Earth A.D.’s Post

Remote Rensing techniques are commonly used to analyze vegetation patterns in mineral exploration. Here’s how remote sensing can be applied to leverage vegetation patterns for mineral exploration: 1. Satellite Imagery: High-resolution satellite imagery can capture detailed vegetation patterns over large areas. Multispectral and hyperspectral sensors onboard satellites can detect subtle variations in vegetation health, composition, and density, which may indicate underlying geological features or mineral deposits. 2. Vegetation Indices: NDVI, other vegetation indices such as Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI), and Chlorophyll Index (CI) can be derived from remote sensing data to assess vegetation health, vigor, and stress levels. 3. Change Detection: Remote sensing data can be used to monitor changes in vegetation cover and composition over time. Analyzing temporal changes in vegetation patterns can reveal areas of rapid vegetation growth or decline, which may be indicative of underlying geological processes or mineralization. 4. Feature Extraction and Classification: Remote sensing techniques, including image processing and machine learning algorithms, can be used to extract vegetation features and classify different vegetation types. These classified vegetation maps can then be analyzed to identify areas of interest for mineral exploration based on known vegetation-mineral associations. 5. Integration with Geospatial Data: Vegetation patterns observed through remote sensing can be integrated with geological, geochemical, and topographic datasets to generate prospectivity maps for mineral exploration. By combining multiple layers of information, geologists can prioritize exploration targets and refine target selection processes. 6. Ground Validation: Remote sensing-derived vegetation patterns can inform ground-based exploration activities, such as field mapping, soil sampling, and geophysical surveys. Geologists can use vegetation signatures as indicators to guide ground truthing efforts and validate remote sensing-based exploration targets. #RemoteSensing #geology #GeospatialAnalysis #EarthScience #GeologicalMapping #SatelliteImagery #Geoscience

Interesting work, but many others are missing in the reference, which is strange. Same structures can appear in different environments, it doesn't seem to be a robust approach. Here is a production example https://lnkd.in/gnTpK_Am 

[post not related to SLB] I play with Google Gemini Pro Vision to see if the model "knows" a little bit about Geoscience images (personal collection). To make it simple, I would say that: 'it depends'. The model can provide some very convincing interpretations as the one attached to this post. But in other illustrations, it can be totally out of scope. A tendency for Gemini Pro is to "speak too much" even after I asked it to stay factual and focused on the image content. For example, Gemini Pro systematically wants to locate any salt geology in the Gulf of Mexico 😂 even when nothing in the figure permits to locate it. It is just the beginning. There is a huge work to be done... to create the dataset needed for evaluating the Gemini Pro capacity in multimodal Geosciences understanding. And then, once evaluated, the Geosciences community could make a plan to make the model more aligned 🚀 #gemini #geosciences #multimodal #genai

Very interesting paper published by Di Martino et al last week in Nature, applying AI to core images to automatically interpret sedimentary facies. The authors closing statement reads, "During the last decades, a virtually continuous stratigraphic record of Holocene deposits in the Po Plain and beneath several coastal plains of Italy was acquired through core drilling. Robust high-resolution sequence-stratigraphic models that rely on information extracted from cores demonstrated that the stratigraphic architecture of Holocene successions worldwide exhibits striking similarities in terms of sediment facies distribution. Sediment core analysis based on semantic segmentation of continuous core images, thus, represents a highly reproducible technique that is likely to be exported successfully to other coeval stratigraphic successions, constituting a reference framework for future CNN-based subsurface analysis. The research approach presented in this paper is naturally suited for in-situ analysis and could substantially reduce the time and efort needed for detailed sediment facies interpretation, making it a valuable tool for large-scale exploration and for a broad range of industrial applications. The future integration of imaging data with other data sources, such as geotechnical and compositional data, and their incorporation in an automated method based on machine learning can make a substantial contribution to the progress of geological research below the ground surface." Link to the paper in the comments. #DigitalGeoscience #geosciences #artificialintelligence #machinelearning #geology #earthsciences #geotechnical

