Abstract

To further understand the interactions of CO2-brine-rock at geological time scales, in this study, a 1D reactive transport model of CO2 intrusion into sandstone of the Longtan Formation (P2l) in the Huangqiao area, China, was constructed based on site-specific data. The simulation time is consistent with the retention time of CO2 in the Longtan sandstone Formation and is set to 20 Ma. The reactive transport model is calibrated and revised using the measured data for sandstone samples from Well X3 (i.e., the natural analogue). By comparing the simulation results with measured data for the natural analogue, the long-term geochemical reactions are investigated. The simulation results indicate that the brine-rock interactions induced by CO2 can be roughly divided into two stages. First, susceptible minerals (e.g., chlorite, ankerite, calcite, and feldspar minerals) dissolve rapidly under acidic conditions formed by the dissolution of CO2. The precipitation of siderite is facilitated by the dissolution of ankerite and chlorite. Smectite-Ca and dawsonite precipitate due to the dissolution of anorthite and albite, respectively. Dawsonite begins to convert into smectite-Na when albite is completely dissolved. As the reactions continue, intermediate products (i.e., illite, smectite-Na, and smectite-Ca) generated in the first stage become the reactants and subsequently react with CO2 and brine. These three clay minerals are not stable under acidic conditions and transform into kaolinite and paragenetic quartz in the later stage of reaction. Comparing the simulation results of the Base Case with the measured data for the natural analogue and inspired by previous studies, the scour of kaolinite is supposed to have occurred in this region and is considered in the revised model by introducing a coefficient of the scour of kaolinite (i.e., Case 2). The simulation results of Case 2 fit well with the measured data on mineral assemblage, and the trend of the sandstone porosity growth caused by the CO2-brine-rock reaction is captured by our simulation results. The combination of numerical simulation and natural analogue study indicates that the joint effects of long-term CO2-brine-rock reactions and scour of kaolinite increase the pore space of the host rock and result in an increase in quartz content in the sandstone.

Highlights

  • Capturing carbon dioxide (CO2) from the atmosphere and injecting it into suitable geologic formations is considered an option to compensate for anthropogenic atmospheric emissions of CO2 [1]

  • Considering the above evidence, we propose that a portion of authigenic kaolinite has been washed away in the Longtan sandstone Formation under the strong flow system caused by the intrusion of CO2, which can explain why the simulated abundance of kaolinite in the Base Case is much higher than the observations from cores

  • Given the complexity of the long-term geochemical reactions and the variety of factors that may impact, we deem that these deviations between simulation results and measured data are tolerable and that the revised model (Case 2) can reproduce the process of long-term CO2-water-rock interaction in the Longtan sandstone Formation in the Huangqiao area

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Summary

Introduction

Capturing carbon dioxide (CO2) from the atmosphere and injecting it into suitable geologic formations is considered an option to compensate for anthropogenic atmospheric emissions of CO2 [1]. Numerical modeling is often employed for long-term CO2 geological storage assessment, which can provide valuable insights into the chemical and physical consequences of CO2 injection into the subsurface environment. Such simulations rely on thermodynamic and kinetic databases that have uncertainty [26]. These authors conducted a s6e0t°CoftoC1O220-°bCrinaen-dsafnrdosmton1e0 interaction MPa to 40 experiments from MPa, which correspond to burial depths from 1500 m to 4000 m, to understand the corrosion of CO2-rich fluid on the sandstone reservoir.

Geological Background
Core Mineralogy Test Data Analysis
Numerical Modeling Approach
Model Setup
Results and Discussion
Summary and Conclusions

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