基于卫星升降轨时序DInSAR的塔里木油田沉降监测及储层状态参数反演

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.

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。

石油开采会导致储层孔隙压力显著降低，致使储层压实，进而引发严重的地面形变，会对油井及附属设施、输送管线以及周边建、构筑物造成破坏。以往研究表明，石油开采所致地表形变主要为沉降，且伴随着水平形变的发生。另一方面，地面沉降也是石油储层孔隙压强变化、储层几何形状、位置、深度及开采量(体积变化)等几何状态与物理状态参数在地表的直观体现，利用油田地面沉降信息可反演储层参数。因此，油田沉降监测一直广受关注。时序DInSAR在形变监测中具有覆盖广和分辨率高的优势，但是易受季节性失相干、油田大形变梯度和形变监测维度缺失等问题的影响，精度受到限制。本项目主要针对季节性失相干及干涉对优选、大梯度形变建模与解算方法、时序二维形变建模与解算方法、油田沉降监测与储层参数反演进行研究，提出了时序DInSAR季节性失相干的概念和理论以及避免季节性失相干的干涉对优选方法、基于干涉相位梯度修正的大梯度形变时序建模和解算方法、基于独立形变模型约束的时序二维形变解算模型与方法，并针对塔里木油田、克拉玛依油田和和辽河油田开展了沉降监测，以沉降最为显著的辽河油田为对象开展了储层参数反演与分析。此外，对储层物理状态参数的反演进行了理论推导和分析。本项目研究是对时序DInSAR基础理论和方法的进一步拓展，且可以促进其形变监测精度的提高，为油田沉降监测和储层参数反演提供有力的支撑，进而为油田安全监测、储层健康状况评估、更好地理解石油开采过程及其优化提供科学的信息和依据，具有重要的科学意义和较好的推广应用价值。