火花塞
微球
流离失所(心理学)
提高采收率
石油工程
机制(生物学)
聚合物
材料科学
地质学
化学工程
复合材料
工程类
机械工程
哲学
认识论
心理治疗师
心理学
作者
Yongtao Ju,Hongmei Luo,Xuena Zhang,Jie Zhang
摘要
Abstract To investigate the mechanisms of deep regulation and displacement technologies for enhancing oil recovery in sandstone reservoirs, a proprietary profile control experimental system integrated with real‐time computed tomography scanning was utilized to achieve, for the first time, full‐cycle three‐dimensional visualization of the microscopic residual oil displacement process. Despite the promising results, pore blockage and long‐term stability of the injected plugs require further investigation. By conducting comparative analyses of the evolution characteristics of microscopic residual oil saturation before and after regulation and displacement under varying plug conditions, the changes in the spatial distribution and occurrence state of microscopic residual oil were quantitatively examined. Results indicate that: (a) Microscopic residual oil primarily exists in network‐like, porous, and isolated forms, with network‐like and porous forms accounting for 82.93%–91.41%, the reduction of which indicates the improved displacement effectiveness and better recovery subsequently; (b) Regulation and displacement effectively block high‐permeability channels and increase displacement pressure in medium‐to‐small pores, network‐like and porous residual oil gradually transitions into isolated residual oil after the deep regulation and displacement, with its proportion increasing from 0.8% to 39.6%; (c) The polymer–microsphere plug combination exhibits superior performance compared to a single plug, the recovery of the combination plug reaches 1.11 times that of the single plug method, presenting a great potential field applications by taking care of some scale‐up considerations, like formation heterogeneity, chemical stability, and so on. The research provides theoretical support for designing regulation and displacement strategies for water‐flooding sandstone reservoirs.
科研通智能强力驱动
Strongly Powered by AbleSci AI