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60th Annual SPWLA Symposium

June 15 - 19, 2019
Booth 313, North Ballroom
Woodlands Waterway Marriott
1601 Lake Robbins Dr,
The Woodlands, TX 77380

Emerson is pleased to be a sponsor of the 60th Annual SPWLA Symposium, to be held in The Woodlands, Texas, June 15-19. Visit us in Booth 313 for a first look at the upcoming Geolog™ 19 release.  Among many new functionalities, the release includes new query and graph views that enable users to fully exploit the powerful and unique Geolog multi-well database, an interactive visual display that breaks down silos between geologists, petrophysicists, and production engineers, and a new Mud Gas Analysis module that allows safer drilling through early detection of gas kicks and lost circulation.

Emerson SME's will be on hand to provide demos of the new release, and show more of the product's features and benefits.

Available On-Demand Presentations

  • Automation in Geolog
  • Casing Inspection & Cement Evaluation in Geolog
  • Customization with Python
  • Formation Test Analysis and Pretest QC
  • Geomechanics and Pore Pressure Prediction
  • Image Analysis Capabilities in Geolog
  • Production Log Analysis
  • Uncertainty Analysis (Multimin and General Uncertainty Capabilities)
  • Using Geolog Facimage to Reveal High-Productivity Areas in an Unconventional Reservoir – A Case Study

For additional information, please contact Carmen Comis.

SPWLA Meeting on Petrophysical Data-Driven Analytics SIG

Emerson is proud to sponsor the SPWLA Meeting on Petrophysical Data-Driven Analytics SIG.  This meeting, being held on June 20 (the day after the Annual Meeting), will be devoted to such topics as Machine Learning, Deep Learning, Artificial Intelligence, Petrophysics, Interpretation and Reservoir Characterization.

Where:  Anadarko Corporation Headquarters, 1201 Lake Robbins Drive, The Woodlands, Texas 77380.  
To register, please click here.

Constantine Vavourakis, Team Lead Petrophysics & Drilling and Machine Learning Specialist at Emerson, will deliver two presentations:
  • Limitations of Naïve Machine Learning Approaches in Geosciences: The Example of Grain Size Prediction from Microresistivity Logs (11:30 AM)
  • Machine Learning Development in Geolog: Leveraging Deep Learning Techniques for Improved Log Prediction (1:00 PM)


Constantine-Vavourakis1.jpegConstantine Vavourakis has a BS degree in Geological Sciences from the University of Texas at Austin and a MS degree in Petroleum Geology from the University of Houston.  He has more than 8 years’ experience in E&P as a Research Geologist, Exploration Geoscientist, and Petrophysicist.  He has recently been researching how advanced machine learning and deep learning techniques can be applied to optimize Formation Evaluation workflows.