Gradient Information Enhanced Image Segmentation and Automatic In Situ Contact Angle Measurement Applied to Images of Multiphase Flow in Porous Media

A gradient‐information‐enhanced image segmentation method using convolutional neural networks is presented, and then combined with contact angle measurement to establish an automated processing workflow. For three‐dimensional X‐ray images, the segmentation accuracy at interfaces and sparsely distributed small objects directly influences the accuracy of the contact angle measurement. Leveraging reliable gradient information to train the neural network, this segmentation method addresses the issue of inaccurate segmentation of interfaces even at low resolution and with small objects present. Furthermore, memory requirements are reduced by performing analysis on orthogonal two‐dimensional planes. The workflow was tested on water‐wet Ketton limestone, as well as on both water‐wet and mixed‐wet sandstone and a reservoir carbonate. The results from both the segmentation and contact angle measurements underscore the effectiveness of the approach. Notably, the workflow shows considerable generalizability and robustness, even with varying wettability and lithology. We use convolutional neural networks enhanced with gradient information to improve the accuracy of segmentation of three‐dimensional images of porous media and the fluids in the pore space, especially at interfaces and for small objects, even when the images have low resolution. We tested the method on several data sets including water‐wet Ketton limestone, both water‐wet and mixed‐wet Bentheimer sandstone, and a reservoir carbonate. The results demonstrated the effectiveness of our approach compared to traditional methods for segmentation. A particular challenge is the determination of contact angle ‐ the local wettability ‐ at the three‐phase contact loop between two fluid phases and the solid. We show that our new method leads to reliable estimates of the distribution of contact angle for the samples studied. This work allows for more accurate image analysis in multiphase flow in porous media with applications in carbon dioxide and hydrogen storage. A gradient information enhanced segmentation method is presented to assist automatic contact angle measurementsThe gradient information method reduces the problems associated with low image resolution and manual segmentation A gradient information enhanced segmentation method is presented to assist automatic contact angle measurements The gradient information method reduces the problems associated with low image resolution and manual segmentation