7:00 am Breakfast Collaboration Roundtables


• Join up with Data and Business teams meeting to discuss how to advance analytics capabilities in:
Partner Roundtable Topic Leader Opportunity


8:15 am Optimizing Predictive Analytics and How This Effects E&P


  • Develop better predictive analysis of maintenance and equipment breakdowns and improve the whole operation
  • Optimize overall performance across all wells and reservoirs with comprehensive health and performance analytics to ensure decision makers stay ahead of critical situations
  • Understand the developing landscape of predictive analytics tools and which solution works best across different functions
  • Increase performance workflows for engineers with more access to analytics

9:00 am Achieving Improvements in Company-scale Capital Allocation with Reduced Physics and Deep Learning to Evaluate the risk/reward of new Completions in Workovers and New Drills



·         Learn how to integrate machine learning and physics knowledge to overcome issues with limited datasets and improve risk characterization of new completion opportunities.

·         See how to use the results from data driven pipelines to high-grade opportunities and incorporate data-driven risk/uncertainty into capital planning

·         Review case study, obstacles, and techniques for deploying data science into existing workflows and decision making to make a strategic impact and avoid getting stuck in the ‘POC’ project phase

10:00 am Morning Coffee & Exhibition

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Track A: Innovating Data Architecture for Advanced Analytics

Track B: Applied Analytics for E&P Optimization

10.30 The Benefits of Building IT Infrastructure to Enhance Machine Learning and Statistical Algorithms

  • Develop a clear plan to modernize IT infrastructure to best support the growing rate of new data processing technologies
  • Optimize statistical algorithms to obtain more data abilities and increase your competitive advantage

Scot Nesom, Data Management & Automation, Consultant

10.30 Data Analytics for Oil Corrosion Risk

  • Learn how to predict oil corrosion and what data analysis tools can we use to help this process
  • Build out your reservoir modeling to support OCR
  • Utilize analytics to lower maintenance costs across your operation

Paritosh Singh, Data Visualization Specialist, Shell

11.15 Why we need Data Democratization to Eliminate Silos

  • Obtain more value from data we need to understand how to safely democratize it
  • Learn how to create meaningful information by eliminating silos
  • Integrate data warehouses & eliminate silos to open up data to more people within the E&P process

Keith Modesitt, Data Science Lead, BP

11.15 Use Case – Leveraging Search Analytics to Improve
Exploration Operations

  • Optimize analytics solutions to improve exploration for new drilling opportunities
  • Build analytics to support your analysis of semantic unstructured data

Dryonis Pertuso, Integrated Operations -Advanced Analytics, Hess

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12:00 pm Lunch

Track A: Innovating Data Architecture for Advanced Analytics

Track B: Applied Analytics for E&P Optimization

1.00 Which came first: The Data or the Business Problem?

  • Learn how a data centric approach results in unnecessary data architectures and increased risk to adoption and business solutions
  • Put the business problems first to be more successful in your designs and efforts

Ansel Manning, Data Engineering Specialist, Chesapeake Energy

1.00 Robotics and Reinforcement learning for Oil Field Equipment Inspections and Analysis

  • The topic is on how to build self-learning algorithms for intelligent robotic systems which can do completely automated maintenance systems and generate recommendations and dill plans.

Jaijith Sreekantan, Senior Data Scientist, Schlumberger

1.40 How to Create more Automation within Your Data Management Process

  • Develop a technology strategy to support data management process through automation and which tools are most effective
  • Learn how autonomous databases can be utilised without compromising security
  • Understand the need to create more autonomation in the data management process to allow more bandwidth for higher level tasks

Scot Nesom, Data Management & Automation, Consultant

1.40 Distinguishing the Signal from the Noise:  A Well Performance Case Study

  • What is the signal and the noise?
  • What is the impact of following the noise?
  • What is the impact of following the signal?

Christina Berner, Senior Reservoir Engineer, Bonanza Creek

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2:20 pm Afternoon Coffee & Exhibition

2:45 pm Audience Discussion:Part one – The Continued Growth of Digital Oilfields


  • Discuss the best digital technologies that are helping upstream companies create better use of data
  • Share how predictive analytics are helping to for see equipment failure and reduce downtime
  • Understand how an open architecture approach can support a better mix of technology

2:45 pm Audience Discussion:Part two – Understanding the connection between Architecture and Analytics


  • Bridge the gap between data architecture and analytics with an open discussion of the two days learnings
  • Optimizing collaboration between all data functions and touch points to improve information sharing and decision making

3:45 pm End of Conference