InterPore2023

Roles of Transport Mechanisms and Model Parameters in Gas Flow Migration across low-permeability porous media

22 May 2023, 10:50

15m

Oral Presentation (MS14) Uncertainty Quantification in Porous Media MS14

Speaker

Leonardo Sandoval (Politecnico di Milano)

Description

Appropriate modeling approaches to quantify gas migration in low-permeability porous media can assist appraisal of sealing efficiency of caprocks, with key applications in sustainable use of underground energy resources. A variety of models depicting gas movement across low-permeability geomaterials are available (Wu et al., 2016; Sun et al., 2017, Rani et al., 2018). Some of these models represent gas migration in low-permeability media as a weighted sum of diverse mechanisms taking place across the porous system. Parameters associated with these models are envisioned to embed the chemical, mechanical, flow, and transport features governing feedbacks between gas and the host rock matrix. Such parameters cannot be easily and unambiguously evaluated via experimental investigations and are always affected by uncertainty. In this context, modern sensitivity analysis techniques enable us to diagnose the behavior of a given model through quantification of the importance and role of model parameter uncertainties onto 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 (i.e., Slip flow and Knudsen diffusion). We quantitatively investigate the impact of each uncertain model parameter on the evaluation of methane flow, which is, in turn, conceptualized as a random quantity. Considering the paucity of available information, we consider three diverse characterizations of the probability density function describing the uncertain model parameters: (a) all parameters are described by uniform distributions; (b) all parameters are represented through truncated normal distributions; and (c) the reference pore radius is described by a truncated log-normal distribution while the remaining parameters are associated with uniform distributions. We then derive analytically the structure of an effective diffusion coefficient embedding all complex mechanisms of the model considered and rely on the global sensitivity analysis results to quantify the relative contribution of each flow mechanism to the overall gas flow.
Our results suggest that, in decreasing order of importance, reference pore radius, reference porosity, pore pressure, tortuosity, and temperature are the model parameters driving the major features of the gas flow probability density function. These results remain essentially unaffected by the choice of probability density function characterizing model uncertain parameters.

References

• Rani S,Prusty BK, Pal SK (2018) Adsorption kinetics and diffusion modeling of CH4 and CO2 in Indian shales. Fuel 216(November 2017):61–70, DOI 10.1016/j.fuel.2017.11.124

• Sun Z, Li X, Shi J, Zhang T, Sun F (2017) Apparent permeability model for real gas transport through shale gas reservoirs considering water distribution characteristics. International Journal of Heat and Mass Transfer 115:1008–1019, DOI 10.1016/j.ijheatmasstransfer.2017.07.123

• Wu K, Chen Z, Li X, Guo C, Wei M (2016) A model for multiple transport mechanisms through nanopores of shale gas reservoirs with real gas effect-adsorption-mechanic coupling. International Journal of Heat and Mass Transfer 93:408–426, DOI 10.1016/j.ijheatmasstransfer.2015.10.003