The recent surge in artificial intelligence (AI) advancements has been driven by the availability of open datasets for model development and evaluation. However, in the field of earth sciences, particularly in digital rock physics applications, open data remains scarce. To bridge this gap, we introduce a dataset comprising 16 rock samples from the Brazilian pre-salt region, available in both low resolution (48 μm - 64 μm) and high resolution (6 μm - 8 μm). The dataset also includes their respective segmented images into pore and matrix. Furthermore, porosity and permeability values obtained from laboratory measurements are provided for all samples. This dataset serves as a valuable resource for developing and benchmarking AI-based superresolution/segmentation models. Additionally, it can be utilized to develop models for predicting porosity and permeability directly from μ-CT images.
© 2024. The Author(s).