Pore-to-core linkages and upscaling for gas injection (CO2 Storage, EOR) in carbonates

研究将集中在多尺度工作流的应用，碳酸盐岩不同的孔隙结构和润湿状态。实验活动将包括一组多尺度观测（孔径尺度分辨率，视野为十厘米）的稳态排水和吸水在水湿和混合湿碳酸盐岩具有明显的多尺度异质性。理论发展和严格的验证将在选定的孔隙结构特征的采石场岩石上进行。大部分工作将用于分析壳牌感兴趣的一个或多个储层的大量样本。这项工作还将与项目2.2密切相关，其中将开发机器学习孔隙结构分类技术，以进一步加强这些工作流程。将花费大量时间开发数据分析工作流程，以应用于碳酸盐岩中的气体注入。评价了在具有多尺度非均质性的碳酸盐岩中，包括微孔隙区域，孔隙尺度岩石和流体性质的图像分割的最佳方法。图像处理工作流程将根据独立观察结果进行验证，例如，将根据来自医学CT图像的推断来评估来自分割的平均孔隙度估计。工作流程，以构建数字的整个核心模型，从孔隙和连续尺度的观察，将制定特别提到的气体注入碳酸盐岩不同的润湿状态。

The research will focus on the application of the multi scale workflow to carbonate rocks with varying pore structures and wetting states. The experimental activity will comprise a set of multi scale observations (pore scale resolution across a field of view of deca cm) of steady state drainage and imbibition in both water wet and mixed wet carbonate rocks with distinct multi scale heterogeneity. Theoretical development and rigorous validation will be performed on quarry rocks selected for pore structure characteristics. The bulk of the activity will be spent analysing scores of samples from one or more reservoirs of interest to Shell. The work will also be closely linked to project 2.2 in which machine learning pore structure classification techniques will be developed to further enhance these workflows. Significant time will be spent on the development of the data analysis workflows for application to gas injection in carbonate rocks. The optimal approach for image segmentation of pore scale rock and fluid properties in carbonates with multi scale heterogeneity, including micro porous regions, will be evaluated. Image processing workflows will be validated against independent observations, e.g., average porosity estimates from segmentation will be evaluated against inference from medical CT imagery. Workflows to construct numerical whole core models from pore and continuum scale observations will be developed with particular reference to gas injection in carbonates with varying wetting states.