Micromodel can provide valuable information to improve understanding of pore-scale transport phenomenon, also can be utilized to simulate the transport process at pore-scale. This research aims to propose settlement option for quantification of salt precipitation in micromodel. The micromodel is used to mimic the formation damage occur in reservoir formation that could simultaneously affect enhanced oil recovery. This is done utilizing visual image interpretation through image analysis on micromodel chip. Following the quantification of salt precipitation, the micromodel was initially injected with nano-silica followed by brine injection that eventually form salt precipitation due to chemical reaction between them. Images taken from NIS-Element AR microscope were automatically in RGB color profile, then made into grayscale and finally into binary modes. Since the micromodel is simulated in 2D form structure, the quantification method complemented with image analysis is focusing on the quantified area, µm2 region of interest (ROI) categorized into 3 main groups of area B05, M45 and T50, respectively. This research will explore on segmentation and thresholding processes of the visual data acquired from micromodel experiment. An image-based computational algorithm is programmed in MATLAB Image Processing Toolbox and ImageJ, hence suspended solids in porous media could be quantified from the visual image executed in micromodel.
|Title of host publication||International Conference on Oil & Gas Engineering and Technology 2020 (ICOGET2020)|
|Publication status||Submitted - 2020|