Iraya Energies’ Post

the latest Datarock Applied Science blog is out. In this installment, we look at why understanding your data is so important and why AI won't take away your job, but can add a powerful tool to your kit

In this months technical blog from the Applied Science team, we take a look at the importance of subject matter input into a #machinelearning project. Having a deep understanding of the subject matter is essential when preparing #geophysical images for analysis using computer vision methods. #Geoscientists should carefully consider how image preparation intends to enhance or suppress texture that could relate to #geology. Visit our newest blog post for further insights: https://lnkd.in/gBh94Vde

My start-up has a geological machine-learning map of the USA, Canada, Mexico, South America, Australia, and Africa. We base all our work "only" on hard rock geochemistry, then get a supervised decision tree AI to predictively figure out the spots to look at based on ground shapes and gravity maps. It is superior to a geological time fast-moving vector such as soil geochemistry (no AI models work on soil geochemistry, we have found). Our approaches let you see what the geophysical anomalies likely contain, such as in the attached image that shows how well AI compares to highly expensive IP work. We are cheaper than IP, we show what metals likely are within targets for metal, an at a higher definition suitable for drill rig placements. This costs 5570 US per square km, and it delivers, as we can see when we compare the work to even IP. #geostatistical_reservoir_modeling

#MostCited Landslide Susceptibility Mapping Based on Interpretable Machine Learning from the Perspective of Geomorphological Differentiation ✍️ by Deliang Sun, Danlu Chen, Jialan Zhang, Changlin Mi, Qingyu Gu, and Haijia Wen 👉 https://brnw.ch/21wKv21 #landslide #machinelearning #geomorphological

Join us on 31 July for a masterclass on machine learning for #Geoscientists! The instructor will be Tom Meuzelaar from Life Cycle Geo, LLC.! 👥 Focus For: #Geologists, Mine professionals, Environmental scientists, #Geochemists, Water scientists and engineers. If you're in any of these fields, this course is for you! 🔗 Register here: https://lnkd.in/dg9ffZ9m #EFGA #Geoscience #MachineLearning

Artificial Intelligence/Machine Learning application with G&G "expert knowledge" has been proven that, it can solve data limitations issues, and reduce the cost or need of acquiring more data. #geophysics #geology #oilfieldservices #subsurfacestudies #rockphysics #hydrocarbonexploration #machinelearning #artificialintelligence

I invite you to check our work on using deep learning for satellite data denoising on Mars: this is my PhD student Robert Platt ‘s first paper! #mars #deeplearning #machinelearning #geosciences

📊🌐Unveiling the Hidden World with Geoelectric 3D Visualization In an intricate dance of geoscience and technology, I've crafted a 3D visualization that not only reveals but also brings to life the electrical resistivity of subsurface materials. This geoelectric model is the culmination of meticulous data analysis and interpolation, powered by the robust capabilities of Python's libraries: pandas, numpy, matplotlib, and scipy. The interactive model is a journey through the earth's layers, showcasing resistivity variations across depths that span from a mere 1 meter to an astounding 464 meters. Each layer's data is meticulously transformed into a vivid, cubic landscape, offering a window into the unseen world beneath our feet. The color-coded representation on this geoelectric map is more than just visually striking—it's a key to unlocking the geological features and potential resources hidden underground. I invite you to join me in exploring the vast possibilities that emerge when we combine geophysical methods with cutting-edge data visualization techniques. Let's engage in a dialogue on how these insights can propel innovation in environmental research and resource management! #Geoelectric #3DVisualization #DataScience #Geophysics #EnvironmentalEngineering #Geology 🌐⚡ Make sure to attach the visual output from your code to captivate your audience. The power of visualization lies in seeing it! Explore more here: https://lnkd.in/ezZnFVYg

Did you attend last year’s Digital Geoscience Conference? Don’t miss out on the next in this conference series: ‘Digital Geoscience 2024: Intelligent Solutions in Geoscience’. Abstracts are currently being accepted until 12 AUGUST! Geoscientists, engineers, researchers and early career professionals are invited to submit abstracts that explore the intersection of geoscience and cutting-edge technology. Abstracts would be especially welcome related to artificial intelligence (AI) in Digital Geoscience as an overarching conference theme and the following additional areas: - Data Collection - Data Visualisation - Risk Management - High-performance Computing & Numerical Modelling Submit your abstract today for the chance to be featured in this cutting-edge conference series https://lnkd.in/eV3DjUgG #DigitalGeo2024 #DigitalGeoscience #DataGeoscience #DataAndGeoscience #GeoscienceAndAI #EarthScience #AIGeoscience #Geology #3DModelling #3DMapping #DigiGeo #Geoscience #DigitalGeo #Geolsoc

The #callforabstracts to the session "T34. #Landslide #monitoring, #modelling, and #prediction: bridging new #tools and #data to the 'slope-failure model' perspective" is now open (Deadline 26/04/2024) at SGI-GIMP joint congress "Geology for a sustainable management of our Planet " (Bari 3-5/09/2024). Contributions addressing #data #collection and #management at different scales are welcome, as well as discussions on the definition of #standards for data collection and storage. At the same time, contributions investigating the key issues for #landslide #hazard #modelling (where, why, when, how big and how fast and far) are encouraged. Convener: Edoardo Rotigliano Margherita Bufalini Stefano Luigi Gariano Luigi Guerriero Claudia Meisina Mario Parise