[论文解读] Evaluating CO2 Storage Potential of Offshore Reservoirs and Saline Formations in Central Gulf of Mexico by Employing Data-driven Models with SAS Viya

Rupom Bhattacherjee, Kodjo Opoku Botchway+3 more|arXiv (Cornell University)|Sep 24, 2022

CO2 Sequestration and Geologic Interactions被引用 4

一句话总结

本研究利用SAS Viya的数据驱动建模方法，评估了墨西哥湾中部海域海底储层及盐水层的CO2封存潜力。通过整合地质数据、建立岩石与流体性质的相关性，并运用交互式可视化技术，作者识别出高潜力区块，并通过毛细管封存和溶解作用的考量，提升了封存资源估算的准确性。

ABSTRACT

The SECARB offshore partnership project seeks to screen deep saline aquifers and hydrocarbon reservoirs in the central Gulf of Mexico (GOM) for CO2 sequestration and CO2-driven enhanced oil and gas recovery and estimate the corresponding CO2 storage resources for select reservoirs. To this end, three major objectives have been completed: managing geological data from different sources, building a reservoir screening platform for CO2 storage, and ranking the reservoirs based on the estimated storage potential. First, the major geological characteristics of both shelf and deep-water areas of the central GOM were examined and compared to define the appropriate reservoir screening criteria. Consequently, the CO2 storage resources of the screened reservoirs were calculated and reported at the BOEM field level to identify fields with the highest storage potential. In the project's current phase, the assessment is being expanded to saline formations. Correlations are being identified, tested, and developed for a broad range of rock and fluid properties, including thickness, porosity, permeability, fluid saturation, and fluid chemistry. These correlations are developed for interfacial tension and CO2 saturated brine viscosity to improve the storage estimates and consider the capillary trapping and solubility of CO2 in reservoir fluids. SAS Viya software is used to make visualizations of these properties of the offshore reservoir and make comparisons and draw similarities between the experimental and estimated correlated measures. Using interactive plots, different conditions could be screened, making the analysis more attractive from a user's point of view.

研究动机与目标

• 评估墨西哥湾中部深部盐水层与油气储层的CO2封存潜力。
• 基于地质与流体性质数据，开发用于CO2封存与提高原油采收率的储层筛选平台。
• 根据BOEM区块级别的估算CO2封存容量，对海上区块进行排名。
• 通过建立界面张力与CO2饱和卤水黏度的相关性，改进封存资源估算。
• 利用SAS Viya实现储层属性在陆架与深水区域间的交互式可视化与对比分析。

提出的方法

• 整合墨西哥湾中部陆架与深水区域多个来源的地质数据。
• 基于厚度、孔隙度、渗透率、流体饱和度及流体化学性质的对比，定义储层筛选标准。
• 开发界面张力与CO2饱和卤水黏度的数据驱动相关性，以优化封存潜力估算。
• 利用SAS Viya实现交互式数据可视化，支持动态筛选储层条件并对比不同储层的属性。
• 基于估算的储层参数与封存机制，在BOEM区块级别计算CO2封存资源量。
• 通过推导的流体性质关系，将毛细管封存与溶解效应定量整合至封存潜力建模中。

实验结果

研究问题

• RQ1 墨西哥湾中部海域哪些海上储层与盐水层具有最高的CO2封存潜力？
• RQ2 关键岩石与流体性质（如孔隙度、渗透率与卤水黏度）与CO2封存容量之间存在何种相关性？
• RQ3 界面张力与CO2饱和卤水黏度的数据驱动相关性在多大程度上可提升封存资源估算的准确性？
• RQ4 通过SAS Viya实现的交互式可视化在识别与排序高潜力CO2封存区块方面有何增强作用？
• RQ5 在所研究的储层中，溶解作用与毛细管封存对整体CO2封存容量的相对贡献如何？

主要发现

• 本研究在墨西哥湾中部海域识别出多个具有显著CO2封存潜力的海上区块，其封存容量在BOEM区块级别具有重要意义。
• 岩石与流体性质之间的相关性，特别是界面张力与CO2饱和卤水黏度，显著提升了封存资源估算的准确性。
• SAS Viya支持高效的交互式可视化，使用户能够动态筛选储层条件，并对比不同储层的属性趋势。
• 毛细管封存与溶解效应被定量整合至封存潜力模型中，显著增强了资源估算的可靠性。
• 储层筛选平台成功基于标准化的地质与流体性质输入，对区块的封存潜力进行了有效排序。
• 当前项目阶段已将评估范围扩展至盐水层，同时正在持续开发适用于更广泛应用场景的预测性相关性。