Artificially Intelligent Earth Exploration Workshop: Teaching the Machine How to Characterize the Subsurface

23–26 November 2020 | Virtual Workshop

ADVERTISEMENT

Our advertisers help SEG provide services to our customers. Please consider unblocking ads for our site.

Considering the differing guidelines and travel restrictions by each country and organization, SEG and the technical committee have collectively decided to move ahead with the workshop, virtually from 23-26 November ‘20.

About

23–26 November 2020
Virtual Workshop

While it is challenging to translate all aspects of the physical workshop within a virtual environment, we are committed to providing our attendees a unique platform with an immersive event experience to maintain the same depth in knowledge-sharing, engagement and networking, in order to guarantee a comprehensive online experience. Like the physical workshop, the virtual workshop will follow the technical program components such as opening & keynote speech, presentations from industry experts, and moderated discussions. The platform offers an optimized and powerful webpage experience – from the comfort of your home or office:

  • Stage: host all the presentations and discussions
  • Floor: overall floor plan where you can see the workshop schedule, sponsors and arrange a meeting
  • Lounge: attendees can grab a table and continue the discussions with 4 attendees on a table
  • VIP Lounge: One-on-one meetings
  • Live chat features for public discussion and Q&A
  • Links to recorded presentations via SEG on-demand after the workshop

Workshop Details

Technical Program now available in different time zones for your easy reference.

Artificial intelligence, and specifically machine learning, has become a powerful tool to address many of the challenges we face as we try to illuminate the Earth and make the proper prediction of its content. From image resolution enhancements, to fault detection, to horizon picking, the quest to teach our computing devices how to perform these tasks efficiently and accurately, as well as quantify the accuracy, has become a feasible and sought-after objective. Recent advances in computer power, machine learning algorithms, and the availability of the modules to apply such algorithms, have allowed the geoscientist to focus on the potential applications of such tools.

The objective of this workshop is to bring together interested individuals to share their experiences in applying machine learning algorithms in geoscience applications, especially applications related to the Oil and Gas sector. In addition, we’ll examine the various schools of thought in machine learning applications in the geoscience field to share advances and breakthroughs, highlight advantages and limitations, compare results, and debate emerging approaches in the world of artificial intelligence. What can we teach the machine, what can’t we teach it, and more importantly, what can it teach us?

The workshop will cover all related subjects that utilize machine learning to solve geophysical data analysis challenges in the Oil and Gas sector. This includes the application of machine learning methods in supervised, unsupervised, reinforcement, or any other method. Implementations may include numerous types of neural networks, like deep, feed-forward, convolutional, recurrent, GAN to the tasks solved by linear regression, SVM, and many other applications.

Organizing Committee

Committee Co-Chair: Tariq Alkhalifah, King Abdullah University of Science and Technology
Committee Co-Chair: Ali Almomin, Saudi Aramco
Committee Co-Chair: Ali Al-Naamani, Petroleum Development Oman

  • Ahmed Riza Ghazali, Petronas
  • Dimitri Bevc, Chevron
  • Elita Li, Singapore National Unviersity
  • Hussein Mustapha, Schlumberger
  • Khalid Obaid, ADNOC
  • Robello Samuel, Halliburton
  • Saud Zakwani, Petroleum Development Oman
  • Song Hou, CGG
  • Tahar Ben Youssef, CGG
  • Thekriat Hussain, Kuwait Oil Company
  • Tianyue Hu, Peking University
  • Umair bin Waheed, King Fahd University of Petroleum and Minerals
  • Xiangliang Zhang, King Abdullah University of Science and Technology
  • Yang Liu, China University of Petroleum
  • Yang Ping, BGP
  • Yike Liu, Chinese Academy of Science

Contact

Anneke de Klerk
SEG Middle East
Telephone: +97143712710
Email: [email protected]

