Pretty Porous Science Lecture #18 "Flow Dependent Relative Permeability Scaling for Steady-State Two-Phase Flow in Porous Media: Laboratory Validation on a Microfluidic Network" by Marios Valavanides

April 21, 2022 /

The SFB 1313 "Pretty Porous Science Lecture" #18 will be given by Marios Valavanides from the Department of Civil Engineering, University of West Attica (Greece) | 21 April 2022 | 4:00 pm CET

We are pleased to announce that Marios Valavanides, professor at the Department of Civil Engineering of the University of West Attica (Greece), will give the SFB 1313 "Pretty Porous Science Lecture" #18. His talk will be on "Flow Dependent Relative Permeability Scaling for Steady-State Two-Phase Flow in Porous Media: Laboratory Validation on a Microfluidic Network".

More information about his visit in Stuttgart can be found on the homepage of the Institute for Applied Mechanics.

Date: Thursday, 21 April 2022
Time: 4:00 pm CET
Speaker: Prof. Marios Valavanides, Department of Civil Engineering, University of West Attica (Greece)
Lecture title: "Flow Dependent Relative Permeability Scaling for Steady-State Two-Phase Flow in Porous Media: Laboratory Validation on a Microfluidic Network"
Place: The lecture will be a hybrid lecture. A small audience is possible in Pfaffenwaldring 61 MML, additionally the lecture is offered online. After registration, you will receive the meeting information.
Registration: If you are interested in participating in the lecture, please contact katharina.heck@iws.uni-stuttgart.de

Abstract

Conventionally, relative permeabilities of two immiscible fluid phases during flow in porous media are considered and expressed as functions of saturation. Yet, this has been put into challenge by theoretical, numerical and laboratory studies of flow in artificial pore network models and real porous media, that have revealed a significant dependency on the flow rates, especially when the flow regime is capillary to capillary-viscous dominated, and part of the disconnected non-wetting phase (NWP) remains mobile (see Introduction). These studies suggest that relative permeability models should include the functional dependence on flow intensities. Revealing the explicit form of such dependence remains a persistent problem. Just recently, a general form of dependence has been inferred, based on extensive simulations with the DeProF model for steady-state two-phase flows in pore networks. The simulations revealed a systematic dependence of the relative permeabilities on the local flow rate intensities that can be described analytically by a universal scaling functional form of the actual independent variables of the process, namely, the capillary number, Ca, and the flow rate ratio, r. The proposed scaling comprises a kernel function accounting for the transition between capillarity- and viscosity-dominated flow phenomena. In a follow-up systematic laboratory study SCAL measurements provided a preliminary proof-of-concept on the applicability of the model and validated its specificity (Valavanides et al., 2020).

In an ongoing laboratory study, we examine the applicability of the basic flow-rate dependent relative permeability scaling model in immiscible two-phase flows in an artificial two-dimensional microfluidic network, across different flow regimes and for different NWP/WP systems.

We assess the applicability of the flow-dependent relative permeability scaling model in a microfluidic pore-network and we correlate the form of the associated kernel function with the interstitial structure of the flow across different flow regimes. Scope is to assess the applicability and/or universality of the aforementioned scaling function across NWP/WP/PM systems of different sizes and to examine the forensic character of the kernel function, i.e. the potential for revealing the interstitial flow structure.

The proposed scaling opens new possibilities in improving SCAL protocols and other important applications, e.g. characterization of systems and flow conditions, rock typing, assessment of end-effects during R/SCAL, as well as the development of more efficient field-scale simulators.

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