Enhanced Learning of Fundamental Petrophysical Concepts Through Image Processing and 3D Printing

Abstract

We designed a multidimensional visual learning project with the primary goal of helping undergraduate students better understand fundamental concepts in petrophysics through a set of exercises centered around an analysis of flooding experiment images. More specifically, we focused on concepts related to the trapped fluid within a rock’s pores in this project. To do this, eight different pore networks with unique internal structures were used and then 3D printed. The models were printed using a transparent resin to showcase the movement of fluids inside the rock model. The fluid’s displacement within the 3D-printed rock model was recorded using a high-definition camera, and still images were taken. Undergraduate petroleum engineering students were then assigned a set of exercises to guide them through an analysis of the pore network model images. Students conducted the analysis through an open-source image analysis software (Fiji) to help explore and better understand fundamental petrophysical properties: porosity, fluid saturation, wettability, grain-size distribution, and displacement efficiency. A survey was given to the students to gauge the effectiveness of the exercise in improving their understanding of these concepts. Survey results illustrated that the project-based learning exercises were effective in helping students to better understand difficult-to-grasp petrophysical concepts as they could be more easily visualized through the captured flooding experiment images and the accompanying analysis. An additional benefit to this unique visual learning experience is the ease at which it can be delivered remotely to adhere to safety measures as a result of the global COVID-19 pandemic.