Automated advanced image processing for micromodel flow experiments; an application using labVIEW

The study of multi-phase fluid flow in microfluidic devices provides an opportunity for researchers to observe fluid transport mechanisms and characterize influencing factors directly. The visual outcome of a micromodel experiment is the subject of further image processing/analysis studies that quantify the variables of interest such as fluid saturation and other morphological features. The application of an automated image-based computational technique offered by various programming languages allows us to quantify better results from micromodel experiments. In this paper, the viability of automating image processing functions available in LabVIEW is demonstrated by a sample image processing code. The performance of this custom algorithm is verified by comparison of extracted data from a carbonated water injection (CWI) micromodel experiment with estimated absolute values derived from volumetric material balance. Through this procedure, a collection of optimized settings for utilized functions in LabVIEW is found that shows a significant agreement with true values. In the last section, the implementation of the presented algorithm in the LabVIEW and a popular commercial software is compared to highlight the pros and cons.