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.

Agency
National Science Foundation (NSF)
Institute
Division of Earth Sciences (EAR)
Type
Standard Grant (Standard)
Application #
0934722
Program Officer
Robin Reichlin
Project Start
Project End
Budget Start
2009-10-01
Budget End
2013-09-30
Support Year
Fiscal Year
2009
Total Cost
$350,000
Indirect Cost
Name
Princeton University
Department
Type
DUNS #
City
Princeton
State
NJ
Country
United States
Zip Code
08540