We hope everyone is having a safe and restful spring break! In the last issue we presented the winners in the three categories of the challenge. We devote this issue to the honorary mentions of our Visualization Challenge! The task was to reuse any 3D dataset from the Digital Rocks Portal to create a static image, video, or 3D printed visualization. We thank our sponsors:South Big Data Innovation Hub(main sponsor),Object Research Systems(“Enchanted Rock” premium sponsor), Kitware(“Town Mountain Granite” sponsor), and Dassault Systèmes(“Austin Chalk” sponsor) for their support and cash prizes for the participants.
We would also like to highlight an opportunity to join industry experts at the SPE Virtual Workshop: Open Subsurface from May 18-21, 2021 to explore how open communities could help accelerate innovation in open subsurface projects. Digital Rocks Portal will be featured as one of the projects! Open source, data, and ecosystems tend to enable a faster pace of innovation. Today, subsurface modeling relies predominantly on proprietary solutions. The objective of this workshop is to explore how open communities could help accelerate innovation. Click here to register, and if you are in industry please consider sponsoring the workshop.
Participant: Fahim Salek, Auburn University Title: Juxtaposition of rock microstructure and pore network model of the pore space Dataset Reused: 11 Sandstones: raw, filtered and segmented data
Participant: Ken Ikeda, The University of Texas at Austin
Title: Stress field in Gildenhauser Sandstone Dataset Reused: Gildehauser Sandstone
Participant: Renee Cole, The University of Texas at Austin
Title: Exploring velocity field in sandstone and carbonate pore spaces
Dataset Reused: Bentheimer Sandstone and Estaillades Carbonate
Participant: Chiye Xie, The University of Texas at Austin
Title: Water-Oil Displacement
Dataset Reused:A Multiscale Sandy Microstructure
Participant: Andrew Solis, Texas Advanced Computing Centre
Title: Visualization of Three-Phase Flow of Water in Mixed-Wet Ketton Limestone
Dataset Reused: Water-wet three-phase flow micro-CT tomograms
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