Application of upscaling methods for fluid flow and mass transport in multi-scale heterogeneous media: A critical review

Physical and biogeochemical heterogeneity dramatically impacts fluid flow and reactive solute transport behaviors in geological formations across scales. From micro pores to regional reservoirs, upscaling has been proven to be a valid approach to estimate large-scale parameters by using data measured at small scales. Upscaling has considerable practical importance in oil and gas production, energy storage, carbon geologic sequestration, contamination remediation, and nuclear waste disposal. This review covers, in a comprehensive manner, the upscaling approaches available in the literature and their applications on various processes, such as advection, dispersion, matrix diffusion, sorption, and chemical reactions. We enclose newly developed approaches and distinguish two main categories of upscaling methodologies, deterministic and stochastic. Volume averaging, one of the deterministic methods, has the advantage of upscaling different kinds of parameters and wide applications by requiring only a few assumptions with improved formulations. Stochastic analytical methods have been extensively developed but have limited impacts in practice due to their requirement for global statistical assumptions. With rapid improvements in computing power, numerical solutions have become more popular for upscaling. In order to tackle complex fluid flow and transport problems, the working principles and limitations of these methods are emphasized. Still, a large gap exists between the approach algorithms and real-world applications. To bridge the gap, an integrated upscaling framework is needed to incorporate in the current upscaling algorithms, uncertainty quantification techniques, data sciences, and artificial intelligence to acquire laboratory and field-scale measurements and validate the upscaled models and parameters with multiscale observations in future geo-energy research.

Automated summary

The physical and biogeochemical heterogeneity in geological formations significantly impacts fluid flow and solute transport behaviors, making upscaling a valid approach for estimating large-scale parameters. Deterministic and stochastic are the two main categories of upscaling methodologies, with volume averaging being widely applicable and numerical solutions gaining popularity. The gap between approach algorithms and real-world applications calls for an integrated upscaling framework incorporating uncertainty quantification techniques, data sciences, and artificial intelligence for future geo-energy research.