CO-SPONSORS

Darktrace tessella

Get Involved With The Event

Sponsorship & Exhibition Opportunities Are Limited


Contact us on sponsorship@lbcg.com to reserve an exhibition booth and/or discuss how you can present a white paper case study, in one of these areas

  • IoT Technology
  • Industrial IoT Solutions for Oil & Gas
  • Digital Transformation Solutions
  • Digital Oilfield Technology
  • Cloud Platforms
  • Machine Learning Technologies & Applications
  • Machine Learning Training Services
  • Cloud-Based Machine Learning Software
  • Workflow Management Solutions
  • Plug-and-Play Platform
  • AI Software for Oil & Gas
  • AI Technology for  Oil & Gas
  • Augmented Reality (AR) Applications
  • Data Science & Analytics
  • Predictive Analytics
  • Data Extraction
  • Data Protection
  • Network Security
  • Communications Management
  • Edge Devices/Gateways

Meet, Network With & Learn From Senior Business Decision Makers & Technical Infleuncers


Including CEOs, VPs, Heads, Directors, Managers, Team Leads, Chiefs, Managers, Supervisors, Engineers, Scientists, Administrators, Architects of...

  • Data
  • IT
  • IoT
  • Machine Learning
  • Innovation
  • Technology
  • Automation
  • Research & Development
  • Digital Transformation
  • Business Solutions
  • Operational Excellence
  • Corporate Development
  • Plus Technical Titles Including:
  • Production
  • Operations
  • Drilling
  • Completions
  • Exploration
  • Reservoir

E&P DRIVEN SPEAKER LINE-UP LED BY

Jacob Melton

Jacob Melton

Data Scientist

Devon Energy

Alexander Klebanov

Alexander Klebanov

Data Scientist

Chesapeake Energy

Mohammad Evazi

Mohammad Evazi Yadecuri

Data Scientist

California Resources Corporation

Todd Heitmann

Todd Heitmann

Director Of Engineering Technology

Echo Energy

Chesapeake Logo

David Benham

Data Scientist

Chesapeake Energy

Huz Ismail

Huz Ismail

Data Scientist

Murphy Oil

Yuechen Li

Yuechen Li

Reservoir Engineer

Marathon Oil

Sean Aslam

Sean Aslam

Senior Data Science Analyst

Murphy Oil

Johnathan Hottell

Johnathan Hottell

SCADA Supervisor

EXCO Resources

Rob Graham

Rob Graham

Automation & Controls Specialist

Williams

Ryan Stalker

Ryan Stalker

Change Management & Organizational Development Specialist

Williams

Mark Reynolds

Mark Reynolds

Digital Transformation Engineer

Formerly Southwestern Energy

Ricardo Vilalta

Ricardo Vilalta

Associate Professor

University of Houston

Jeff Cornelius

Jeff Cornelius Ph.D.

EVP ICS Solutions

Darktrace

Maximizing Operational Efficiencies In Upstream Onshore Operations

MACHINE LEARNING & AI UPSTREAM ONSHORE OIL & GAS 2018
WHY NOW? WHAT'S CHANGED IN THE LAST 6-12 MONTHS?

In the last few months, more and more companies are starting to see Machine Learning being used in their day-to-day operations, not only as the way of the future, but as the way of now. Some companies are just getting started, others are figuring out how to get started, while others have multiple, on-going, established and successful projects. The universal truth is that everyone is interested in Machine Learning & AI, and at a stage where they are looking at 'what's possible' and 'how Machine Learning applies to day-to-day operations '.

They don't want to wait much longer.

Recognizing this, the team that brings you the industry-renowned Well Site Automation conference, is proud to announce the inaugural Machine Learning & AI Upstream Onshore Oil & Gas 2018 conference - focusing on understanding profitable applications of AI to optimize well production & operational efficiencies.

PURELY DESIGNED TO DELIVER SOLUTIONS FOR UPSTREAM ONSHORE OPERATORS

Operators, large, medium or small, are continually looking for ways to improve operational efficiency, make operations faster and more efficient, make assets run better, find bottlenecks in processes, find asset failures before they occur, eliminate unplanned downtime. What they are beginning to realize is that there are ways to improve every single one of those metrics using Machine Learning and AI.

The recent influx of AI technologies means the opportunity to process numerous real-time data sets, every minute of every day, and build models where you are able to quantity change and achieve even greater cost savings in the short term, all operational areas, is now within reach.  Production optimization is definitely where the real advantage is to solve engineering problems with Machine Learning and AI.

With this mind, the Machine Learning & AI Upstream Onshore Oil & Gas 2018 purely focuses on understanding the profitable applications of Machine Learning and AI, primarily for optimizing production for onshore E&Ps, and examine how to improve operational efficiencies in drilling and completions.

Showcasing Machine Learning & AI Business Cases, Practical Case Studies & Real-World Experiences To:

  • Increase Operational & Production Efficiency
  • Find Process Bottlenecks & Make Operations Faster
  • Pre-Empt Failure & Make Assets Run Better
  • Optimize Maintenance Schedules & Eliminate Unplanned Downtime
  • Control Internal Workflows
  • Optimize Drilling & Completions Decisions
  • Solve Exploration, Reservoir Simulation & Seismicity challenges
  • Generate Value & Profit From Real-Time Data And Well Intelligence
  • Achieve Additional Cost Savings & Properly Route Your Manpower

This Is USA's First Upstream Onshore Machine Learning & AI Conference - Don't Miss It!

On behalf of American Business Conferences, I look forward to welcoming you to Houston in August 2018.

Kind regards,

Alishba Jan

Divisional Director - Oil & Gas - American Business Conferences

Save $200

Agenda At A Glance

Machine Learning & AI Upstream Onshore Oil & Gas 2018

  • Establishing The Business Case For Machine Learning & AI : Demonstrating ROI and understanding 'What's possible' with AI in upstream oil & gas operations
  • Where Does Machine Learning Provide The Greatest Value? Know where the real opportunities exist to focus your attention and investment on bigger opportunities first
  • Deep-Dive Into What Has Been Accomplished Using Machine Learning : Best-in-class strategies for implementing operational Artificial Intelligence and Machine Learning in day-to-day operations
  • Optimize Production Performance & Efficiency : Use Cases to improve well productivity, optimize artificial lift cycle-time, detect anomalies on artificial lift equipment and optimize chemical usage
  • Predict Equipment Failure : Learn how to predict and eliminate equipment failure ahead of time using Machine Learning
  • Improve Equipment Reliability : Know exactly when to perform maintenance and on which equipment using Machine Learning models
  • Optimize Internal Workflows : Leverage artificial intelligence as a mechanism for internal workflow management
  • Embrace How To Collect, Use & Profit From Data : Overcome the full horizon of data science challenges, including Data Quality, Mixing, High-Grading, Transfer, Connectivity, Ownership, Security and Storage
  • Real-Time Drilling Optimization Using AI : Optimize decisions on Drill Bit Trajectory, Geosteering & Lateral Length Using AI tools
  • Optimize Well Design & Completions Using Machine Learning : Assess the value of data science to optimize well design and improve completions decisions
  • Solve Exploration & Reservoir Challenges : Learn how intelligent software systems can support exploration, reservoir development and seismicity management decisions
  • Change Management' & 'Skills Transformation' : Best practices for achieving employee buy-in, training internal staff and managing trust issues
  • Advanced Application Of Machine Learning Case Studies : Assess the true power of Machine Learning to increase operational efficiency
  • Cost-Effective Machine Learning Technologies : Assess functionalities and limitations of systems t hat are capable of Machine Learning

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