IUCRC Planning Grant University of Southern California: Center for CO2 Storage Modeling, Analytics, and Risk Reduction Technologies (CO2-Smart)

IUCRC 规划拨款南加州大学：二氧化碳封存建模、分析和风险降低技术中心 (CO2-Smart)

• 批准号: 2231665
• 负责人: Behnam Jafarpour
• 金额: $ 2万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-15 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2231665&HistoricalAwards=false
• 关键词: IUCRC; Planning; Grant; University; Southern

Geologic CO2 storage offers a viable option for reducing CO2 in the atmosphere. Successful implementation of projects in this area hinges on scientific and technological advances in multi-physics flow modeling, subsurface monitoring data analytics, and risk assessment and mitigation strategies. This Industry-University Collaborative Research Center for CO2 Storage Modeling, Monitoring, Analytics, and Risk Reduction Technologies (CO2-SMART) aims to create a synergistic research program to accelerate the development, adaptation, and deployment of novel AI-enriched technologies to enable efficient and safe implementation of the geologic storage of CO2. The prospective members of the Center include the main CO2-producing sectors of the industry, including upstream and downstream oil and gas companies, chemical and petrochemical companies, as well as power plants and utility companies. The Center will train the next generation of engineers and scientists as future leaders for implementing and managing large-scale GCS projects. This will help to address one of the most pressing challenges of our time with broad and significant societal, energy security, and public health impacts. The Center will be guided by an industry advisory board of Center members who will assist it in maintaining its focus on addressing the emerging industry challenges for successful implementation of CO2 storage in the subsurface. The technical focus of the Center will be on integrating recent advances in multi-physics modeling and simulation, subsurface monitoring data acquisition, and modern AI and data science algorithms to develop reliable technologies for safe and sustainable subsurface geologic storage of CO2. The emerging AI-based technologies are bound to replace the traditional labor-intensive modeling workflows with efficient automated platforms, where big data analytics is used not only to enhance data processing, visualization, and management, but also to provide advanced physics-informed predictive analytics, anomaly/fault detection, and decision support capabilities for real-time operation. The Center will focus on several key research and development thrust areas, including (1) modeling and characterization of subsurface fluid, rock, and fracture properties, as well as the parameters pertaining to the underlying multi-physics processes, (2) multiscale and multi-physics modeling and prediction of subsurface flow processes, (3) high-resolution dynamic characterization and imaging using multi-physics monitoring data modalities and advanced deep learning architectures, (4) modern risk assessment and uncertainty quantification technologies pertaining to complex multi-physics systems, and (5) optimization and control of the injected CO2 plume movement under risk and uncertainty. Developing and advancing state-of-the-art technologies in these research areas will directly benefit the industry members and serve the general industrial and scientific communities, as well as the public at large.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

地质二氧化碳存储为减少大气中的二氧化碳提供了可行的选择。该领域的项目成功实施取决于多物理流程建模，地下监视数据分析以及风险评估和缓解策略的科学和技术进步。该行业 - 大学合作研究中心用于CO2存储建模，监测，分析和降低风险技术（CO2-SMART）旨在创建一个协同的研究计划，以加快新型AI-Enched技术的开发，适应和部署，以实现CO2的地球储存的有效和安全实施CO2的地质存储。该中心的潜在成员包括该行业的主要二氧化碳产业，包括上游和下游石油和天然气公司，化学和石化公司以及发电厂和公用事业公司。该中心将培训下一代工程师和科学家作为实施和管理大规模GCS项目的未来领导者。这将有助于应对当时最紧迫的挑战之一，并具有广泛而重要的社会，能源安全和公共卫生的影响。该中心将由中心成员的行业顾问委员会指导，该委员会将协助其专注于解决新兴行业的挑战，以成功实施地下的二氧化碳存储。 该中心的技术重点将是整合多物理建模和模拟，地下监视数据获取以及现代AI和数据科学算法的最新进展，以开发可靠的技术，以确保CO2的安全可持续的地下地质存储。新兴的基于AI的技术必定会用有效的自动化平台替代传统的劳动密集型建模工作流，其中大数据分析不仅用于增强数据处理，可视化和管理，还可以为实时运行提供高级物理学知识的预测分析，异常/故障/故障检测和决策支持能力。该中心将着重于几个关键的研发推力区域，包括（1）地下流体，岩石和断裂属性的建模和表征，以及与基础多物理过程有关的参数，（2）多尺度和多物理学和多物理学模型和高度跨度的模型，（3）高度跨度的模型和高度差异性图表，（3）（3）（3）（3）（3）（3）（3）（3）（3）体系结构，（4）与复杂多物理系统有关的现代风险评估和不确定性量化技术，以及（5）在风险和不确定性下对注射的CO2羽流运动的优化和控制。这些研究领域的开发和发展最先进的技术将直接使行业成员受益，并为一般的工业和科学社区以及广大公众提供服务。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的审查标准通过评估来进行评估的。