Sensitivity Analysis and Quantification of the Role of Governing Transport Mechanisms and Parameters in a Gas Flow Model for Low-Permeability Porous Media

Abstract

Recent models represent gas (methane) migration in low-permeability media as a weighted sum of various contributions, each associated with a given flow regime. These models typically embed numerous chemical/physical parameters that cannot be easily and unambiguously evaluated via experimental investigations. In this context, modern sensitivity analysis techniques enable us to diagnose the behavior of a given model through the quantification of the importance and role of model input uncertainties with respect to a target model output. Here, we rely on two global sensitivity analysis approaches and metrics (i.e., variance-based Sobol’ indices and moment-based AMA indices) to assess the behavior of a recent interpretive model that conceptualizes gas migration as the sum of a surface diffusion mechanism and two weighted bulk flow components. We quantitatively investigate the impact of (i) each uncertain model parameter and (ii) the type of their associated probability distribution on the evaluation of methane flow. We then derive the structure of an effective diffusion coefficient embedding all complex mechanisms of the model considered and allowing quantification of the relative contribution of each flow mechanism to the overall gas flow.

Relative importance of uncertain model parameters driving water fluxes in a Land Surface Model

“…Here, we focus on the mean and the variance of the model output. These metrics have been applied in diverse settings, including scenarios related to, e.g., groundwater hydrology (Bianchi Janetti et al, 2019;Dell'Oca, 2023), subsurface energy resources associated with gas flow migration across low-permeability media (Sandoval et al, 2022), analysis of seismic metabarriers (Zeighami et al, 2023), dynamics of emerging contaminants in groundwater (Ceresa et al, 2023), or assessment of infiltration structures (Dell'Oca et al, 2023).…”

“…The joint use of these metrics is exemplified upon relying on realistic field conditions (in terms of, e.g., climate, vegetation, and soil type) associated with two watersheds in the Vosges region (France) across a one-year period. The relevance of relying on various sensitivity analysis, each providing a unique contribution to enriching our knowledge of the system behavior, is underlined in several studies (e.g., Maina and Guadagnini, 2018;Bianchi Janetti et al, 2019;Ju et al, 2021;Sandoval et al, 2022; and references therein).…”

Comparative Assessment of Two Global Sensitivity Approaches Considering Model and Parameter Uncertainty

“…The importance of relying on a variety of approaches, each comprising diverse aspects of uncertainty and all of them contributing to a synergic enrichment of our knowledge of the system behaviors, is underlined in several studies (e.g., Bianchi Janetti et al., 2019; Ju et al., 2021; Maina & Guadagnini, 2018; Sandoval et al., 2022 and references therein). It is often difficult for one method to meet all of the needs required to achieve a given objective or to provide a complete sensitivity assessment, and results associated with one method might sometimes suffer from biases as compared to those that can be obtained with another.…”

“…For instance, Bianchi Janetti et al ( 2019) use three GSA methods (i.e., the Morris, Sobol, and AMA indices) to evaluate the impact of uncertain parameters associated with different conceptual geological models on the spatial distribution of groundwater heads. Sandoval et al (2022) use the variance-based Sobol indices and the AMA indices to assess the relative influence of uncertain model parameters on various features of the probability density function (PDF) of target model outputs when considering gas flow migration across low-permeability media. Providing a comprehensive analysis on the benefits of relying on the joint use of these GSA metrics as well as an assessment of the relative merits of each of these approaches under various sources of uncertainty is precisely the main objective of our study.…”