The present study focuses on understanding the leakage potentials of the stored supercritical CO2 plume through caprocks generated in geostatistically created heterogeneous media. For this purpose, two hypothetical cases with different geostatistical features were developed, and two conditional geostatistical simulation models (i.e., sequential indicator simulation or SISIM and generalized coupled Markov chain or GCMC) were applied for the stochastic characterizations of the heterogeneities. Then, predictive CO2 plume migration simulations based on stochastic realizations were performed and summarized. In the geostatistical simulations, the results from the GCMC model showed better performance than those of the SISIM model for the strongly non-stationary case, while SISIM models showed reasonable performance for the weakly non-stationary case in terms of low-permeability lenses characterization. In the subsequent predictive simulations of CO2 plume migration, the observations in the geostatistical simulations were confirmed and the GCMC-based predictions showed underestimations in CO2 leakage in the stationary case, while the SISIM-based predictions showed considerable overestimations in the non-stationary case. The overall results suggest that: (1) proper characterization of low-permeability layering is significantly important in the prediction of CO2 plume behavior, especially for the leakage potential of CO2 and (2) appropriate geostatistical techniques must be selectively employed considering the degree of stationarity of the targeting fields to minimize the uncertainties in the predictions.
Bibliographical noteFunding Information:
Acknowledgments This work was jointly supported by ‘‘Technology development for CO2 geological storage demonstration through participating in the Canadian projects (2011T100100331)’’ of the Korea National Oil Corporation (KNOC) and ‘‘Block funding projects (GP2012-030)’’ of Korea Institute of Geoscience and Mineral Resources (KIGAM) transferred from the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grants.
All Science Journal Classification (ASJC) codes
- Global and Planetary Change
- Environmental Chemistry
- Water Science and Technology
- Soil Science
- Earth-Surface Processes