Fast assessment of CO2 plume characteristics using a connectivity based proxy

Ahmed, 2006, 354 Alnes, 2011, Results from Sleipner gravity monitoring: Updated density and temperature distribution of the CO2 plume, Energy Procedia, 10th International Conference on Greenhouse Gas Control Technologies, 4, 5504 Ballin, 1992, Prediction of uncertainty in reservoir performance forecast, J. Can. Pet. Technol., 31, 10.2118/92-04-05 Bandilla, 2014, Impact of model complexity on CO2 plume modeling at Sleipner, Energy Procedia, 63, 3405, 10.1016/j.egypro.2014.11.369 Bhowmik, 2014, Improved particle tracking proxy for assessing plume migration during geologic sequestration, Energy Procedia, 12th International Conference on Greenhouse Gas Control Technologies, GHGT-12, 63, 3853 Boucher, 2010 Bridge, 1979, A simulation model of alluvial stratigraphy, Sedimentology, 26, 617, 10.1111/j.1365-3091.1979.tb00935.x Carruthers, 2003, 21 Cavanagh, 2013, Benchmark calibration and prediction of the sleipner CO2 plume from 2006 to 2012, Energy Procedia, GHGT-11, 37, 3529, 10.1016/j.egypro.2013.06.246 CMG, 2012 Court, 2012, Applicability of vertical-equilibrium and sharp-interface assumptions in CO2 sequestration modeling, Int. J. Greenh. Gas Control, 10, 134, 10.1016/j.ijggc.2012.04.015 Darcis, 2011, Sequential model coupling for feasibility studies of CO2 storage in deep saline aquifers, Oil Gas Sci. Technol.—Rev. d’IFP Energies Nouv., 66, 93, 10.2516/ogst/2010037 De Lima, 2012, Assisted history- matching for the characterization and recovery optimization of fractured reservoirs using connectivity analysis, Soc. Petrol. Eng. Deutsch, 1996, Improved reservoir management through ranking stochastic reservoir models, Soc. Petrol. Eng. Deutsch, 1996, Hierarchical object-based stochastic modeling of fluvial reservoirs, Math. Geol., 28, 857, 10.1007/BF02066005 Donnez, 2007, 285 Eigestad, 2009, Geological modeling and simulation of CO2 injection in the Johansen formation, Comput. Geosci., 13, 435, 10.1007/s10596-009-9153-y Fredman, 1987, Fibonacci heaps and their uses in improved network optimization algorithms, J. ACM, 34, 596, 10.1145/28869.28874 Guo, 2014, A vertically integrated model with vertical dynamics for CO2 storage, Water Resour. Res., 50, 6269, 10.1002/2013WR015215 Hird, 1998, Quantification of reservoir connectivity for reservoir description applications, SPE Reserv. Eval. Eng., 1, 10.2118/30571-PA Hirsch, 1999, Graph theory applications to continuity and ranking in geologic models, Comput. Geosci., 25, 127, 10.1016/S0098-3004(98)00116-2 Issautier, 2014, Impacts of fluvial reservoir heterogeneity on connectivity: implications in estimating geological storage capacity for CO2, Int. J. Greenh. Gas Control, 20, 333, 10.1016/j.ijggc.2013.11.009 Jensen, 2000, 136 Jeong, 2013, Uncertainty quantification of CO2 plume migration using static connectivity of geologic features, Energy Procedia, 37, 3771, 10.1016/j.egypro.2013.06.273 Keogh, 2007, The development of fluvial stochastic modelling in the Norwegian oil industry: a historical review, subsurface implementation and future directions, Sediment. Geol., 202, 249, 10.1016/j.sedgeo.2007.05.009 Kovscek, 2005, Geologic storage of carbon dioxide and enhanced oil recovery. I. Uncertainty quantification employing a streamline based proxy for reservoir flow simulation, Energy Convers. Manag., 46, 1920, 10.1016/j.enconman.2004.09.008 Kulkarni, 2001, A streamline approach for integrating transient pressure data into high-resolution reservoir models, SPE J., 6, 273, 10.2118/74135-PA Lie, 2011, Open-source MATLAB implementation of consistent discretisations on complex grids, Comput. Geosci., 16, 297, 10.1007/s10596-011-9244-4 Mathias, 2009, Approximate solutions for pressure buildup during CO2 injection in brine aquifers, Transp. Porous Media, 79, 265, 10.1007/s11242-008-9316-7 Nilsen, 2011, Field-case simulation of CO2 plume migration using vertical-equilibrium models, Energy Procedia, 4, 3801, 10.1016/j.egypro.2011.02.315 Nordbotten, 2005, Injection and storage of CO2 in deep saline aquifers: analytical solution for CO2 plume evolution during injection, Transp. Porous Media, 58, 339, 10.1007/s11242-004-0670-9 Pardo- Igúzquiza, 2003, CONNEC3D: a computer program for connectivity analysis of 3D random set models, Comput. Geosci., 29, 775, 10.1016/S0098-3004(03)00028-1 Remy, 2011 Scheidt, 2009, Representing spatial uncertainty using distances and kernels, Math. Geosci., 41, 397, 10.1007/s11004-008-9186-0 Senel, 2013, CO2 injection in a saline formation: pre- injection reservoir modeling and uncertainty analysis for Illinois Basin–Decatur project, Energy Procedia, 37, 4598, 10.1016/j.egypro.2013.06.368 Sethian, 1996, A fast marching level set method for monotonically advancing fronts, Proc. Natl. Acad. Sci., 93, 1591, 10.1073/pnas.93.4.1591 Sharifi, 2014, 2014. Dynamic Ranking of Multiple Realizations By Use of the Fast-Marching Method, SPE J., 10.2118/169900-PA Singh, 2010, Reservoir Modeling of CO2 Plume Behavior Calibrated Against Monitoring Data From Sleipner, Norway, Society of Petroleum Engineers. Thiele, 2015, Discussion of Streamline Simulation: A Technology Update, J. Pet. Technol., 53, 26, 10.2118/0501-0026-JPT Vilarrasa, 2013, Semianalytical Solution for CO2 Plume Shape and Pressure Evolution During CO2 Injection in Deep Saline Formations, Transp. Porous Media, 97, 43, 10.1007/s11242-012-0109-7 Willhite, 1986 Xie, 2015, Depth of Investigation and Depletion in Unconventional Reservoirs With Fast-Marching Methods, SPE J., 10.2118/154532-PA Zhang, 2013, Density-driven enhanced dissolution of injected CO2 during long-term CO2 geological storage, J. Earth Syst. Sci., 122, 1387, 10.1007/s12040-013-0342-7