Attend

Registration Categories

Single Day Pricing (1/2 day Workshop)
US$95 (member) | US$120 (non-member) | US$30 (student)

Early Bird Registration Fee (4 x 1/2 day Workshop) (expires 2 November 2020)
US$340 (member) | US$415 (non-member) | US$75 (student)

Full Registration Fee (4 x 1/2 day Workshop) (begins 3 November 2020)
US$415 (member) | US$490 (non-member) | US$90 (student)

Group Rates

5 Pax - Full Registration Fee (4 x 1/2 day Workshop)
US$340 (member) | US$415 (non-member) | US$75 (student)

For Group and Student Registrations, please email [email protected].

Cancellation Policy

Written notice received by 16 November 2020 entitles registrants to a full refund of the registration fee minus US$50 for processing. No refunds will be issued after 16 November 2020. Substitutions are permissible with written approval by the workshop organizers. Notify Anneke de Klerk at [email protected] immediately to request a substitution.

Workshop Schedule

Monday, 23 November | 5:00 - 9:05 CST | 11:00 - 15:05 GMT | 15:00 - 19:05 GST
Tuesday, 24 November | 5:00 - 9:20 CST | 11:00 - 15:20 GMT | 15:00 - 19:20 GST
Wednesday, 25 November | 5:00 - 9:00 CST | 11:00 - 15:00 GMT | 15:00 - 19:00 GST
Thursday, 26 November | 5:00 - 8:35 CST | 11:00 - 14:35 GMT | 15:00 - 18:35 GST

Who should attend?

Geoscientists, data scientists and engineers from industry and academia who have an interest in all related subjects that utilize machine learning to solve sub-surface data challenges in the Oil and Gas sector.

Technical Program

Technical Program now available in different time zones for your easy reference.

The objective of this workshop is to bring together interested individuals to share their experiences in applying machine learning algorithms in geoscience applications, especially applications related to the Oil and Gas sector. In addition, we’ll examine the various schools of thought in machine learning applications in the geoscience field to share advances and breakthroughs, highlight advantages and limitations, compare results, and debate emerging approaches in the world of artificial intelligence. What can we teach the machine, what can’t we teach it, and more importantly, what can it teach us?

The workshop will cover all related subjects that utilize machine learning to solve geophysical data analysis challenges in the Oil and Gas sector.

Opening Address by Saudi Aramco & Petroleum Development Oman

Keynote Speakers

  • Aria Abubakar - Schlumberger
  • Daniele Colombo - Saudi Aramco
  • Lizhi Xiao - China University of Petroleum
  • Maarten de Hoop - Rice University
  • Stephane Gesbert – Shell
  • Steve Freeman – Schlumberger

Technical Topics:

  • Big Geo-Data    
  • Processing and Analysis
  • Intelligent Velocity Model Building         
  • Reservoir Geomechanics and Well Logging         
  • Automated Seismic Interpretation
  • Smart Reservoir characterization            

Sponsorship Opportunities

To maximize exposure and visibility for our partners, we offer an array of unique sponsorship opportunities designed to suit a range of budgets with specific target audiences for optimum return on investment. For a list of sponsorship opportunities and an application form for sponsorship, please contact us at [email protected] for additional information.

Register now

Important Dates

Early bird savings end:
2 November 2020

Back to Top

This website uses cookies. If you continue without changing your browser settings, you consent to our use of cookies in accordance with our cookie policy. You can disable cookies at any time. Learn more

We also use partner advertising cookies to deliver targeted, geophysics-related advertising to you; these cookies are not added without your direct consent.

 

8801 S. Yale Ave. Suite 500
Tulsa, OK 74137
Phone: 918-497-5500
Email: [email protected]

CONNECT with us

Don't miss a thing.

Visit your SEG Communications Center to update your communications preferences.

Don't have an SEG account? It's free to create one - and you don't have to be an SEG member.

Twitter facebook linkedIn instagram youtube
Featuring bonus content!