A Geodyssey – Geoscience Text Analytics and Enterprise Search Research

My peer-reviewed critique in Geoenergy finds that African-led geoscience AI/ML capacity is significantly under-counted in research linked to the Deep-time Digital Earth (DDE) initiative.

The DDE-linked paper identifies just 8 African-...

Presented AI Ethics Recommendations for Geoscientists at the European Geosciences Union (EGU) in Vienna yesterday.

At around 20,000 attendees, the

Porosity and permeability prediction from petrographic point-counting data using machine learning. A new study from the Karlsruhe Institute of Technology has demonstrated that machine learning can accurately predict porosity and perme...

Open-source data: A Global-Scale Time Series Dataset for Groundwater Studies within the Earth System. Paper out this week in Nature from Bäthge et al (2026), introduces GROW (Global-scale integrated GROundWater dataset), a large, standardised, ...

Machine learning for sustainable geoenergy: uncertainty, physics and decision-ready inference. Interesting paper this week from Menke et al (2026) at the Institute of GeoEnergy Engineering, and Subsurface Energy Transition and Innovation Centre...