March 21 – 23


Day One
Wednesday March 22 2017

Day Two
Thursday March 23 2017

Breaking down Data Silos to Enable Better Integration & Sharing of Data

Chair’s Opening Remarks

Moving towards a Single Version of the Truth throughout the Data Value Chain

  • Mark Reynolds Senior Solutions Architect Technical E&P Applications, Southwestern Energy


  • Making the leap from data into solutions: Understanding data management challenges behind master data and planning data
  • Engineering challenges behind real-time/streaming data sources
  • Limitations of spreadsheets, BI, and user directed research

Cross-Sector Case Study: Enabling Meaningful Operational & Business-Wide Analytics through Breaking down Functional Silos

  • Ankit Lodha Analytics Operations Lead in Clinical Systems and Analytical Reporting, Amgen


  • Improving decision-making across the business and quantifying value of data through embedding common data models that enables access and integration of operational and ERP data
  • Incentivizing users to break down functional silos for enhanced business-critical analytics and enabling them to cut costs/increase production
  • Deriving value and securing buy-in from better analytics and visualization of real-time and historical data, including machine learning and predictive analytics

Morning Refreshments & Networking

Case Study: Integrating External Vendor Chemical Management Data into In-House Data Sets to Enhance Business Value


Chemical programs are often one of the top cost drivers for ongoing LOE costs, but frequently these programs are managed by third party vendors with operators having little insight into the actual chemical usage in the field or its effectiveness. This presentation will outline EP Energy’s challenge and solution to this issue:

  • Issues with third party chemical management and the inability to easily view chemical usage
  • The absurdity of trusting a chemical provider to self-report on their own effectiveness
  • Engaging with the vendor to standardize, clean-up, and gain access to chemical data
  • Integrating chemical data into internal systems
  • Presenting chemical data in the context of other relevant production data in an analytical workbench

Overcoming E&P Data Management Challenges to Enable Better Analytics

  • Paloma Urbano IT Director, E&P Data Management Portfolio & Strategy, ConocoPhillips
  • Sanjay Mehta Manager, Advanced Analytics, ConocoPhillips


By exploring the application of analytics in the E&P lifecycle this session will discuss the data management challenges with using traditional E&P applications and analytical platforms to accelerate the adoption within an organization.

  • Identifying the data management issues and strategies that support or remove the friction for widespread adoption of analytics
  • Data Management process and technology changes to enable efficient integration and access of data across analytic platforms
  • Bridging data management environments for traditional E&P applications and analytics case studies, including in the different stages of the E&P lifecycle
  • Trends in analytical platforms and their suitability to integrate E&P data
  • Upskilling for analytics, different skills are required from the traditional G&G skills, who and how?
  • Value of analytics versus investments, making a case for the investment
  • How and when to transition from ad-hoc analytics to pervasive analytics

Lunch & Networking

Data Visualization & Analytics That Unlocks the Full Value of Data

GPU Accelerated Analytics for Understanding Upstream Datasets

  • Joe Eaton Technical lead for Accelerated Graph and Data Analytics, NVIDIA


  • Learn about the breakthrough capabilities GPUs can bring to data analytics
  • Learn about the features in nvGRAPH for understanding large connected datasets
  • See the roadmap for data analytics on the NVIDIA platform

Making the Best Operational & Financial Business Decisions Based on Analytics of Improved Data

  • Jim Claunch VP Operations Excellence, Statoil North America


  • Working closely with end users of information to understand their requirements and ensuring analytics is delivering on need
  • Using data lakes/data hubs to correlate datasets for more effective analytics and reporting
  • Better prioritizing equipment such as pumpers through correlating production and financial profitability data from current or historical well downtime events
  • Spotfire and other tools to best present data as real-time data analytics emerges in the industry
  • Understanding and overcoming the security challenge around correlating information that is created behind firewalls, particularly with the increasing prevalence of IoT technologies

Making the Most of Your Data: Emerging Use of Advanced Analytics Tools


  • Ensuring your data is prepared for quality insights from predictive analytics, cognitive computing, machine learning and AI
  • Enabling better text and image recognition
  • Static and dynamic visualization to empower end users with better models and insights
  • Using data more effectively to gain a competitive business advantage

Afternoon Refreshments

Cross-Sector Case Study: Operational Real-Time Analytics of Big Data in the Pharma Sector to Increase Business Value & Buy-In


  • Overcoming functional data silos and proprietary data challenges to enable real-time and predictive analytics of large datasets that generate business value
  • The emergence of natural language processing, AI, cognitive computing and image recognition software in the pharma sector
  • Data cleansing and interrogation of unstructured text and binary files to enable deeper analytics
  • Gaining acceptance of big data analytics outcomes by eventual users through ensuring good data in leads to good reporting out and showing ROI
  • Enabling deeper analysis of data through mining big data

Using AI & IIoT for End Users to Gain Meaningful Insights for Cost Reduction & Production Optimization

  • Stephen Taylor Manager - Reporting, Analytics and Data Management, Devon Energy

Chair’s Summary

Close of Conference