X-ray imaging and magnetic resonance approach for enhanced oil recovery

用于提高石油采收率的 X 射线成像和磁共振方法

• 批准号: DP190103744
• 负责人: Prof Christoph Arns
• 金额: $ 31.05万
• 依托单位: The University of New South Wales
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2019
• 资助国家: 澳大利亚
• 起止时间: 2019-05-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP190103744
• 关键词: ray; imaging; magnetic; resonance; approach

This project aims to develop an efficient multi-scale modelling capability to quantify the effect of two-phase fluid flow within porous material by modelling rock wettability heterogeneity and alteration on two-phase flow performance for heterogeneous rock. Super-resolution methods combined with a deep learning approach will be used to determine a digital representation of reservoir rock, achieving an unprecedented combination of resolution necessary to resolve small-scale fluid connectivity and field of view required to capture heterogeneity. The project expects to develop a workflow to populate a high-resolution model with wettability parameters by combining micro-CT imaging with nuclear magnetic resonance measurements. This improved understanding should provide significant benefits by enhancing our capability to optimise enhanced oil and gas recovery programs.

该项目旨在通过模拟岩石润湿性非均质性和蚀变对非均质岩石两相流动性能的影响，开发一种有效的多尺度建模能力，以量化多孔材料中两相流体流动的影响。超分辨率方法将与深度学习方法相结合，用于确定储层岩石的数字表示，从而实现解决小尺度流体连通性所需的分辨率和捕获非均质性所需的视野的前所未有的组合。该项目希望通过将微ct成像与核磁共振测量相结合，开发一个具有润湿性参数的高分辨率模型的工作流程。这种更好的理解将通过提高我们优化油气采收率计划的能力，为我们带来显著的好处。