Validating the Generalized Pore Network Model Using Micro-CT Images of Two-Phase Flow

Abstract

A reliable prediction of two-phase flow through porous media requires the development and validation of models for flow across multiple length scales. The generalized network model is a step towards efficient and accurate upscaling of flow from the pore to the core scale. This paper presents a validation of the generalized network model using micro-CT images of two-phase flow experiments on a pore-by-pore basis. Three experimental secondary imbibition datasets are studied for both sandstone and carbonate rock samples. We first present a quantification of uncertainties in the experimental measurements. Then, we show that the model can reproduce the experimental fluid occupancies and saturations with a good accuracy, which in some cases is comparable with the similarity between repeat experiments. However, high-resolution images need to be acquired to characterize the pore geometry for modelling, while the results are sensitive to the initial condition at the end of primary drainage. The results provide a methodology for improving our physical models using large experimental datasets which, at the pore scale, can be generated using micro-CT imaging of multiphase flow.

Pore Network Model Predictions of Darcy‐Scale Multiphase Flow Heterogeneity Validated by Experiments

“…The pore network model simulations were run using the approach of Valvatne and Blunt (2004) with the updated algorithm (PNflow) described in Raeini, Bijeljic, and Blunt (2018) and further validated by Bultreys et al (2018) and Raeini et al (2019). This model relies on an assumption of quasi-static capillary dominated flow.…”

Pore-by-pore modeling, analysis, and prediction of two-phase flow in mixed-wet rocks

“…One particular source of uncertainty and ambiguity in model predictions is the assignment of wettability, or contact angle, on a pore-by-pore basis [28]. Most modeling studies have attempted to calibrate multiphase flow in a few rock types based only on the macroscopic experimental data, which, as discussed above, is not reliable [22].…”

“…In recent years, several studies have sought to validate image-based models against experimental micro-computedtomography (micro-CT) results including pore scale fluid distribution and topology [21,28,[30][31][32][33][34]. Akai et al [30] simulated an unsteady-state waterflooding experiment on a mixedwet carbonate rock using the lattice Boltzmann method incorporating locally measured contact angles [35].…”

“…They obtained a fluid occupancy that agreed with experiment in more than 75% of the network. Furthermore, Raeini et al [28] performed pore-by-pore comparisons for a generalized network model on repeated unsteady state CO 2 waterflood experiments in sandstones and carbonates [26,27] and on steadystate waterflood Bentheimer sandstone experiments. They quantified the mismatch between the micro-CT experiment and the network model by defining the discrepancy in pore occupancy.…”

Steady-State Water Drainage by Oxygen in Anodic Porous Transport Layer of Electrolyzers: A 2D Pore Network Study

“…Pore network models (PNMS) are a type among various pore scale models available, e.g., Lattice Boltzmann models which are mostly available on the scale of one pore. PNMs are discrete models that represent the pore space by a lattice of pores and throats (e.g., [42][43][44][45][46]). In comparison to other methods, which are computationally more expensive in terms of discretization of the physical domain and solving of the governing equations, PNMs can be used to study larger systems computationally more efficiently.…”