In-situ, real time micro-CT imaging of pore scale processes, the next frontier for laboratory based micro-CT scanning

Over the past decade, laboratory based X-ray computed micro-tomography (micro-CT) has given unique insights in the internal structure of complex reservoir rocks, improving the understanding of pore scale processes and providing crucial information for pore scale modelling. Especially in-situ imaging using X-ray optimized Hassler type cells has enabled the direct visualization of fluid distributions at the pore scale under reservoir conditions. While sub-micrometre spatial resolutions are achievable in lab-based micro- CT, the temporal resolutions are still limited to minutes or hours. This time restriction is often a bottleneck for imaging dynamic in-situ processes, thus limiting the applicability to relatively slow pore scale processes occurring in the order of hours to days, or to end points in drainage-imbibition cycles. To overcome this issue, X-ray Engineering (XRE) and Ghent University’s Centre for X- ray Tomography (UGCT) have jointly developed a gantry-based micro-CT system. This system’s X-ray tube and detector rotate continuously in a horizontal plane around the fixed sample. The setup still allows to tune the geometrical magnification, with spatial resolutions down to 5 µm. This fixed sample setup is also ideal for in-situ imaging, as the flow cells can be directly connected to high pressure flow tubing and sensor lines, without the need to allow rotational movement relative to the X-ray source and detector. An efficient hardware design with a fast flat panel detector, combined with custom X-ray transparent flow cells to increase X-ray flux and dedicated 4D software tools in acquisition, reconstruction and analysis, allows to reach temporal resolutions in the order of seconds. The possibilities of this new approach in dynamic in-situ imaging are illustrated with flow tests on a carbonate sample. We discuss the challenges in dynamic imaging and present methods to improve X-ray flux and optimize image quality by means of this experiment. Furthermore, we show that the integration of fast imaging experiments with other information from peripheral sensors or from imaging data at different resolutions can help to link behaviour at the pore scale to the effective properties at the core scale, but also facilitates the experimental workflow