Breaking ground: Reducing the risk of injecting greenhouse gases underground

Matthew GrasingerAs a participant of the Mickey Leland Energy Fellowship (MLEF) program, Matthew Grasinger helped reduce the risks associated with geological carbon sequestration. (Photo courtesy of Robert Zupan)

As a participant of the Mickey Leland Energy Fellowship (MLEF) program, Matthew Grasinger helped reduce the risks associated with geological carbon sequestration. This technique is part of carbon capture and sequestration, which decreases the emission of greenhouse gases into the atmosphere by capturing the gases from their emission source and injecting the gases into deep underground geological formations. By developing computational methods to improve the selection process of potential sites for geological carbon sequestration, Grasinger’s work can be applied to analyze and reduce the potential risks associated with the technique.

During his fellowship, Grasinger researched at the Los Alamos National Laboratory’s Earth and Environmental Science Division where he investigated how to mitigate the risks that accompany geological carbon sequestration. Grasinger’s research demonstrated that CO2 site selection must be done with care to reduce the potential for CO2 leakage, which can migrate into groundwater or up into the atmosphere, and to lower the prospect for rock formation fracture and slip, which can lead to earthquakes.

One of the challenges in deciding among numerous potential sites for geological CO2 sequestration is the uncertainty in the subsurface physical processes and the related physical parameters. Subsurface properties such as permeability, porosity, and rock density are prohibitively difficult to measure and can vary greatly, even with short distances or changes in depth.

Grasinger addressed these issues through applying the Bayesian-Information-Gap Decision Theory (BIG-DT) framework to site selection for CO2 well injections. The BIG-DT framework is a decision-making method for situations with varying degrees and types of uncertainty. BIG-DT is implemented in the open-source code Model Analyses & Decision Support (MADS). By coupling MADS with PFLOTRAN, a code for subsurface flow and reactive transport, Grasinger created a way to model the CO2 injection process and determine the robustness of a possible injection site against failure.

Applying computer methods in decision analysis for selecting CO2 injection sites will make geological carbon sequestration safer, which protects both people and the environment. Geological carbon sequestration is a crucial way in which the environmental impact of fossil fuels can be reduced while fossil fuels continue to be used. The U.S. Department of Energy estimates that somewhere from 1,800 to 20,000 billion tons of CO2 can be stored below ground in the United States alone.

“CO2 sequestration gives us the potential to continue to use fossil fuels until we develop cleaner energy technologies, while keeping the environmental impact of fossil fuels to a minimum. This research aims to accomplish CO2 sequestration in an environmentally responsible way, because if it is done at an inappropriate site, CO2 can induce earthquakes, contaminate ground water, or migrate into the atmosphere,” said Grasinger.

When asked about his overall impression of the fellowship, Grasinger replied, “Los Alamos has some of the most talented scientists in the world, and researching there gave me the opportunity to learn as much as I possibly could from them, plus it gave me an opportunity to see a part of the country I had never seen before.”

Not only did he enjoy the location and working alongside talented scientists, he said that he appreciated the chance to develop new skills that would benefit him throughout his career. Grasinger is currently pursuing his doctoral degree in civil engineering at the University of Pittsburgh.

The Mickey Leland Energy Fellowship program is administered through the U.S. Department of Energy’s Oak Ridge Institute for Science and Education (ORISE), which is managed for DOE by ORAU.