The New IT Paradigm in Data Driven Energy Three years ago, Machine Learning, 4th Scientific Paradigm, and eScience were seldom discussed in O&G. Today, these topics and the role of data, data knowledge, and artificial intelligence are topics found in planning, engineering, and improvement. The New IT Paradigm and the pragmatic realities of Data Driven Energy are explored in this presentation.

1. Mark Reynolds
Mark Reynolds
Digital Transformation &Data Driven Solutions
Principal Architect / Systems Engineer
Machine Learning in O&G
The New IT Paradigm in a Data Driven Energy
April 18-19, 2018

2. Presentation Synopsis
The New IT Paradigm in Data Driven Energy
Three years ago, Machine Learning, 4th Scientific Paradigm, and
eScience were seldom discussed in O&G. Today, these topics and the
role of data, data knowledge, and artificial intelligence are topics
found in planning, engineering, and improvement. The New IT
Paradigm and the pragmatic realities of Data Driven Energy are
explored in this presentation.

3. The Structure of Scientific Revolutions
• Normal Science
• Equilibrium, harmony
• Model Drift
• Outliers cease to be outliers
• Ripples turn to discontinuity
• Model Crisis
• Alternate methods permitted
• Out-of-the-box reconsidered
• Model Revolution
• New model becomes the new-normal
• Paradigm Change
• (Textbooks play catch-up)
Normal
Science
Model
Drift
(Anomaly)
Model
CrisisModel
Revolution
Paradigm
Change Kuhn
Cycle
Source: Thomas Kuhn, (1962) The Structure of Scientific Revolutions. University of Chicago Press
Mark Reynolds, compilation

4. Past Paradigm Shifts
• Seismic
• Horizontal Drilling
• Off Shore
• Factory Drilling
• The New Normal
• Economics
• Health Safety Environmental Regulatory
(HSER)
• Big Crew Change
• Mobility (anytime, anywhere)
Paradigm Shifts in Process
• The New Normal
• Economics
• Health Safety Environmental Regulatory
(HSER)
• Big Crew Change
• Mobility (anytime, anywhere)
• Big Data (aka ML, AI, etc)
• IIoT (+ Edge Computing)
• Uber Real-Time
• Cloud
• DevOps
Data Driven Energy: Shifting Paradigms in O&G, OT, and IT
Source: Mark Reynolds, compilation

5. Data Driven Energy: The 4th Scientific Paradigm
Descriptive
and
Formulaic
Hypothetical
and
Investigative
Expertise
Driven
Models and
Cases
Multivariant
Differential
Modelling
eScience
Traditional Science
Source: Mark Reynolds, compilation

6. The eScience Scientific Paradigm in Data Driven Energy
• O&G is where we found itEmpirical
• O&G is where we expect itTheoretical
• O&G is where we estimate itComputational
• O&G is where we infer it
Data
Exploration
Source: Mark Reynolds, compilation
Machine Learning
IIoT + Edge
Uber Real-Time
Cloud
DevOps

7. ML + AI
IIoT + Edge
Uber Real-Time
Cloud
DevOps
The New IT Paradigm in Data Driven Energy
Source: Mark Reynolds, compilation

8. Continuous Improvement Alone
Won’t Be Enough
• “Continuous improvement
never transformed a candle
into a light”
• “Horses have never improved
to the point they become cars”
Why All of these Paradigm Shifts
Matter
• “There is more oil in our filing
cabinets than we’ve ever
pumped”
• “If you want to find the new
oil, look under the old oil”
Quotes and Quips Along the Journey
Source: Mark Reynolds, compilation

9. The 4th Paradigm Quantum Shift in Data Driven Energy
Acquire Analyze Annunciate Archive Analyze Anticipate Apply
Data
Information
Visualization
Knowledge
Forensics
Understanding
Analysis & Mining
Wisdom
Anticipating
Application
 Creating Informational Accessibility and Transparency
 Discovering Experiential Performance Improvements
 Segmenting Processes and Process Results
 Automating Decisions and Processes
 Innovating New Models, Products, Services
Real-Time & 24/7 Data-Intensive Scientific Discovery --- the 4th Paradigm
 Creating
 Discovering
 Segmenting
 Automating
 Innovating
Source: Mark Reynolds, compilation
Descriptive Analytics Diagnostic Analytics Predictive Analytics Prescriptive Analytics Cognitive Analytics

10. Operations Technology
• engineering applications
• operations and field automation
(SCADA) systems
Information Technology
• data center
• networks (WAN & LAN)
• desktop support
• enterprise application platforms
The New OT & IT Paradigm in Data Driven Energy
Source: Jim Crompton,, NOAH Consulting Operational Technology (OT) vs. Information Technology (IT), February 2017
http://www.infosysblogs.com/noah-consulting/2017/02/operational_technology_ot_vs_i.html
Shadow IT
Informal community of highly digitally literate engineers and
operators … This "Innovation on the Edge" approach often
competes quietly with the "standardization from the center"
initiatives from corporate IT.

