CMG COLLABORATIVE RESEARCH: Advanced Computational Models for Geological Storage of Carbon Dioxide

CMG 合作研究：二氧化碳地质封存的高级计算模型

• 批准号: 0934722
• 负责人: Michael Celia
• 金额: $ 35万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-10-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0934722&HistoricalAwards=false
• 关键词: CMG; COLLABORATIVE; RESEARCH; Advanced; Computational

Geological storage of captured carbon dioxide is an important part of an overall carbon capture and storage (CCS) strategy to reduce anthropogenic emissions of CO2. Mathematical models to describe geological storage involve partial differential equations for multiphase, multicomponent mass and energy transport in porous media, augmented by nonlinear material-specific constitutive equations and equations of state. These governing equations must be solved over large three-dimensional domains, at the field scale or even the full basin-wide scale, and over time periods of hundreds to thousands of years. These systems exhibit potentially large spatial variations over multiple length scales, and may involve large uncertainties in some of the key parameters, especially when leakage of CO2 or leakage of displaced brine is considered. The importance of leakage estimation, coupled with the large uncertainty in parameters associated with leakage, implies that a Monte Carlo type of approach is needed. This, in turn, implies that efficient computational tools are essential. This proposal focuses on the development and analysis of a set of new modeling and simulation approaches for large-scale injection and subsequent transport of carbon dioxide, including potential leakage along concentrated flow paths such as leaky wells. The objectives of the proposed research include (i) to develop new Eulerian-Lagrangian methods for multiphase multicomponent flow and reactive transport with application to storage of carbon dioxide; (ii) to embed the Eulerian-Lagrangian methods in a multi-scale hybrid framework to simulate large-scale transport as well as leakage along concentrated pathways; and (iii) to develop and analyze new, highly efficient stochastic approaches to deal with the large uncertainties inherent in the storage problem of carbon dioxide. In combination, these new computational approaches will allow for large-scale simulation of CO2 injection, migration, and possible leakage across a wide range of domains and applications.Anthropogenic emissions of carbon dioxide continue to increase the atmospheric concentration of carbon dioxide. The current concentration is the highest atmospheric concentration for at least the last 650,000 years. Current consensus is that such increases in atmospheric carbon dioxide are leading to global warming of the earth, with wide-ranging environmental implications. The carbon problem is arguably the most important environmental problem of the 21st century, and technological solutions are the only hope to solve the problem. One of the most promising technical solutions is carbon capture and geological storage. This proposal focuses on development of new computer simulation approaches that will allow the very large simulations required to properly analyze the geological storage option, including detailed risk assessment analysis with a focus on fluid leakage from the injection formation to other subsurface formations or to the atmosphere. This work will thereby have potentially wide impact on both technological and policy decisions associated with geological storage of captured CO2. Furthermore, the results of this work will be applicable to a wide range of other physical systems involving subsurface fluid movement, including groundwater contamination problems as well as oil and gas recovery. The proposed research activities will provide advanced interdisciplinary training to graduate and undergraduate students, including undergraduate students from the historically black South Carolina State University. All of these activities will have broad and long-lasting impacts and contribute directly to the intellectual infrastructure of the nation while addressing one of the grand environmental challenges for the 21st century.

捕获的二氧化碳的地质储存是减少人为二氧化碳排放的整体碳捕获和储存(CCS)战略的重要组成部分。描述地质储存的数学模型包括多孔介质中多相、多组分的质量和能量传输的偏微分方程组，以及与材料有关的非线性本构方程和状态方程。这些控制方程必须在大的三维域、场尺度甚至整个盆地尺度上求解，并在数百至数千年的时间段内求解。这些系统在多个长度尺度上表现出潜在的巨大空间变化，并且在一些关键参数中可能涉及很大的不确定性，特别是在考虑二氧化碳泄漏或置换盐水泄漏的情况下。泄漏估计的重要性，加上与泄漏有关的参数的巨大不确定性，意味着需要一种蒙特卡洛式的方法。这反过来又意味着高效的计算工具是必不可少的。这项提议的重点是开发和分析一套新的建模和模拟方法，用于二氧化碳的大规模注入和随后的运输，包括沿泄漏井等集中流动路径的潜在泄漏。拟议研究的目标包括：(1)开发多相多组分流动和反应传输的新的欧拉-拉格朗日方法，并将其应用于二氧化碳的储存；(2)将欧拉-拉格朗日方法嵌入多尺度混合框架中，以模拟大规模的传输以及集中路径上的泄漏；以及(3)开发和分析新的、高效的随机方法，以处理二氧化碳储存问题中固有的巨大不确定性。这些新的计算方法结合在一起，将允许在广泛的领域和应用中大规模模拟二氧化碳的注入、迁移和可能的泄漏。人类排放的二氧化碳继续增加大气中二氧化碳的浓度。目前的浓度是至少过去65万年来最高的大气浓度。目前的共识是，大气中二氧化碳的这种增加正在导致地球的全球变暖，对环境产生广泛的影响。碳问题可以说是21世纪最重要的环境问题，而技术解决方案是解决这一问题的唯一希望。最有前景的技术解决方案之一是碳捕获和地质封存。这项提议的重点是开发新的计算机模拟方法，以便进行适当分析地质储存方案所需的超大型模拟，包括详细的风险评估分析，重点是从注入地层到其他地下地层或大气的流体泄漏情况。因此，这项工作可能会对与捕获的二氧化碳的地质储存有关的技术和政策决策产生广泛影响。此外，这项工作的结果将适用于涉及地下流体运动的广泛其他物理系统，包括地下水污染问题以及石油和天然气回收。拟议的研究活动将为研究生和本科生提供高级跨学科培训，包括来自历史上一直是黑人的南卡罗来纳州立大学的本科生。所有这些活动都将产生广泛和持久的影响，并直接促进国家的知识基础设施，同时应对21世纪的重大环境挑战之一。