자원환경지질 (Economic and Environmental Geology)

  • 제50권5호
  • /
  • Pages.363-373
  • /
  • 2017
  • /
  • 1225-7281(pISSN)
  • /
  • 2288-7962(eISSN)
대한자원환경지질학회 (The Korean Society of Economic and Environmental Geology)
권호 표지
DOI QR코드

DOI QR Code

이산화탄소 저장부지 위해성 관리를 위한 가상물리시스템 적용성 평가

Application of Cyber Physical System (CPS) for Risk Management of a CO2 Storage Site

  • 정진아 (한국지질자원연구원 Geo-ICT융합기술팀) ;
  • 박은규 (경북대학교 지구환경시스템과학부) ;
  • 전성천 ((주) 지오그린21) ;
  • 김현준 (고려대학교 BK21 플러스 에코리더양성사업단) ;
  • 윤성택 (고려대학교 지구환경과학과)
  • 투고 : 2017.10.09
  • 심사 : 2017.10.23
  • 발행 : 2017.10.28
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 연구에서는 이산화탄소 지중저장 부지관리를 위한 가상물리시스템(Cyber Physical System, CPS)의 적용성을 검토하였다. 특히, 이산화탄소 누출 예측을 위한 가상트윈으로써 서배깅 회귀분석 기법을 활용하였고, 실제 모니터링 자료를 이용하여 해당기법의 성능을 검증하였다. 검증 결과, 서배깅 회귀분석 기법이 자료 내 이상치에 대하여 견고한 추세 예측성능을 보여주었으며 장기 농도변화 예측성능 또한 우수함을 확인하였다. 또한 적은 연산자원을 활용하여 즉시적인 예측결과를 도출함에 따라 이산화탄소 누출 실시간 예측 및 위험 경보에도 적합함을 알 수 있었다. 이러한 결과들은 서배깅 회귀분석 기법을 가상트윈으로 활용하는 CPS가 이산화탄소 누출 위험을 효율적으로 관리하는데 활용 될 수 있음을 보여준다.

In the present study, adaptability of cyber-physical system (CPS) for risk management of $CO_2$ storage site is examined and the subagging regression (SBR) method is proposed as a key component of the cyber-twin to estimate the risk due to potential $CO_2$ leakage. For these purposes, $CO_2$ concentration data monitored from a controlled $CO_2$ release field experiment is employed to validate the potentialities of the SBR method. From the validation study, it is found that the SBR method has robust estimation capability by showing minimal influence from anomalous measurements, and makes stable and sound predictions for the forthcoming $CO_2$ concentration trend. In addition, the method is found to be well suited as a tool of operational risk assessment based on real-time monitoring data due to the computational efficiency. The overall results suggest that the SBR method has potential to be an important component comprising the cyber twin of CPS for risk management of $CO_2$ storage site.

