Risk-averse agents benefit from collaboration in CO2 storage without pressure communication, while belief distributions that mix physical uncertainty with maximum-entropy priors remain informative even when pressure communication creates high variability in feasible injection rates.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
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Numerical tests indicate that a stochastic Galerkin discretization with embedded slabwise space-time finite elements and GMRES-GMG solvers outperforms Monte-Carlo sampling for random parabolic problems in convergence and algebraic solver statistics.
citing papers explorer
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Risk sharing in cooperative game models for CO$_2$ storage with uncertain geology and pressure competition
Risk-averse agents benefit from collaboration in CO2 storage without pressure communication, while belief distributions that mix physical uncertainty with maximum-entropy priors remain informative even when pressure communication creates high variability in feasible injection rates.
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Stochastic Galerkin and Monte-Carlo methods for parabolic problems: Numerical performance of variational matrix-free approximations
Numerical tests indicate that a stochastic Galerkin discretization with embedded slabwise space-time finite elements and GMRES-GMG solvers outperforms Monte-Carlo sampling for random parabolic problems in convergence and algebraic solver statistics.