Zobrazeno 1 - 10
of 134
pro vyhledávání: '"Hamon, François"'
Autor:
Aronson, Ryan M., Tomin, Pavel, Castelletto, Nicola, Hamon, François P., White, J. A., Tchelepi, Hamdi A.
We study in detail the pressure stabilizing effects of the non-iterated fixed-stress splitting in poromechanical problems which are nearly undrained and incompressible. When applied in conjunction with a spatial discretization which does not satisfy
Externí odkaz:
http://arxiv.org/abs/2409.16257
Deep learning surrogate modeling shows great promise for subsurface flow applications, but the training demands can be substantial. Here we introduce a new surrogate modeling framework to predict CO2 saturation, pressure and surface displacement for
Externí odkaz:
http://arxiv.org/abs/2408.10717
Fast and accurate numerical simulations are crucial for designing large-scale geological carbon storage projects ensuring safe long-term CO2 containment as a climate change mitigation strategy. These simulations involve solving numerous large and com
Externí odkaz:
http://arxiv.org/abs/2408.03452
We consider the numerical behavior of the fixed-stress splitting method for coupled poromechanics as undrained regimes are approached. We explain that pressure stability is related to the splitting error of the scheme, not the fact that the discrete
Externí odkaz:
http://arxiv.org/abs/2402.10469
This work studies the performance of a novel preconditioner, designed for thermal reservoir simulation cases and recently introduced in Roy et al. (2020) and Cremon et al. (2020), on large-scale thermal CO2 injection cases. For Carbon Capture and Seq
Externí odkaz:
http://arxiv.org/abs/2308.11892
Deep-learning-based surrogate models show great promise for use in geological carbon storage operations. In this work we target an important application - the history matching of storage systems characterized by a high degree of (prior) geological un
Externí odkaz:
http://arxiv.org/abs/2308.06341
Autor:
Lee, Chak Shing, Hamon, François P., Castelletto, Nicola, Vassilevski, Panayot S., White, Joshua A.
A full approximation scheme (FAS) nonlinear multigrid solver for two-phase flow and transport problems driven by wells with multiple perforations is developed. It is an extension to our previous work on FAS solvers for diffusion and transport problem
Externí odkaz:
http://arxiv.org/abs/2308.00125
Autor:
Ju, Xin, Hamon, François P., Wen, Gege, Kanfar, Rayan, Araya-Polo, Mauricio, Tchelepi, Hamdi A.
Deep-learning-based surrogate models provide an efficient complement to numerical simulations for subsurface flow problems such as CO$_2$ geological storage. Accurately capturing the impact of faults on CO$_2$ plume migration remains a challenge for
Externí odkaz:
http://arxiv.org/abs/2306.09648
Autor:
Sai, Ryuichi, Jacquelin, Mathias, Hamon, François P., Araya-Polo, Mauricio, Settgast, Randolph R.
Designing large-scale geological carbon capture and storage projects and ensuring safe long-term CO2 containment - as a climate change mitigation strategy - requires fast and accurate numerical simulations. These simulations involve solving complex P
Externí odkaz:
http://arxiv.org/abs/2304.11274
Comparison of nonlinear field-split preconditioners for two-phase flow in heterogeneous porous media
This work focuses on the development of a two-step field-split nonlinear preconditioner to accelerate the convergence of two-phase flow and transport in heterogeneous porous media. We propose a field-split algorithm named Field-Split Multiplicative S
Externí odkaz:
http://arxiv.org/abs/2205.05913