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Machine Learning in Geoscience 2020 – call for abstracts

Thu 20 February 2020

Category: Call for Papers, Community, Conference, Education

Exchanging insights, developments and new technologies

Wednesday 22 April 2020 l 9.00am – 5.00pm
Institute of Directors 
l 116 Pall Mall, London, SW1Y 5ED

PESGB are pleased to invite you to this year’s Machine Learning in Geoscience conference.

This event is a platform for operators, service companies, software & hardware providers, and academia, to share real-world examples and lessons learned in delivering machine learning in the oil and gas sector. We will focus on the challenges of applying the technology and illustrate solutions that can deliver increased project efficiencies and valuable insight into oilfield data.

Specialists from leading companies will come together to exchange insights on the latest developments and new technologies in machine learning. Case studies and interactive panel discussions will enable delegates to benchmark against industry best practices.

We are seeking abstracts for oral and poster presentations. Please send your abstracts to:
Abstract deadline: Monday 9 March 2020

Registration fees

PESGB member: £300
Non-member: £375
* Exclusive Machine Learning SIG and Concessionary
tickets available on request

Sponsorship Opportunities

Sponsorship opportunities are available and any offers will be gratefully received. These opportunities have been designed to suit all marketing strategies and budgets. Each opportunity will offer your company industry brand awareness at the event, with some offering additional exposure to the wider PESGB network. If you would like to discuss the opportunities available, please contact

Thank you to our Networking Sponsor

Join the Machine Learning SIG

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 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.

Click here to join


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