11. Convergence of OT and IT
“As more companies work toward IT/OT alignment, the CIO and
the IT organization will be at the forefront of fostering
relationships and changing the culture of the organization,” said
Kristian Steenstrup, distinguished analyst and Gartner Fellow.
“This will require a hybrid of traditional IT and OT skills and
development of new intellectual property, while experience
external to the company will be tapped into to assist with cross-
topic education.”
Source: Christy Pettey,, When IT and Operational Technology Converge, January 2017
https://www.gartner.com/smarterwithgartner/when-it-and-operational-technology-converge/

12. Crossing the OT-IT Paradigm
Today Tomorrow
Integrated Systems Engineering
Entropy  Data
Data  Information
Information  Knowledge
Knowledge  Understanding
Understanding  Wisdom
Wisdom  Application
Application  Cognitive

13. Integrated Systems Engineering – the New OT-IT Paradigm
Systems &
Knowledge
Engineer
O&G
Systems
Control
Systems
Remote
Systems
Information
Systems
Embedded
Systems
Robotic
Systems
Data Fusion
Real-Time
Systems
Look-Back
Analysis
Look-Ahead
Systems
Land and Regulatory
Geology Geophysics
Drilling Engineering
Completion Engineering
Production Engineering
Reservoir Engineering
Systems Engineering
Source: Mark Reynolds, compilation

14. Integrated Systems Engineering – the New OT-IT Paradigm
Land
Drilling
Reservoir Completion
Water
Production
Steering Regulatory
Midstream
Source: Mark Reynolds, compilation

15. Integrated Systems Engineering – the New OT-IT Paradigm
Proactive &
Closed-Loop
Systems
Mining and
Analytics
Forensics
Control
Visualization
and
Observation
Source
Capture and
Utilization
• Intelligence during operations (Observation and Anticipation)
• Intelligence reviewing operations (Forensic)
• Intelligence planning operations (Historical and Analytical)
Well
Plan RT
Prod
RT
Drill
Geo-
steer
RT
Frac
Daily
Rpts
AFE
  
  
Source: Mark Reynolds, compilation

16. Applying Systems Engineering to Data Driven Energy
• Physical Layer
• Electronic Interfaces – seismic, drilling, completions, production
• Data Layer
• Acquisition, filtering and cleansing, organization, accessibility
• Business Process Layer
• Procedures, workflows, best practices
• Visualization and Surveillance Layer
• Unified dashboards and integrated surveillance
• Intelligence, prediction, and automation layer
Source: Mark Reynolds, compilation

17. The New OT-IT Paradigm in Data Driven Energy
Traditional Technologies
• Computers
• Cell Phones
• LAN / WAN
• Master Data
• Applications
• Services
• Security
• Servers
• Data Movement
New Paradigm Technologies
• IIoT
• Edge Computing
• Real-Time Up-Time
• In-Situ Processing
• After-Action Reduction
• Data Dispersion
• Cross Application Integration
• Cross Platform Integration
• ML / AI

18. Crisis and Recovery Occurring Today in the Paradigm Shift
Pre-Crisis
Precipitating
event
Crisis mode
Time period of
Reconsidering, Realignment
Reassessing, and Reimagining
Enhanced capacity to cope
Diminished capacity to cope
Inability to cope
Normal
Science
Model
Drift
Model
Crisis
Model
Revolution
Paradigm
Changed Kuhn Cycle

19. Keep Your Eye on the Prize
Data
Information
Knowledge
Understanding
Wisdom
Application
The question is NOT
“How can we … ?”
But instead
“What is the objective?”
( or “Why?” )
Source: Mark Reynolds, compilation

20. Mark Reynolds
Mark Reynolds Vitae
• Southwestern Energy
• Lone Star College
• Intent Driven Designs
• Scan Systems
• Sikorsky Aircraft
• General Dynamics
Personal Email: mark@DataDriven.Energy
Linkedin: www.linkedin.com/in/MarkDataDriven
Twitter: @MarkDataDriven
http://DigitalTransformation.Engineer
Copyright 2018 by Mark Reynolds 20