Simulation of CO2 Storage using a Parameterization Method for Essential Trapping Physics: FluidFlower Benchmark Study

TL;DR

This paper introduces an efficient simulation framework for CO2 storage in saline aquifers, capturing essential trapping mechanisms and validated against literature, with application to a heterogeneous benchmark model to study migration and trapping effects.

Contribution

A novel parameterization method is proposed for simulating CO2 trapping physics, enabling efficient and accurate modeling of complex processes in saline aquifers.

Findings

Good agreement with literature on convective transport dynamics

Hysteresis effect does not influence plume migration in the benchmark

Diffusion significantly enhances convective mixing and trapping

Abstract

An efficient compositional framework is developed for simulation of CO2 storage in saline aquifers during a full-cycle injection, migration and post-migration processes. Essential trapping mechanisms, including structural, dissolution, and residual trapping, which operate at different time scales are accurately captured in the presented unified framework. In particular, a parameterization method is proposed to efficiently describe the relevant physical processes. The proposed framework is validated by comparing the dynamics of gravity-induced convective transport with that reported in the literature. Results show good agreement for both the characteristics of descending fingers and the associated dissolution rate. The developed simulator is then applied to study the FluidFlower benchmark model. An experimental setup with heterogeneous geological layers is discretized into a two-dimensional computational domain where numerical simulation is performed. Impacts of hysteresis and the diffusion of CO2 in liquid phase on the migration and trapping of CO2 plume are investigated. Inclusion of the hysteresis effect does not affect plume migration in this benchmark model, whereas diffusion plays an important role in promoting convective mixing. This work casts a promising approach to predict the migration of the CO2 plume, and to assess the amount of trapping from different mechanisms for long-term CO2 storage.