Global sensitivity analysis of CO2 storage in fractured aquifers via computer experiments

Abstract

• Accelerated CO 2 storage sensitivity analysis via Computer Experiments as surrogate modes. • Rigorous dynamic models use to model non-reactive CO 2 storage mechanisms, inspired by the Teapot Dome in Wyoming dataset. • Demonstration that a network of connected fractures in an eolian sandstone shifts the importance of CO 2 storage controlling parameters. In this work, we use the “Design and Analysis of Computer Experiments” (DACE) technique to analyze the sensitivity of CO 2 storage in fractured aquifers. The aquifer static or geogical model was inspired by the Tensleep formation at Teapot Dome, a potential CO 2 storage target in Wyoming. The CO 2 storage performance in aquifers is comprehensively simulated in our dynamic model by considering all the trapping mechanisms, except for mineralization, i.e. structural, dissolution and residual, as well as local capillary trapping. Operational strategies are investigated to achieve an effective trade-off between higher CO 2 trapping efficiency and delayed CO 2 breakthrough at producers. The effect of natural fractures is explored by running single-porosity, dual-permeability and dual-porosity models. Results show that different models produce significantly different trapping efficiencies, which indicates that natural fractures and their type impact the CO 2 storage practice appreciably. To carry out the global sensitivity analysis, two 100-point computer experiments were designed using the modified space-filling method considering a bottom aquifer, matrix permeability and porosity, fracture permeability and spacing, and water Total Dissolved Solids (TDS). Results show that an active bottom aquifer reduces trapping efficiency noticeably. In addition, dissolution trapping becomes the dominant trapping mechanism. The variability of CO 2 trapping efficiency is explained primarily by fracture permeability, then depth, and finally matrix permeability. In contrast, in the absence of aquifer drive, the variability is almost completely explained by matrix permeability. Furthermore, our results provide guidance to the collection of information as to reduce the most dominant uncertainties.