High-performance supercomputing as a risk evaluation tool for geologic carbon dioxide storage

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Numerical modelling is a vital tool for predicting the behavior and fate of CO2 in reservoirs as well as its impacts on subsurface environments. Recently, powerful numerical codes that are capable of solving coupled complex processes of physics and chemistry required for such modeling works have been developed. However they are often computationally demanding for solving the complex non-linear models in sufficient spatial and temporal resolutions. Geological heterogeneity and uncertainties further increase the challenges in modeling work, because they may necessitate stochastic modeling with multiple realizations. There is clearly a need for high-performance computing. In this study, we implemented TOUGH2-MP code (a parallel version of multi-phase flow simulator TOUGH2) on two different types (vector- And scalar-type) of world-class supercomputers with tens of thousands of processors in Japan. The parallelized code generally exhibited excellent performance and scalability after adequate tune-ups of the code. Using the code and the supercomputers, we have been performed several computationally demanding simulations. In this paper, we present the performances of parallel computation of the code measured on the two supercomputers. Then the following two examples are presented: 1) a highly heterogeneous high-resolution model, representing irregular nature of sand/shale distribution; 2) "Dissolution Diffusion Convection Process", which is expected to significantly enhance the dissolution trapping. Through the above two examples, it is illustrated that the spatial resolution of numerical model can critically change the evaluation of the effectiveness of CO2 trapping mechanisms, demonstrating the necessity of supercomputing techniques for evaluating these risks more accurately.




Yamamoto, H., Nanai, S., Zhang, K., Audigane, P., Chiaberge, C., Ogata, R., … Nakajima, K. (2013). High-performance supercomputing as a risk evaluation tool for geologic carbon dioxide storage. In Energy Procedia (Vol. 37, pp. 3997–4005). Elsevier Ltd. https://doi.org/10.1016/j.egypro.2013.06.299

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