油田沉降监测对维护设施安全及反演储层状态参数具有重要意义。时序DInSAR应用于油田沉降监测和储层参数反演表现出较好的潜力，但易受季节性失相干、大形变梯度和仅能监测一维形变等问题的制约，监测结果精度和空间覆盖度受到限，且缺少多频度参数反演研究，不满足储层开采过程高效监测需求。本项目选取塔里木油田为研究区，开展时序DInSAR油田沉降监测和储层参数反演研究：揭示时序DInSAR季节性失相干规律，发展有效削弱季节性失相干的方法；发展大梯度形变时序建模和解算方法；构建基于真实形变模型约束的时序二维形变解算模型，解算精确的时序沉降信息，基于此反演储层几何状态参数及多频度物理状态参数，揭示塔里木油田沉降规律和开采动态过程。本项目旨在为大范围、高效率和高精度地监测油田沉降和反演储层参数提供可靠技术途径，为油田安全监测、储层健康状况检测及开采过程管理提供科学依据。研究成果具有重要的科学意义和推广价值。

The monitoring of oil field subsidence is of great significance for safety maintenance of facilities and the inversion of reservoir state parameters. The application of multi-temporal DInSAR (MT-DInSAR) to oil field subsidence monitoring and reservoir parameter inversion exhibits preferable potentials, except that the seasonal decorrelation, significant deformation gradient and one-dimensional deformation tracking often lead to decrease of accuracy and spatial coverage (or spatial resolution). Meanwhile, the lack of multi-frequency reservoir parameter inversion make it not able to satisfy the requirement of efficient monitoring of reservoir mining process. This project will select the Tarim Oilfield as the test site, and carry out research on subsidence monitoring and reservoir parameter inversion based on the MT-DInSAR. The basic strategy of the project is provided here. By comprehensive analyzing the interferometric coherence, it is expected to reveal the seasonal decorrelation mechanism of the MT-DInSAR and to develop the method for effectively decreasing the seasonal decorrelation. A large-gradient deformation time series modeling and estimation method will be developed for the purpose to extract the large-gradient subsidence of Oilfield. Another principle procedure is to establish a two-dimensional deformation retrieving approach based on the constraint constructed with the reasonable deformation models. The main purpose is to accurately derive subsidence time series and to estimate the multi-frequency reservoir state parameters. Meanwhile, we will reveal the subsidence pattern and the mining process. This project aims to provide reliable approaches for subsidence monitoring and reservoir state parameters inversion and analysis in the large-scale region with high-efficiency and high-accuracy, and to provide scientific basis for oil field safety monitoring, reservoir health condition detection and mining process management. The research results have important scientific significance and good popularization and application value.