April 2025

๐Ÿ“ขย LTrace is proud to sponsor 8th Brazil Chapter InterPore Conference on Porous Media! ๐Ÿ“ข

28 Apr , 2025 Digital rock physics,GeoSlicer

๐Ÿ“ขย LTrace is proud to sponsor 8th Brazil Chapter InterPore Conference on Porous Media! ๐Ÿ“ข

๐Ÿ“ The conference will take place in our beloved city of Florianรณpolis, from August 11โ€“13, 2025. ๐Ÿ“–ย LTrace will also conduct a mini-course about the new software GeoSlicer. GeoSlicer is a digital rock platform that leverages AI tools to process digital rocks at all scales. It will be offered to any InterPore BR 2025 participant who […]

๐ŸŽ‰ LTrace at the International Rock Imaging Symposium! iRIS-2025๐Ÿ”ฌ

16 Apr , 2025 Digital rock physics,GeoSlicer,Pore Network Model

๐ŸŽ‰ LTrace at the International Rock Imaging Symposium! iRIS-2025๐Ÿ”ฌ

From April 8โ€“10, we had the privilege of joining the Rock Imaging Special Interest Group at the Geological Society in London for an inspiring few days of cutting-edge research, discussion, and collaboration. ๐Ÿ’ฌ We were honored to speak alongside world-class researchers and industry leaders in rock imaging โ€” a field thatโ€™s essential to both the […]

๐Ÿš€ Most Downloaded Article List โ€“ Geophysics Journal! ๐Ÿ†

4 Apr , 2025 Bayes,Geophysics,Geostatistics,Seismic Inversion

๐Ÿš€ Most Downloaded Article List โ€“ Geophysics Journal! ๐Ÿ†

Thrilled to share that two articles co-authored by our co-founder Leandro Passos de Figueiredo have been featured among the most downloaded papers in the prestigious journal Geophysics! This recognition highlights the quality, relevance, and impact of the work, and the excellent collaboration culture weโ€™ve nurtured at LTrace over the years. ๐Ÿ‘ Congratulations to all the […]

๐ŸŒ Pleased to share our progress in history matching with seismic data assimilation ๐Ÿš€

2 Apr , 2025 AI,Deep Learning,History Matching

๐ŸŒ Pleased to share our progress in history matching with seismic data assimilation ๐Ÿš€

Weโ€™ve been investigating how AI can support the Ensemble Smoother with Multiple Data Assimilation (ES-MDA) to improve history matching and reservoir model updates. By using AI to reduce seismic data volume, weโ€™ve been able to save time while achieving results comparable to the standard ES-MDA approach. ๐Ÿ“Š Key Achievements: โœ… Reduced seismic data using pre-trained […]