Machine Learning in Geoscience

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Upcoming events

Date/Time: Thursday 28 January 2021 – 17.00-18.00
Guest speaker: To be confirmed
Topic: To be confirmed
Register here

Past events

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

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.

Organisations wishing to sponsor the Machine Learning SIG should contact:

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


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