Probabilistic modeling of field-scale CO₂ generation by carbonate–clay reactions in sedimentary basins

<p>This work explores a probabilistic modeling workflow and its implementation targeting CO<span class="inline-formula">₂</span> generation rate and CO<span class="inline-formula">₂</span> source location by the occurrence of carbonate–clay reactions (CCRs) in three-dimensional realistic sedimentary basins. We ground our study on the methodology proposed for a one-dimensional case study and a single CCR formulation by <span class="cit" id="xref_text.1"><a href="#bib1.bibx8">Ceriotti et al.</a> (<a href="#bib1.bibx8">2017</a>)</span> which includes a framework to account for thermodynamic parameter uncertainties. This methodology is here extended to a realistic three-dimensional sedimentary basin setting and transferred to encompass different types of CCRs, including two newly formulated CCRs which account for minerals typically observed in sedimentary environments. While testing the ability of the selected procedure to model diverse CCRs in three-dimensional realistic subsurface sedimentary systems, we quantitatively compare the impact of CCR formulation on the spatial distribution of CO<span class="inline-formula">₂</span> source location, temperature and pressure compatible with CO<span class="inline-formula">₂</span> gaseous generation, and CO<span class="inline-formula">₂</span> generation rate in three-dimensional environments characterized by complex and non-uniform stratigraphy. The application of the procedure to various types of CCRs enables us to provide an insight into the impact of mineralogical composition on the activation temperature and pressure and the amount of CO<span class="inline-formula">₂</span> released by the different CCR mechanisms. Finally, we show the implementation of the proposed probabilistic framework to define scenarios associated with various levels of probability to be used as the input and boundary conditions for CO<span class="inline-formula">₂</span> migration and transport models in the subsurface.</p>