This work aims to conduct, interpret and derive the multi-phase fluid flow behaviour more efficiently and feasibly from a novel perspective. The goal is to conduct a SCAL measurement using a microfluidic setup on a chip and interpret the in-situ results, where the parameters influencing the multi-phase fluid flow in porous media, such as wettability, capillary pressure, and relative permeability, are measured simultaneously. There are numerous economic and technical advantages of this approach. Conventionally, SCAL measurements are conducted through core samples using X-ray and multi-phase fluid flow parameters in porous media are measured separately. These properties can be simultaneously determined in digital rock physics (DRP) by applying micro-CT imaging but with high costs. The steady-state method was utilised in this study and re-designed for microfluidic flooding. The measurement was conducted using one oleic and one aqueous phase, applying different fractional flow steps, mimicking the range of varying water saturation in the reservoir during the depletion process. The used microchip has a synthetic pore-structure design with circular grain shapes. The measurements conducted are visible in real-time using a microfluidic approach. The experimental results show that it is possible to adapt the microfluidic flooding for conducting and interpreting SCAL measurements. An additional advantage of this method is that the wettability and capillary pressure could be successfully determined by means of image processing using only the data obtained from the steady-state method in a microchip. Since the measurements are visible live, and images of the microchip are captured with the desired frequency, the image processing facilitates the understanding and interpretation of multi-phase fluid flow in porous structures, which is not possible with cores. Overall, to overcome the technical and economic limitations of digital rock physics, the application of SCAL through microchips representing the porous media is a good alternative. The SCAL-on-Chip is a promising approach for describing and analysing multi-phase fluid flow. Image processing contributes to developing "smarter" and cheaper interpretation tools for estimating wettability and capillary pressure. It provides the possibility to derive mathematical models of the relationship between multi-phase flow characteristics. The derivation of a general function between the measured properties could be possible with machine learning and a sufficient amount of experiments using pore structures that closely resemble porous media.

Relative permeability and capillary pressure are the key parameters of the multiphase flow in a reservoir. To ensure an accurate determination of these functions in the areas of interest, the core flooding and centrifuge experiments on the relevant core samples need to be interpreted meticulously. In this work, relative permeability and capillary pressure functions are determined synchronously by history matching of multiple experiments simultaneously in order to increase the precision of results based on additional constraints coming from extra measurements. To take into account the underlying physics without making crude assumptions, the Special Core Analysis (SCAL) experiments are chosen to be simulated instead of using well know simplified analytical or semi-analytical solutions. Corresponding numerical models are implemented with MRST (Lie, 2019) library. The history matching approach is based on the adjoint gradient method for the constrained optimization problem. Relative permeability and capillary pressure curves, which are the objectives of history matching, within current implementation can have a variety of representations as Corey, LET, B-Splines and NURBS. For the purpose of analyzing the influence of correlations on the history matching results in this study, the interpretation process with assumed analytical correlations is compared to history matching based on generic NURBS representation of relevant functions.

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