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.
Highlights
Predicting flow properties of porous media—for instance, relative permeability and capillary pressures under different displacement paths, wettability and flow rates—is essential in the study of subsurface flow processes
In the generalized network model, every voxel in an image is assigned to a unique pore and throat (Raeini et al 2017)
These experiment– model mismatches show an improvement of roughly 4% compared to the results presented on a coarse image of Ketton in the previous section; this shows the importance of having high-resolution micro-CT images for accurate parametrization of the pore space and its crevices, which allow both the displacement processes and the saturation within each pore and throat to be predicted accurately
Summary
Predicting flow properties of porous media—for instance, relative permeability and capillary pressures under different displacement paths, wettability and flow rates—is essential in the study of subsurface flow processes. Nm, μm, mm, cm stand for domain sizes in the order of several nanometres, micrometres, millimetres and centimetres, respectively, and block stands for the block sizes used in reservoir simulation models These models need to be validated, and in most cases calibrated, against different data sources, for instance experimental or high-fidelity simulation data, to improve the flow of information—model inputs and outputs—from the sub-pore to field-scale models of multiphase flow. The validation and calibration of these models requires, respectively, quantifying and minimizing the mismatches between the model predictions and experimental data at different scales and on large datasets Examples of such data, for the case of pore network models, for μm to mm upscaling, are repeated (Andrew et al 2014) and four-dimensional (space-time domain) images of multiphase flow through mm-sized rock samples We investigate the accuracy of the model in predicting fluid occupancies at pore and throat centres as well as in computing pore saturations
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