Submit Now: Deadline 27 February

Rationale: 

It was clear at the EAGE/PESGB 1st Machine Learning workshop (PETEX, Nov 29-30, 2018) that there have been rapid advances in the application of Machine Learning (ML) for seismic, petrophysics, geology and reservoir modelling applications. However, some challenges need to be addressed, for example: 

• Is a data-driven approach such as machine learning optimal for the use case at hand? 
  
• Are we focussing too much on tactical rather than strategic improvements? 
  
• Can ML-derived results be interpreted and explained satisfactorily? 
  
• How do we introduce these tools and methods into our business? 
  

The challenges need to be addressed by a focussed forum and we see the annual EAGE meeting as an ideal gathering of thought leaders and stakeholders for this activity. 

Description: 

The workshop will discuss recently developed applications of ML, and the challenges and opportunities associated with the development of these applications in the petroleum industry. 

After a short survey of the expectations of potential participants, the first half of the workshop will consist of technical presentations of recent advances of ML, with an emphasis on Deep Learning. This will include: 

• “Speed posters” to act as an ice breaker at the start of the workshop. 
  
• A general overview of where Artificial Intelligence and DL are going in the industry, ideally from a digital leader of one of the major operators. 
  
• Technical presentations from petroleum companies and academia about recent applications. 
  
• The second half of the workshop will be dedicated to: 
  
• Recent industry initiatives on data availability, open communities, cloud computing and training, which are important drivers to facilitate the development of ML applications in the industry. 
  
• Perspectives from outside the industry, ideally from a major technology player, and an experienced practitioner of ML and AI capabilities. 
  
• Structured, themed and interactive exchanges with the audience. 
  

Who should attend: 

• Geoscientists and reservoir engineers interested in new developments in machine learning. 
  
• Academics, data scientists, machine learning professionals interested in upstream petroleum industry applications. 
  
• Students, service companies, developers, oil and gas company staff are welcome to attend.