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: 0934747
• 负责人: Hong Wang
• 金额: $ 30万
• 依托单位: University South Carolina Research Foundation
• 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=0934747&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.

对捕获的二氧化碳进行地质封存是减少人为CO2排放的总体碳捕获和封存战略的重要组成部分。描述地质储存的数学模型涉及多孔介质中多相、多组分质量和能量输运的偏微分方程，并由非线性材料特定本构方程和状态方程增强。这些控制方程必须在大的三维域上求解，在野外尺度甚至整个盆地尺度上，在数百到数千年的时间段内。这些系统在多个长度尺度上表现出潜在的大的空间变化，并且可能涉及一些关键参数的大的不确定性，特别是当考虑CO2泄漏或置换盐水泄漏时。渗漏估计的重要性，加上与渗漏有关的参数的很大不确定性，意味着需要一种蒙特卡罗类型的方法。这反过来又意味着有效的计算工具是必不可少的。本提案的重点是开发和分析一套新的建模和模拟方法，用于大规模注入和随后的二氧化碳输送，包括沿沿着集中流动路径的潜在泄漏，如泄漏威尔斯。本研究的目标包括：（i）开发新的欧拉-拉格朗日方法，用于多相多组分流动和反应输运，并应用于二氧化碳的储存;（ii）将欧拉-拉格朗日方法嵌入多尺度混合框架，以模拟大尺度输运以及沿沿着集中路径的泄漏;和（iii）开发和分析新的，高效的随机方法来处理在二氧化碳的存储问题中固有的大的不确定性。结合起来，这些新的计算方法将允许大规模模拟CO2注入，迁移和可能的泄漏在广泛的领域和应用。人为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65万年来大气浓度的最高值。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，具有广泛的环境影响。碳问题可以说是21世纪世纪最重要的环境问题，技术解决方案是解决问题的唯一希望。最有前途的技术解决方案之一是碳捕获和地质储存。该提案侧重于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。因此，这项工作将对与捕获的CO2的地质储存有关的技术和政策决定产生潜在的广泛影响。此外，这项工作的结果将适用于广泛的其他物理系统，涉及地下流体运动，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先进的跨学科培训，包括来自历史上黑人的南卡罗来纳州州立大学的本科生。所有这些活动都将产生广泛和持久的影响，并直接有助于国家的知识基础设施，同时应对21世纪世纪的重大环境挑战之一。