Abstract
Among the technologies for carbon neutral, CO2 geological sequestration is one of the most promising. The mechanisms of CO2 behavior within pore space are complex and influenced by multiple factors, with the geometric structure of porous formations being particularly critical to the technology’s efficiency. Among several important and challenging problems in geological sequestration, this work addresses the issue of selecting lithologies based on their geometrical structure. This study proposes a mathematical approach to characterize the geometric structure of porous rock and fluid flow using a random walk (RW) method. Our approach simulates the time evolution of particle flow through highly disordered and heterogeneous digital rock models under a pressure gradient imposed between inlet and outlet surfaces. Through RW simulations, a probabilistic model for mineralization via a clogging (pore-filling) model is introduced, to examine the accumulation of particles within porous structures over time: single-phase clogging and multiple-phase clogging. In single-phase clogging, the porosity decrease can be described as a monotonically non-increasing function of the deposition probability. However, this is no longer true in the multiple-phase strategy because large deposition probability blocks the capillaries near the inlet surface, preventing the fluid from easily invading easily the outlet. In this study, numerical studies conducted on four types of natural rocks—Bentheimer, Doddington, Estaillades, and Ketton—revealed that Ketton exhibits the highest permeability. Our results suggest that Bentheimer, Doddington, and Ketton formations are suitable candidates for CO2 sequestration, while Estaillades is less favorable from a geometric standpoint. The methods presented in this work contribute to effectively identifying natural rocks with geometric structures advantageous for CO2 storage.
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