키워드

참고문헌

  1. Boreham, C., Underschultz, J., Stalker, L., Kirste, D., Freifeld, B., Jenkins, C. and Ennis-King, J. (2011) Monitoring of $CO_2$ storage in a depleted natural gas reservoir: gas geochemistry from the CO2CRC Otway Project, Australia. Int. J. Greenhouse Gas Control, v.5, p.1039-1054. https://doi.org/10.1016/j.ijggc.2011.03.011
  2. Burkett, E.R., Given, D.D. and Jones L.M. (2014) Shake-Alert-an earthquake early warning system for the United States west coast. U.S. Geological Survey Fact Sheet 2014-3083. doi:10.3133/fs20143083.
  3. Byrd, R.H., Hribar, M.E. and Nocedal, J. (1999) An interior point algorithm for large-scale nonlinear programming. SIAM J. Optim., v.9(4), p.877-900. https://doi.org/10.1137/S1052623497325107
  4. Chen, N., Xiao, C., Pu, F., Wang, X., Wang, C., Wang, Z. and Gong, J. (2015) Cyber-physical geographical information service-enabled control of diverse In-situ sensors. Sensors, v.15, p.2565-2592. https://doi.org/10.3390/s150202565
  5. Eun, Y., Park, K.-J., Won, M., Park, T. and Son, S.H. (2013) Recent Trends in Cyber-Physical Systems research. Korea Inf. Sci. Soc., v.31(12), p.8-15.
  6. Feitz, A., Jenkins, C., Schacht, U., McGrath, A., Berko, H., Schroder, I., Noble, R., Kuske, T., George, S., Heath, C., Zegelin, S., Curnow, S., Zhang, H., Sirault, X., Jimenez-Berni, J. and Hortle, A. (2014) An assessment of near surface $CO_2$ leakage detection techniques under Australian conditions. Energy Procedia, v.63, p.3891-3906. https://doi.org/10.1016/j.egypro.2014.11.419
  7. Gelenbe, E. and Wu, F.-J. (2013) Future research on cyber-physical emergency management systems. Future Internet, v.5, p.336-354. https://doi.org/10.3390/fi5030336
  8. Han, W.S., Kim, K.Y., Choung, S., Jeong, J., Jung, N.H. and Park, E. (2014) Non-parametric simulations-based conditional stochastic predictions of geologic heterogeneities and leakage potentials for hypothetical $CO_2$ sequestration sites. Environ. Earth Sci., v.71(6), p.2739-2752. https://doi.org/10.1007/s12665-013-2653-z
  9. Jeong, J., Park, E., Han, W.S. and Kim, K.-Y. (2017a) A subagging regression method for estimating the qualitative and quantitative state of groundwater. Hydrogeol. J., v.25(5), p.1491-1500. https://doi.org/10.1007/s10040-017-1561-9
  10. Jeong J., Park, E., Han, W.S., Kim, K.-Y., Jun, S.-C., Choung, S., Yun, S.-T., Oh, J. and Kim, H.-J. (2017b) A predictive estimation method for carbon dioxide transport by data-driven modeling with a physicallybased data model. J. Contam. Hydrol., v.206, p.34-42. https://doi.org/10.1016/j.jconhyd.2017.09.011
  11. Lee, K.K., Lee, S.H., Yun, S.T. and Jeen, S.W. (2016) Shallow groundwater system monitoring on controlled $CO_2$ release sites: a review on field experimental methods and efforts for $CO_2$ leakage detection. Geosci. J., v.20(4), p.569-583. https://doi.org/10.1007/s12303-015-0060-z
  12. Lewicki J.L., Oldenburg C.M., Dobeck, L. and Spangler, L. (2007) Surface $CO_2$ leakage during two shallow $CO_2$ release. Geophys. Res. Lett., 34(24). L24402, doi:10.1029/2007GL032047.
  13. Nordbotten, J.M., Celia, M.A., Bachu, S. and Dahle, H.K. (2005) Semianalytical solution for $CO_2$ leakage through an abandoned well. Environ. Sci. Tech., v.39(2), p.602-611. https://doi.org/10.1021/es035338i
  14. Mei, S.W. and Chen, L.J. (2012) Research focuses and advance technologies of smart grid in recent years. Chin. Sci. Bull., v.57, p.2879-2886. https://doi.org/10.1007/s11434-012-5261-5
  15. Ogata, A. and Banks, R.B. (1961) A solution of the differential equation of longitudinal dispersion in porous media. U.S. Geological Survey Professional Paper, No. 411-A.
  16. Oldenburg, C.M., Lewicki, J.L., Dobeck, L. and Spangler, L. (2010) Modeling Gas Transport in the Shallow Subsurface During the ZERT $CO_2$ Release Test. Trans. Porous Media, v.82(1), p.77-92. https://doi.org/10.1007/s11242-009-9361-x
  17. Potra, F.A. and Wright, S.J. (2000) Interior-point methods. J. Comp. Appl. Math., v.124(1), p.281-302. https://doi.org/10.1016/S0377-0427(00)00433-7
  18. Reusen, I., Lewyckyj, N., Adreaensen, S., Biesenmans, J., Everaerts, J. and Kempenaers, S. (2008) Near-realtime forest fires monitoring system: case study with a manned aerial vehicle within the OSIRIS project, WIT Trans. Ecol. Environ., v.119, p.145-152.
  19. Smart System. (2012) Cyber Physical Systems: situation analysis of current trends, technologies, and challenges. Technical Report. National Institute of Standards and Technology. Columbia. Maryland. 67p.
  20. Strazisar, B.R., Wills, A.W., Diehl, J.R., Hammack, R.W. and Veloski, G.A. (2009) Near-surface monitoring for the ZERT shallow $CO_2$ injection project. Int. J. Greenhouse Gas Control, v.3, p.736-744. https://doi.org/10.1016/j.ijggc.2009.07.005
  21. Smith, K.L., Steven, M.D., Jones, D.G., West, J.M., Coombs, P., Green, K.A., Barlow, T.S., Breward, N., Gwosdz, S., Kruger, M., Beaubien, S.E., Annunziatellis, A., Graziani, S. and Lombardi, S. (2013) Environmental impacts of $CO_2$ leakage: recent results from the ASGARD facility, UK. Energy Procedia, v.37, p.791-799. https://doi.org/10.1016/j.egypro.2013.05.169
  22. Tang, L.-A., Yu, X., Kim, S., Gu, Q., Han, J., Leung, A. and La Porta, T. (2013) Trustworthiness analysis of sensor data in cyber-physical systems. J. Comp. Sys. Sci., v.79, p.383-401. https://doi.org/10.1016/j.jcss.2012.09.012
  23. Wang, Z., Song, H., Watkins, D.W., Ong, K.G., Xue, P. Yang, Q. and Shi, X. (2015) Cyber-physical systems for water sustainability: challenges and opportunities. IEEE Commun. Mag., v.53(5), p.216-222. https://doi.org/10.1109/MCOM.2015.7105668
  24. Zheng, L., Apps, J.A., Spycger, N., Birkholzer, J.T., Kharaka, Y.K., Thordsen, J., Beers S.R., Herkelrath, W.N., Kakouros, E. and Trautz, R.C. (2012) Geochemical modeling of changes in shallow groundwater chemistry observed during the MSU-ZERT $CO_2$ injection experiment. Int. J. Greenhouse Gas Control, v.7, p.202-217. https://doi.org/10.1016/j.ijggc.2011.10.003