Machine Learning in Geoscience

Contact us at,,, or

Upcoming Events

Soon to be announced.


Past events

Machine Learning & Young Professionals Joint SIG Meeting (hybrid)
Date/Time: Thursday 13 July 2023 – 18:00-19:30
Part I 
Applications of Computer Vision in Earth Science – Dr. Cédric John, Imperial College
Part II  Artificial Intelligence in Reservoir Characterization: Challenges and Innovations – Dr. Mehdi Paydayesh, SLB

Date/Time: Thursday 23 February 2023 – 17:00-18:00
Guest Speaker: Paolo Dell’Aversana, geoscientist
Topic: Chat GPT-3 – a new alliance between artificial and biological intelligence

Date/Time: Thursday 24 February 2022 – 17:00-18:00
Guest Speaker: Ross 0’Driscoll – ION Geophysical
Topic: Deep reinforcement learning for random noise attenuation

Date/Time: Thursday 27 January 2022 – 17:00-18:00
Guest Speakers: Eshan Naeini, Earth Analytics
Topic: Denoising with Machine Learning with Application to Seismic Data

Date/Time: Wednesday 8 December 2021 – 17:00-18:00
Guest Speakers: Edward Jarvis, Haoyi Wang, Song Hou – CGG, UK
Topic: Petrographic thin section analysis with machine learning

Date/Time: Thursday 28 October 2021 – 17:00-18:00
Guest Speaker: Rebecca Head, Halliburton
Topic: Leveraging Supervised Machine Learning for Rapid Lithology Prediction 

Date/Time: Thursday 30 September 2021 – 17:00-18:00
Guest Speaker: TBC
Topic: TBC

Date/Time: Thursday 24 June 2021 – 17.00-18.00
Guest speaker: Olawale Ibrahim
Topic: Evaluation of Machine Learning Geoscience Predictions

Date/Time: Thursday 27 May 2021 – 17.00-18.00
Guest speaker: Dr Mark Vardy, Sand Geophysics
Topic: Machine Learning and the Marine Near Surface – Example Applications for Site Investigation

Date/Time: Thursday 29 April 2021 – 17.00-18.00
Guest speaker: Konrad Wojnar – Resoptima
Topic: Assimilation of 4D seismic data for probabilistic modelling using ensemble-based methods

Date/Time: Thursday 25 March 2021 – 17.00-18.00
Collaboration: This event was organised in collaboration with the Royal Statistical Society
Guest speaker: Stephen McGough, Senior Lecturer in the School of Computing, Newcastle University
Topic: An introduction to Generative Adversarial Networks and their uses

Date/Time: Thursday 25 February 2021 – 17.00-18.00
Guest speaker: James Lowell, R&D Director – Geoteric
Topic: AI Seismic Interpretation: Working with your digital co-worker, and can you trust them?

Date/Time: Thursday 28 January 2021 – 17.00-18.00
Guest speaker: Patrick Connolly – Consultant
Topic: Estimating facies probabilities from seismic data

Date/Time: Thursday 17 December 2020 – 17.00-18.00
Guest speaker: Jimmy Klinger – Schlumberger
Topic: How can mainstream data science drive innovation in the energy sector?

Date/Time: Thursday 26 November 2020 – 17.00-18.00
Guest speaker: Eirik Larsen – Co-founder and CEO, Earth Science Analytics
Topic: Creating value with data – Cloud-native and AI-assisted geoscience software

Date/Time: Thursday 29 October 2020 – 17.00-18.00
Guest speaker: Ali Moradi Tehrani – CGG
Topic: Hybrid Deep Machine Learning Inversion

Date/Time: Thursday 5 March 2020 – 18.00-12.00
Guest speaker: Earth Science Analytics
Topic: Capturing uncertainty in Machine Learning. Kindly sponsored by Earth Science Analytics


Join this SIG

Machine Learning has seen explosive growth in recent years and its methods of learning from data are already widely applied across many areas such as life sciences, finance and social media. Driven by rapid developments in learning algorithms, advances in computing infrastructure and increasing amounts of data from which to learn, machine learning is also starting to play an increasingly significant part in hydrocarbon exploration and production. Machine learning offers the promise of increased efficiency in areas like seismic interpretation and petrophysical analysis, and in understanding the avalanche of data produced by various digital sensors. It also holds the potential to analyse and extract value from the vast amounts of legacy data that through lack of resources are currently left to gather dust.

The Machine Learning Special Interest Group welcomes all with an interest in the field from those who just want to learn a bit about the technology through to those who have experiences to share. We think it is important for us all, as users of this rapidly evolving technology, to be able to ask the right questions about the advantages and limitations of the methods we may increasingly come to rely on. So join this group for education and critical thinking about machine learning as well as networking in an informal atmosphere.

To join this Special Interest Group you must be a GESGB member. Please visit to find out more about becoming a member.