Abstract
Pore-scale two-phase flow modeling is an important technology to study a rock's relative permeability behavior. To investigate if these models are predictive, the calculated pore-scale fluid distributions which determine the relative permeability need to be validated. In this work, we introduce a methodology to quantitatively compare models to experimental fluid distributions in flow experiments visualized with microcomputed tomography. First, we analyzed five repeated drainage-imbibition experiments on a single sample. In these experiments, the exact fluid distributions were not fully repeatable on a pore-by-pore basis, while the global properties of the fluid distribution were. Then two fractional flow experiments were used to validate a quasistatic pore network model. The model correctly predicted the fluid present in more than 75% of pores and throats in drainage and imbibition. To quantify what this means for the relevant global properties of the fluid distribution, we compare the main flow paths and the connectivity across the different pore sizes in the modeled and experimental fluid distributions. These essential topology characteristics matched well for drainage simulations, but not for imbibition. This suggests that the pore-filling rules in the network model we used need to be improved to make reliable predictions of imbibition. The presented analysis illustrates the potential of our methodology to systematically and robustly test two-phase flow models to aid in model development and calibration.
Highlights
Multiphase flow through permeable rock is a crucial aspect of several important geo-engineering challenges such as petroleum recovery, geological CO2 sequestration, and environmental remediation of groundwater resources
Large-scale models of these applications require the input of constitutive properties, such as capillary pressure (Pc) and relative permeability, that describe the rock’s behavior during flooding operations [1,2]
The idea is that calibration to cheap experimental data allows models to extrapolate to either other samples or more complex situations
Summary
Multiphase flow through permeable rock is a crucial aspect of several important geo-engineering challenges such as petroleum recovery, geological CO2 sequestration, and environmental remediation of groundwater resources. While image-based pore-scale models have been used to investigate the Pc and kr behavior of reservoir rocks since the seminal work by Bakke and Øren [3], the capacity of these models to capture the appropriate physics and predict experimental data remains contentious [4,5,6]. In many image-based modeling studies, there is still commonly a philosophy of attempting purely a priori Pc and kr predictions, with a strong focus on reducing uncertainties of the second type [13]. While this is an import effort, ignoring the other uncertainties makes a thorough validation of these models extremely difficult. Direct simulation approaches face similar challenges, for example, when trying to constrain the wettability distribution in the model [17]
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