Add to Favourites
To login click here
Subsurface stratigraphic modeling is essential for a variety of environmental, societal, and economic challenges. However, the need for specific sedimentological skills in sediment core analysis may constitute a limitation. This work outlines a novel deep-learning-based approach to perform automatic semantic segmentation directly on core images, leveraging the power of convolutional neural networks. The proposed automated model can rapidly characterize sediment cores, allowing immediate guidance for stratigraphic correlation and subsurface reconstructions.