In fractured reservoirs, the fractures not but also form the main flow channels which connect productivity of reservoirs. However, because of the only provide the storage space for hydrocarbons, the pores of the matri...In fractured reservoirs, the fractures not but also form the main flow channels which connect productivity of reservoirs. However, because of the only provide the storage space for hydrocarbons, the pores of the matrix, so fractures dominate the heterogeneity and randomness of the distribution of fractures, exploration and evaluation of fractured reservoirs is still one of the most difficult problems in the oil industry. In recent years, seismic anisotropy has been applied to the assessment of fractured formations, whereas electrical anisotropy which is more intense in fractured formations than seismic anisotropy has not been studied or used so extensively. In this study, fractured reservoir models which considered multiple sets of fractures with smooth and partly closed, rough surfaces were established based on the fractures and pore network, and the vertical and horizontal electrical resistivities were derived as a function of the matrix and fracture porosities according to Ohm＇s law. By using the anisotropic resistivity equations, variations of the electrical anisotropy of three types of fractured models under the conditions of free pressure and confining pressure were analyzed through the variations of the exerted pressure, matrix porosity, fracture aperture and formation water resistivity. The differences of the vertical and horizontal resistivities and the anisotropy between the connected and non-connected fractures were also analyzed. It is known from the simulated results that an increase of the confining pressure causes a decrease of electrical anisotropy because of the elasticity of the closed fractures and the decrease of the fracture aperture. For a fixed fracture porosity, the higher the matrix porosity, the weaker the electrical anisotropy in the rock formation.展开更多
Production optimal control technologies have become important tools for efficiently developing oil and gas reservoirs in recent years.This paper presents an overview of the research and application of these technologi...Production optimal control technologies have become important tools for efficiently developing oil and gas reservoirs in recent years.This paper presents an overview of the research and application of these technologies in smart oilfield,including reservoir data matching and prediction,well production optimization,and automatic well monitoring and control technologies.With the support of the National Natural Science Foundation of China,we made years of effort and finally derived a novel data—driven reservoir data matching and prediction methods.Besides,the new automatic optimization technologies and flow monitoring and control devices were also presented.The proposed technologies helped improve the computational efficiency by hundreds of times compared to traditional technologies.The real-time optimization and control of the injection and production parameters was realized using the proposed technologies,which have been widely applied in actual reservoirs at home and abroad,achieving significant economic benefits.展开更多
We present an efficient and risk-informed closed-loop field development (CLFD) workflow for recurrently revising the field development plan (FDP) using the accrued information. To make the process practical, we integr...We present an efficient and risk-informed closed-loop field development (CLFD) workflow for recurrently revising the field development plan (FDP) using the accrued information. To make the process practical, we integrated multiple concepts of machine learning, an intelligent selection process to discard the worst FDP options and a growing set of representative reservoir models. These concepts were combined and used with a cluster-based learning and evolution optimizer to efficiently explore the search space of decision variables. Unlike previous studies, we also added the execution time of the CLFD workflow and worked with more realistic timelines to confirm the utility of a CLFD workflow. To appreciate the importance of data assimilation and new well-logs in a CLFD workflow, we carried out researches at rigorous conditions without a reduction in uncertainty attributes. The proposed CLFD workflow was implemented on a benchmark analogous to a giant field with extensively time-consuming simulation models. The results underscore that an ensemble with as few as 100 scenarios was sufficient to gauge the geological uncertainty, despite working with a giant field with highly heterogeneous characteristics. It is demonstrated that the CLFD workflow can improve the efficiency by over 85% compared to the previously validated workflow. Finally, we present some acute insights and problems related to data assimilation for the practical application of a CLFD workflow.展开更多
基金The authors also would like to acknowledge the support of the National Basic Research Program (973 Program) (2007CB209607) of ChinaNational High-tech R&D Program (863 Program) (2007AA060502)the Fundamental Research Project (07A10303) of CNPC
文摘In fractured reservoirs, the fractures not but also form the main flow channels which connect productivity of reservoirs. However, because of the only provide the storage space for hydrocarbons, the pores of the matrix, so fractures dominate the heterogeneity and randomness of the distribution of fractures, exploration and evaluation of fractured reservoirs is still one of the most difficult problems in the oil industry. In recent years, seismic anisotropy has been applied to the assessment of fractured formations, whereas electrical anisotropy which is more intense in fractured formations than seismic anisotropy has not been studied or used so extensively. In this study, fractured reservoir models which considered multiple sets of fractures with smooth and partly closed, rough surfaces were established based on the fractures and pore network, and the vertical and horizontal electrical resistivities were derived as a function of the matrix and fracture porosities according to Ohm＇s law. By using the anisotropic resistivity equations, variations of the electrical anisotropy of three types of fractured models under the conditions of free pressure and confining pressure were analyzed through the variations of the exerted pressure, matrix porosity, fracture aperture and formation water resistivity. The differences of the vertical and horizontal resistivities and the anisotropy between the connected and non-connected fractures were also analyzed. It is known from the simulated results that an increase of the confining pressure causes a decrease of electrical anisotropy because of the elasticity of the closed fractures and the decrease of the fracture aperture. For a fixed fracture porosity, the higher the matrix porosity, the weaker the electrical anisotropy in the rock formation.
基金the National Natural Science Foundation of China(Grant Nos.51344003,51674039,51874044,51922007,and 51604035)the National Science and Technology Major Project of China(Grant No.2016ZX05014).
文摘Production optimal control technologies have become important tools for efficiently developing oil and gas reservoirs in recent years.This paper presents an overview of the research and application of these technologies in smart oilfield,including reservoir data matching and prediction,well production optimization,and automatic well monitoring and control technologies.With the support of the National Natural Science Foundation of China,we made years of effort and finally derived a novel data—driven reservoir data matching and prediction methods.Besides,the new automatic optimization technologies and flow monitoring and control devices were also presented.The proposed technologies helped improve the computational efficiency by hundreds of times compared to traditional technologies.The real-time optimization and control of the injection and production parameters was realized using the proposed technologies,which have been widely applied in actual reservoirs at home and abroad,achieving significant economic benefits.
文摘We present an efficient and risk-informed closed-loop field development (CLFD) workflow for recurrently revising the field development plan (FDP) using the accrued information. To make the process practical, we integrated multiple concepts of machine learning, an intelligent selection process to discard the worst FDP options and a growing set of representative reservoir models. These concepts were combined and used with a cluster-based learning and evolution optimizer to efficiently explore the search space of decision variables. Unlike previous studies, we also added the execution time of the CLFD workflow and worked with more realistic timelines to confirm the utility of a CLFD workflow. To appreciate the importance of data assimilation and new well-logs in a CLFD workflow, we carried out researches at rigorous conditions without a reduction in uncertainty attributes. The proposed CLFD workflow was implemented on a benchmark analogous to a giant field with extensively time-consuming simulation models. The results underscore that an ensemble with as few as 100 scenarios was sufficient to gauge the geological uncertainty, despite working with a giant field with highly heterogeneous characteristics. It is demonstrated that the CLFD workflow can improve the efficiency by over 85% compared to the previously validated workflow. Finally, we present some acute insights and problems related to data assimilation for the practical application of a CLFD workflow.