Geophysics driving Geological Outcomes Continental Drift Theory Continental Drift - the movement of continental land masses across the surface of the earth over long periods of geological time - is an idea that was first proposed and described by Alfred Wagner during the first decades of the 20th century - through his observation, analysis and interpretation of the interlocking shape of continental boundaries. Continental Drift Theory is defined as the geophysical phenomenon of continental motion extrapolated over long periods of geological time - which demonstrates that large land masses have been slowly drifting across the Earth’s surface since about 3.4 billion years ago. Alfred Lothar Wegener (1 November 1880 – November 1930) was a German climatologist, geologist, geophysicist, meteorologist and polar explorer. During his lifetime Wagner was principally known for his achievements in climatology and meteorology and as a pioneer of polar research - but today he is mostly remembered as the originator of the Continental Drift Hypothesis by suggesting that continents are slowly drifting around the Earth in 1912. Alfred Wagner’s Continental Drift Theory was not universally accepted until geophysical evidence of ocean ridge spreading was mapped in detail from the 1950’s - plotting mirrored strips of magnetic reversal at the same age either side of mid-ocean ridges in oceanic floor basalt. The Atlantic Mid- Ocean ridge formation is exposed at the surface in Iceland. As recently as the 1950’s a Professor of Geology at Leicester University was once asked by an undergraduate geology student, David Attenborough “why do you not teach Continental Drift?”. The Professor replies “if you can show me a mechanism which can transport huge continental masses for vast distances over the surface of the Earth over many eons of time – then I will teach Continental Drift!”. Metamorphism and the Evolution of Plate Tectonics (Nature) https://lnkd.in/dmv7qwEt

Geology hides within the spectral decomposition. If you are not looking at consistently and systematically generated RGB combinations of spectral decomposition in time, frequency, offset, vintage,++ …you are missing geology. OpenGeoSolutions Navigators include spectral decomposition across the full extents of your data…with “just enough” RGB blending in time/depth, frequency, offset, vintage… to help you vector in on the geology of interest. Screen opportunities faster with OpenGeoSolutions Objective Seismic Attributes and Navigator Visualization. This weeks missed opportunity – the time wasted generating a few RGB images with your current desktop software… when you could have fast, intuitive, consistent visualization of spectral decomposition across the full extents of your data. Discover the geology in your seismic! Contact OpenGeoSolutions for a data consultation. https://lnkd.in/grZhf7Hd #geology #seismic #geophysics #oilgas #oilandgas #seismic_attributes_analysis 20Hz Spectral Decomposition Time RGB with Spectral Discontinuity(TM) Reddish ==>Above Grey Scale ==> At Bluish ==>Below

Let me lay out a few differences between Gen Z geologists and older generation geologists. Please note that these are general observations and there will always be exceptions: 1. Technology Utilization: Gen Z geologists are usually more comfortable with using advanced technology and software. With the advent of digital mapping and modeling, GIS, remote sensing, and data analysis software, they are often more adept at leveraging these tools in their research and fieldwork. Older geologists, while they may also master these technologies, often started their careers with more traditional paper mapping and field notebook methods. 2. Communication Styles: Gen Z geologists are typically more proficient at using social media platforms and other online channels for networking, research, and knowledge sharing. They are also more likely to participate in online seminars and virtual conferences. In contrast, older geologists might prefer face-to-face meetings and traditional conferences. 3. Environmental Concerns: While geologists of all ages are concerned about the environment, Gen Z geologists appear to more proactively incorporate this concern into their work. There seems to be a greater emphasis on understanding human impact on the planet and exploring sustainable solutions in their research. 4. Interdisciplinary Approach: Geology is becoming increasingly interdisciplinary. Gen Z geologists are often trained to understand a wider range of topics, from climate science to biology, in order to understand complex Earth systems. Older geologists may have begun their careers with a more specialized and focused study of certain branches of geology. 5. Opportunities and Challenges: Gen Z geologists are entering a field that has many new opportunities, from renewable energy to Mars exploration, but also new challenges, especially related to climate change and societal impacts. Older generations may not have had the same kinds of opportunities when they started their careers, but also didn't face the same urgency around global issues. In the end, each generation brings its own strengths and perspectives, and both can learn a great deal from each other. #geologypage #geologist #geology #geologyhub

