AI & Data Science
Sub brand
Back to top

Introduction

Date: Tuesday, December 14, 2021
Time: 9:00am – 10:00am CST
Duration: 1 hour


Collector estimation integrity and delays in exploration stages affect development costs and directly depend on the accuracy and speed of seismic data processing and interpretation algorithms. Join Gazprom Neft and NVIDIA to learn how neural networks label every voxel of a seismic field, marking a massive step towards eliminating uncertainty in petroleum production. In this webinar, the presenters will also demonstrate algorithms on actual field data built with an open source toolkit.



By attending this webinar, you will:
  • Learn about current industry standards for deep learning implementation in production
  • Explore the key elements of launching machine learning (ML) projects inside your organization
  • Get an advanced understanding of ready-to-use data processing pipelines
  • Find out how ML-specific libraries outperform current seismic algorithms
  • Obtain crucial knowledge about fast and accurate AI solutions
Join us after the presentation for a live Q&A session.

WEBINAR REGISTRATION

THANK YOU FOR REGISTERING FOR THE WEBINAR



You will receive an email with instructions on how to join the webinar shortly.

Main Content

maincontent goes here

Content

Content goes here

Content

content goes here

main image description

Content

Content goes here

Content

DGX Station Datasheet

Get a quick low-down and technical specs for the DGX Station.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.

Content

Content goes here

Speakers

Sergey Tsimfer

Lead Data Scientist, Gazprom Neft

Sergey Tsimfer leads a team at Gazprom Neft that develops deep learning algorithms for seismic interpretation. Each of the instruments are optimized to utilize resources effectively and can be easily adapted to similar tasks in geological exploration, which greatly accelerates each stage and maximizes GPU utilization. Sergey obtained an MSc of Applied Mathematics at Saint Petersburg State University.

Anna Dubovik

Head of Data Science Department, Gazprom Neft

Anna Dubovik and her group at Gazprom Neft have established and implemented standards for data science in the oil and gas community. This includes open tools and data for deep learning engineers in seismic processing and interpretation, benchmarking-ML competitions, hackathons, and online courses. Her previous work was in open source medical AI solutions development for CT and ECG data. Anna obtained an MSc in Machine Learning and Artificial Intelligence at Skoltech University in Moscow.

Nefeli Moridis

Developer Relationship Manager - Subsurface, NVIDIA

On the global energy team at NVIDIA, Nefeli Moridis focuses on helping to accelerate subsurface applications, such as reservoir simulation, onto GPUs. Prior to joining NVIDIA, Nefeli worked in the oil and gas industry as a reservoir engineer and as a consultant, focusing on projects in unconventional reservoirs in the U.S. and internationally. Nefeli holds PhD and MSc degrees in Petroleum Engineering from Texas A&M University, a MSc from the French Institute of Petroleum in Reservoir Engineering, and a BSc from the University of Texas at Austin in Petroleum Engineering.

Presenter 4 Name

Job Title 4

Presenter 4 Bio

Other Speakers

Name1

Job Title.
Name 2

Job Title.
Name 3

Job Title.

Content Title

Content here

Register

Webinar: Description here

Date & Time: Wednesday, April 22, 2018