Opensource GEOAssist Agent V1.0 Released!

Iniital 19th August 2025 Post: I created an Open-source Geological AI App yesterday that lists reference literature and visualises plate reconstructions if relevant to the question. It was just to illustrate how we can use Large Language Models (LLM) to enable natural language querying of multiple sources, both unstructured and structured, to help us gather... Continue Reading →

Teaching rocks to speak

Teaching Rocks to Speak: The Promise of Large Geologic Models and Generative AI. If you are attending the IMAGE conference this month you may wish to pop over to see Andrew Davidoff’s presentation.In my opinion it’s a non-technical high level thought provoking piece on subsurface Multi-modal Large Language Models (MLLM) from the perspective of someone... Continue Reading →

Free webinar AI, Drones and Satellites for Geoscientists

Free webinar AI, Drones and Satellites for Geoscientists: Sponsored by AIPG, Geological Society of South Africa, Zimbabwe & West African Institute of Mining, Metallurgy and Petroleum.I will be joining renowned experts in their fields on September 24th for an educational webinar to talk about how AI is transforming the geological sciences.Glen Nwaila David HodgettsNatalie Brand... Continue Reading →

Google AlphaEarth Foundation models released in the Satellite Embedding Dataset in Google Earth Engine.

Google AlphaEarth Foundation models released in the Satellite Embedding Dataset in Google Earth Engine.“AlphaEarth Foundations is an artificial intelligence (AI) model that functions like a virtual satellite. It accurately and efficiently characterizes the planet’s entire terrestrial land and coastal waters by integrating huge amounts of Earth observation data into a unified digital representation, or "embedding,"... Continue Reading →

Identifying seismic reflection terminations using deep learning

Identifying seismic reflection terminations using deep learning. Interesting paper from AlGharbi et al (2025) automating seismic interpretation predicting seismic terminations.AbstractSeismic stratigraphy entails a regional scanning (reconnaissance) of seismic data to identify and annotate seismic reflection terminations. To identify these terminations in modern 3D seismic datasets, interpreters have to examine thousands of inlines and crosslines, which... Continue Reading →

A large-scale open-source 3D seismic dataset with labeled paleochannels for advancing deep learning in seismic interpretation.

A large-scale open-source 3D seismic dataset with labeled paleochannels for advancing deep learning in seismic interpretation. Interesting paper from Wang et al (2025).Abstract“Identifying paleochannels in 3D seismic volumes (seismic paleochannel interpretation) is essential for georesource development and offering insights into paleoclimate conditions. However, it remains a labor- intensive and time-consuming task. Deep learning has shown... Continue Reading →

INGV AI Day

Enjoyed presenting the keynote at INGV 'AI Day' today. How we ethically design, educate, promote and use Language Models within the geosciences is likely to be of increasing importance.

Can you create a classification model to identify landslides? AI for Good, University of Cambridge, ESA, WMO challenge.

“Landslides, triggered by natural events like heavy rainfall and earthquakes, pose significant risks to lives, infrastructure, and the environment. Effective monitoring and mapping of landslides are crucial for mitigating these risks, guiding emergency responses, and supporting resilient infrastructure planningUsing multi-source satellite data, you will work to create an accurate landslide detection model. This model should... Continue Reading →

Delighted to be invited to give the keynote at INGV day on July 9th. “The future of AI in the Earth Sciences”.

Delighted to be invited to give the keynote at INGV day on July 9th. “The future of AI in the Earth Sciences”.“Participants at AI@INGV Day will first and foremost find a concrete opportunity to connect with colleagues and groups already working on Artificial Intelligence within the Institute.This will be a valuable moment to meet, share... Continue Reading →

Pix2Geomodel: A Next-Generation Reservoir Geomodeling with Property-to-Property Translation.

Pix2Geomodel: A Next-Generation Reservoir Geomodeling with Property-to-Property Translation. Interesting paper from Al-Fakih et al (2025).Conclusions“This study presented Pix2Geomodel, a pioneering conditional GAN framework, to enhance geological modeling of the Groningen gas field’s Rotliegend reservoir. By leveraging Pix2Pix architecture, the framework successfully predicted facies, porosity, permeability, and water saturation from masked inputs and facilitated property-to-property translation,... Continue Reading →

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