Review on pore-network modeling studies of gas-condensate flow: Pore structure, mechanisms, and implementations

Gas-condensate flow is a critical process in the near-well region where the well production efficiency is strongly affected by the production of condensate dropout. Pore-scale simulations have provided an understanding of the underlying processes such as snap-off and the effect of the interplay between viscous and capillary forces on gas-condensate flow and its induced blockage within the pore spaces. Among various modeling approaches used to explore these phenomena, pore-network modeling, due to its computational efficiency and the ability to simulate relatively large sample sizes, has appealed to researchers. This article presents a review of the development of pore-network models to simulate gas-condensate flow, particularly in the near wellbore regions. This contribution reviews pore-scale mechanisms that should be included in simulating the gas-condensate flow, together with the involved processes and the peculiarities pertinent to such modeling efforts. After a brief review of different pore scale studies and their differences, advantages, and disadvantages, the review focuses on pore-network modeling, and the application of pore-network modeling in gas-condensate flow in the recent studies. The employed methodologies, highlights, and limitations of each pore network study are examined and critically discussed. The review addresses pore-space evolution, flow mechanisms, and the involved flow and transport parameters. The formulations of capillary entry pressure in different pore geometries, the corresponding conductance terms, snap-off criteria, and conditions for the creation of condensate bridging in different pore structures are presented. Additionally, three major approaches used in pore-network modeling of gas condensation, namely quasi-static, dynamic methods and dynamic compositional pore-network modeling, are presented and their main governing equations are provided using various tables. Finally, the significance of gas-condensate flow modeling including its modeling challenges together with the main similarities and differences among pore-network studies are provided

Theoretical and experimental investigations on the role of transient effects in the water retention behaviour of unsaturated granular soils

In the present study, an experimental setup is presented and employed to examine the influence of rate of change of saturation on the transient water retention curves of granular soils with a low suction range. The results are evaluated and compared to existing theoretical approaches to model the non-equilibrium soil-water retention behaviour as well as to experimental findings from other researchers. Furthermore, suction stress characteristic curves under non-equilibrium conditions are obtained. Finally, the importance and the application of the results in hydro-mechanical modelling of unsaturated soils are discussed

Determination of soil-water retention curve: an artificial intelligence-based approach

Soil Water Retention Curve (SWRC) is a fundamental relationship in unsaturated soil mechanics, knowledge of which is essential for determining major mechanical and hydraulic properties of unsaturated soils. There are several empirical, semi-empirical and physically-based models which have been proposed to date for estimating SWRC. While the physically-based models which employ the basic soil characteristics such as grain-size and pore-size distributions are regarded superior to purely empirical models, their Achilles’ heel is the several simplifying assumptions based on which these models are constructed, thereby, restricting their applications and influencing their accuracy. Given the complexity of the soil porous structure, one may resort to the new inference techniques rather than mechanistic modelling to find the relationship among soil physical characteristics and the retention properties. Therefore, an alternative approach to purely empirical relationships as well as physically-based and conceptual models for determining SWRC is the use of Artificial Intelligence (AI) based techniques to acquire a relationship for SWRC based on the soil basic properties, especially grain size distribution and porosity. Among AI-based methods, Multi-Gene Genetic Programming (MGGP), often used to establish a close form equation for a complex physical system, offers a suitable alternative to the current approaches. In this study, a database compromising of 437 soils (containing various soil types, namely, sand, clay, silt, loam, silt loam, clay loam, sandy loam, sandy clay loam, silty clay loam, silty clay, and loamy sand soils) was used along with MGGP to establish a relationship among suction, saturation, porosity and grain size distribution. The proposed equation had a reasonable agreement with the experimental data compared to the other grain-based and physically-based models

Theoretical and experimental investigations on the role of transient effects in the water retention behaviour of unsaturated granular soils

In the present study, an experimental setup is presented and employed to examine the influence of rate of change of saturation on the transient water retention curves of granular soils with a low suction range. The results are evaluated and compared to existing theoretical approaches to model the non-equilibrium soil-water retention behaviour as well as to experimental findings from other researchers. Furthermore, suction stress characteristic curves under non-equilibrium conditions are obtained. Finally, the importance and the application of the results in hydro-mechanical modelling of unsaturated soils are discussed