This study introduces a diagenetic modeling approach which is then applied to a simple one-dimensional scenario with an alternation of sandstone and shale layers. A key focus of the work is the analysis of the role of critical parameters that may drive pressure and overpressure dynamics in a basin. Due to its one-dimensional nature, the modeling technique presented can be currently applied as a Quality Control (QC) tool to assess the occurrence of diagenetic effects that might affect pressure evolution to assist in improving forecasting of overpressures in a new well in the same area or under similar geological settings. Coupling of hydro-geochemical and mechanical processes with the evolution of temperature enables one to model the effect of basin scale temperature-activated reactions on diagenetic scenarios. The resulting set of partial differential equations includes parameters whose values are always affected by high uncertainty. We provide uncertainty quantification (UQ) of the compaction process through a Global Sensitivity Analysis (GSA) of the system response following incomplete knowledge of a set of model parameters. The model response is approximated through a polynomial chaos expansion of the system dynamics. This decomposition provides (a) a GSA based on Sobol indices, and (b) a meta-model of the system that can then be adopted to perform multiple Monte Carlo realizations of the diagenetic process at an affordable computational time. Our results allow to (i) investigate the effect of parametric uncertainty on the system states, and (ii) perform robust parameter calibration within an inverse modeling framework. This work does not disclose significant data from the field or computer work; it contributes to improve our understanding and modeling of diagenesis of sandstones and shales and basin overpressure evolution.


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