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Quantification of CO2 generation in sedimentary basins through Carbonate Clays Reactions with uncertain thermodynamic parameters (2210.16119v1)

Published 28 Oct 2022 in physics.geo-ph and stat.AP

Abstract: We develop a methodological framework and mathematical formulation which yields estimates of the uncertainty associated with the amounts of CO2 generated by carbonate-clays reactions (CCR) in large-scale subsurface systems to assist characterization of the main features of this geochemical process. Our approach couples a one-dimensional compaction model, providing the dynamics of the evolution of porosity, temperature and pressure along the vertical direction, with a chemical model able to quantify the partial pressure of CO2 resulting from minerals and pore water interaction. The modeling framework we propose allows (i) estimating the depth at which the source of gases is located and (ii) quantifying the amount of CO2 generated, based on the mineralogy of the sediments involved in the basin formation process. A distinctive objective of the study is the quantification of the way the uncertainty affecting chemical equilibrium constants propagates to model outputs, i.e., the flux of CO2. These parameters are considered as key sources of uncertainty in our modeling approach because temperature and pressure distributions associated with deep burial depths typically fall outside the range of validity of commonly employed geochemical databases and typically used geochemical software. We also analyze the impact of the relative abundancy of primary phases in the sediments on the activation of CCR processes. As a test bed, we consider a computational study where pressure and temperature conditions are representative of those observed in real sedimentary formation. Our results are conducive to the probabilistic assessment of (i) the characteristic pressure and temperature at which CCR leads to generation of CO2 in sedimentary systems, (ii) the order of magnitude of the CO2 generation rate that can be associated with CCR processes.

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