Quantitative analysis of the numerical simulation uncertainties from geological models in CO2 geological storage: A case study of Shenhua CCS project

The intensifying global climate change has prompted the imperative implementation of CO₂ capture and storage (CCS) projects as a mitigation strategy. Ensuring the safety and reliability of these projects requires meticulous validation, including the establishment of geological models and conducting numerical simulations. In CO₂ geological storage initiatives, the limitation of well data during the initial stages leads to data deficiency. This scarcity compromises the precision of geological and numerical models, hindering their ability to accurately depict actual subsurface conditions. Meanwhile, parameters related to heterogeneity significantly also impact storage effectiveness and safety. This study addresses these challenges by utilizing the Shenhua CCS demonstration project as a case study. Various heterogeneous parameters are selected, and local and global sensitivity analysis methods are subsequently introduced to determine the ranges and sequences of these parameters in numerical simulations. The simulation results can aid in assessing the influence of various heterogeneous parameters on the CO₂ plume and bottom hole pressure. The study establishes the importance ranking of various heterogeneous parameters under different temporal and spatial conditions through sensitivity analysis. The findings reveal the following key points:

1. During the small-scale injection period, the CO₂ plume is particularly sensitive to variations in net-to-gross and vertical permeable properties.

2. During and after larger-scale injections, the net-to-gross significantly impacts plume evolution, while bottom hole pressure is predominantly influenced by variations in vertical permeable properties.

3. Both the CO₂ plume and well bottom pressure are primarily affected by changes in sand body morphologies, especially at low net-to-gross scenarios.

These conclusions assist in prioritizing the collection of critical parameter data in CCS projects, facilitating the establishment of more precise and reliable geological and numerical simulation models. The heightened accuracy and reliability of these models contribute to improving their predictive capabilities, ultimately guiding engineering practices.