𝐆𝐞𝐨𝐥𝐨𝐠𝐢𝐜𝐚𝐥 𝐚𝐧𝐝 𝐆𝐞𝐨𝐭𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 is a comprehensive discipline that covers multiple fields such as Earth science, environmental science, and engineering. It includes multiple disciplinary directions such as geology, geophysics, geochemistry, geomorphology, meteorology, hydrology, soil science, ecology, environmental science, engineering mechanics, and geological engineering. 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐬 𝐢𝐧 𝐆𝐞𝐨𝐥𝐨𝐠𝐢𝐜𝐚𝐥 𝐚𝐧𝐝 𝐆𝐞𝐨𝐭𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 (𝑰𝑺𝑺𝑵: 2810-9384) is seeking high-quality research papers that advance our understanding of the behavior of soil and rock materials, as well as their interaction with structures and the environment. We welcome contributions from scholars and practitioners across a range of disciplines. 𝐂𝐥𝐢𝐜𝐤 𝐭𝐨 𝐠𝐞𝐭 𝐦𝐨𝐫𝐞 𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐚𝐛𝐨𝐮𝐭 𝐭𝐡𝐞 𝐣𝐨𝐮𝐫𝐧𝐚𝐥. https://lnkd.in/ge6wfJJw #geology #geotechnicalengineering #soilmechanics #rockengineering #geophysics #structuralgeology #geohazards #foundationdesign #tunnelling #miningengineering #geosustainability #environmentalengineering #earthworks #groundimprovement #geotechnics #geologicalengineering #slopeengineering #damengineering #infrastructureengineering

𝐆𝐞𝐨𝐥𝐨𝐠𝐢𝐜𝐚𝐥 𝐚𝐧𝐝 𝐆𝐞𝐨𝐭𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 is a comprehensive discipline that covers multiple fields such as Earth science, environmental science, and engineering. It includes multiple disciplinary directions such as geology, geophysics, geochemistry, geomorphology, meteorology, hydrology, soil science, ecology, environmental science, engineering mechanics, and geological engineering. 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐬 𝐢𝐧 𝐆𝐞𝐨𝐥𝐨𝐠𝐢𝐜𝐚𝐥 𝐚𝐧𝐝 𝐆𝐞𝐨𝐭𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 (𝑰𝑺𝑺𝑵: 2810-9384) is seeking high-quality research papers that advance our understanding of the behavior of soil and rock materials, as well as their interaction with structures and the environment. We welcome contributions from scholars and practitioners across a range of disciplines. 𝐂𝐥𝐢𝐜𝐤 𝐭𝐨 𝐠𝐞𝐭 𝐦𝐨𝐫𝐞 𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐚𝐛𝐨𝐮𝐭 𝐭𝐡𝐞 𝐣𝐨𝐮𝐫𝐧𝐚𝐥. https://lnkd.in/ge6wfJJw #geology #geotechnicalengineering #soilmechanics #rockengineering #geophysics #structuralgeology #geohazards #foundationdesign #tunnelling #miningengineering #geosustainability #environmentalengineering #earthworks #groundimprovement #geotechnics #geologicalengineering #slopeengineering #damengineering #infrastructureengineering

New Paper Alert! 🚨 My paper, "Target-oriented least-squares reverse-time migration with Marchenko redatuming and double-focusing: Field data application" has recently been published in Geophysics. Key Insights: 1. We successfully applied a target-oriented LSRTM algorithm using Marchenko redatuming and double-focusing, which accounts for all orders of multiple scattering in complex geological settings on a marine dataset. 2. This advanced method improves accuracy when imaging specific subsurface targets. 3. We demonstrate a double-focusing algorithm to significantly reduce data size, optimizing computational efficiency. 4. Our field data results from the Norwegian Sea highlight how this technique reduces internal multiple effects and produces higher-resolution images. Impact: This work contributes to the development of more precise and efficient subsurface monitoring solutions, particularly for #geothermal, #co2storage, and #hydrogenstorage applications. I'm grateful for the guidance and support of my supervisors, Prof. Kees Wapenaar and Dr. Joost van der Neut, throughout this research. I would also like to thank Dr. Eric Verschuur for fruitful discussions, and Prof. Alison Malcolm and three unknown reviewers for their constructive comments. Feel free to reach out if you'd like to discuss this research or its potential applications further! Link to the paper: https://lnkd.in/ehu__NvJ #Geophysics #LSRTM #seismicimaging #TargetOriented #Marchenko #redatuming #energytransition #subsurfacemonitorig