targets is established,and the Gauss-Newton iteration method is used to solve the flight parameters.The experimental results show that the estimation algorithm proposed in this paper weakly relies on prior information and has higher estimation accuracy,providing a practical new idea and method for the parameter estimation of space non-cooperative targets under single-satellite warning.
基金supported by the National Basic Priorities Program "973" Project (Grant No.2007CB209600)China Postdoctoral Science Foundation Funded Project
文摘This is a case study of the application of pre-stack inverted elastic parameters to tight-sand reservoir prediction. With the development of oil and gas exploration, pre-stack data and inversion results are increasingly used for production objectives. The pre-stack seismic property studies include not only amplitude verse offset （AVO） but also the characteristics of other elastic property changes. In this paper, we analyze the elastic property parameters characteristics of gas- and wet-sands using data from four gas-sand core types. We found that some special elastic property parameters or combinations can be used to identify gas sands from water saturated sand. Thus, we can do reservoir interpretation and description using different elastic property data from the pre-stack seismic inversion processing. The pre- stack inversion method is based on the simplified Aki-Richard linear equation. The initial model can be generated from well log data and seismic and geologic interpreted horizons in the study area. The input seismic data is angle gathers generated from the common reflection gathers used in pre-stack time or depth migration. The inversion results are elastic property parameters or their combinations. We use a field data example to examine which elastic property parameters or combinations of parameters can most easily discriminate gas sands from background geology and which are most sensitive to pore-fluid content. Comparing the inversion results to well data, we found that it is useful to predict gas reservoirs using λ, λρ, λ/μ, and K/μ properties, which indicate the gas characteristics in the study reservoir.
