Micromodel can provide valuable information to improve understanding of pore-scale transport phenomenon and can also be utilized to simulate the transport process at pore scale. This research aims to propose settlement option for quantification of suspended solids in micromodel. The micromodel is used to mimic the formation damage which occurs in reservoir formation that could simultaneously affect enhanced oil recovery. This is done by utilizing visual image interpretation through image analysis on micromodel chip. Following the quantification of suspended solids, the micromodel was injected with brine that eventually forms agglomeration. Images are taken from NIS-Element AR microscope automatically in RGB color profile and 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 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.

微观模型可以提供有价值的信息，以增进对孔隙尺度传输现象的理解，也可以用于模拟孔隙尺度下的迁移过程。这项研究旨在为微模型中的悬浮固体定量提出沉降选项。该微模型用于模拟在储层中发生的地层损害，该损害可同时影响提高的石油采收率。这是通过在微模型芯片上通过图像分析利用可视图像解释来完成的。在对悬浮固体进行定量之后，向微模型注入盐水，最终形成团聚。图像是从NIS-Element AR显微镜自动以RGB颜色配置文件拍摄的，然后变成灰度级，最后变成二进制模式。由于微模型是以2D形式的结构进行模拟的，²个兴趣区域分别分为B05，M45和T50区域3个主要组。这项研究将探索从微观模型实验获得的视觉数据的分割和阈值处理过程。在MATLAB Image Processing Toolbox和ImageJ中编程了基于图像的计算算法；因此，可以从在微模型中执行的可视图像中量化多孔介质中的悬浮固体。