摘要
在油藏描述与油气田开发中,随着智能控制与智能决策技术的不断运用与发展,将会出现大量的随机信号非线性检索滤波与最优估计算法问题亟待解决。为了充分挖掘油藏描述与油气田开发中广泛存在的各种大数据复杂信息,在深入搜索与深刻分析智能控制中一类多维广义非平稳部分可观测扩散过程随机信息流的特征刻画与泛函结构的基础上,着重研究了智能控制中此类随机信号的非线性检索滤波与优化算法,为进一步研究与解决油气田综合勘探、开发中的智能控制与决策的相关问题提供了有效手段与方法。
In reservoir description and oil and gas field development,with the continuous application and development of intelligent control and intelligent decision-making technology,there will be a large number of random signal nonlinear retrieval filtering and optimal estimation algorithm problems that need to be solved urgently.In order to fully mine the complex information of various big data widely existing in reservoir description and oil and gas field development,this paper conducts in-depth search and in-depth analysis of intelligent control for a class of multi-dimensional generalized non-stationary partially observable diffusion process stochastic information flow characterization and functional characterization and functional on the basis of the structure,the nonlinear retrieval filtering and optimization algorithm of such random signals in intelligent control is emphatically studied,which provides effective means and methods for further research and resolution of intelligent control and decision-making in comprehensive exploration and development of oil and gas fields.
作者
肖筱南
赵小平
XIAO Xiaonan;ZHAO Xiaoping(Tan Kah Kee College,Xiamen University,Zhangzhou,Fujian 363105,China;School of Economics and Management,Xi’an Shiyou University,Xi’an,Shaanxi 710065,China)
出处
《西安石油大学学报（自然科学版）》
CAS
北大核心
2022年第5期123-126,共4页
Journal of Xi’an Shiyou University（Natural Science Edition）
基金
国家自然科学基金(12071392)。
关键词
智能控制
随机信号
信息检索
优化算法
扩散过程
油藏描述
intelligent control
stochastic signal
information retrieval
optimization algorithm
diffusion process
reservoir description
