Modeling evaluation of physiochemical processes controlling gas migration in shallow groundwater systems

Abstract

Gases may be released into shallow groundwater systems during energy development and geological carbon storage (commonly referred to as gas migration, GM) and can result in greenhouse gas emissions, safety concerns, and the reduction of groundwater quality. The physiochemical processes occurring during GM, including gas release, movement, partitioning, and dissolved-phase transport in the saturated groundwater zone, are difficult to characterize and model; however, modeling is important to develop strategies for detecting and monitoring GM and formulate conceptual models to describe GM at impacted sites. In this study, a previously developed numerical model, which coupled macroscopic invasion percolation (macro-IP) and multicomponent mass transfer, was enhanced to simulate gas releases in the shallow subsurface. Evaluation of the effects of the coupled physiochemical processes was performed by comparing model simulations to previously conducted bench-scale gas injection experiments. Results show that gas flow is highly sensitive to the entry pressures assigned within the model domain and the critical gas saturation (Sg,crit) used to model gas-water flow based on macro-IP; however, mass transfer and the resulting domain-scale dissolved-gas transport were relatively insensitive to these parameters. Multicomponent mass transfer, considering not only the partitioning of the released gas, but also the dissolved background gases ubiquitous in shallow groundwater, was vitally important to simulate dissolution and the resulting free-phase gas distribution within the experimental systems. The use of the local equilibrium assumption for gas-water mass transfer could not consistently describe the experimental observations. Overall, the modeling evaluation performed in this study provides improved understanding of the key processes controlling GM in the shallow subsurface and will advance efforts including up-scaling and scenario testing to accurately quantify the environmental impacts of GM.