Nanoscale Control of Geologic CO2 (NCGC)

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Nanoscale Controls on Geologic CO2 (NCGC)

DOE-SC-Basic Energy Sciences

The mission for the Center for Nanoscale Controls on Geologic CO2 (NCGC) is to enhance the performance and predictability of subsurface storage systems by understanding the molecular and nanoscale origins of CO2 trapping processes, and developing computational tools to translate to larger-scale systems. One of 32 U.S. Department of Energy (DOE) Energy Frontier Research Centers (EFRC), the NCGC is a collaborative effort led by Lawrence Berkeley National Laboratory (LBNL), Oak Ridge National Laboratory (ORNL), Ohio State University, Princeton University, Purdue University, Stanford University, and Washington University in St. Louis.

The vision for the Center is to understand, predict, and enhance the performance of underground CO2 storage systems. Specific goals are to produce (1) a next-generation understanding of the nanoscale-to-mesoscale chemical-mechanical behavior of shale (a critical material for a low-carbon energy future), (2) quantitative models for the efficiency of reservoir capillary trapping and its effect on solution and mineral trapping, (3) methods to predict mineralogical trapping, and (4) theory, experimental data, and computational tools to allow nanoscale effects to be translated to mesoscale and continuum-scale model equations and parameters.

The research of the NCGC is divided into three Thrust Areas that address

  1. Sealing effectiveness of fractured shales
  2. Reservoir processes that control secondary trapping (capillary, dissolution, and mineral trapping)
  3. Developing the computational tools and insight necessary to model mesoscale couplings along with material properties and dynamics.

Systems of study will include well-characterized natural rock and mineral samples, and synthetic materials fabricated by established methods and methods to be developed. A key aspect of the Center’s approach is to bring multiple characterization methods, and diverse complementary expertise, to bear on the same experiments, and to integrate modeling and simulation with experiments.