The IoT is a game-changer opening the Systems Engineer and the Data Scientist to the O&G Development teams. Upstream, mid-stream, and downstream segments of the market are confronted by the big question “Now what?”

1. Data Analytics and
Asset Management
Application of Data Collected
Through the IoT
Mark Reynolds
Senior Solutions Architect,
Upstream Integrated Operations
final – 09/15/2015

2. 1
Introduction to Southwestern Energy
Southwestern Energy Company is a growing
independent energy company primarily engaged in
natural gas and crude oil exploration, development and
production within North America. We are also focused
on creating and capturing additional value through our
natural gas gathering and marketing businesses, which
we refer to as Midstream Services.
Source: http://www.swn.com/

3. 2
This presentation addresses the ramifications of IoT to the
application of Systems Engineering process for O&G
Development teams. Particular attention will be given to the
methodology of IoT application and the challenges of the
Learning Organization.
Application of Data Collected Through the IoT
The IoT is a game-changer opening the Systems Engineer and
the Data Scientist to the O&G Development teams. Upstream,
mid-stream, and downstream segments of the market are
confronted by the big question “Now what?”

4. 3
What is IT? What is OT?
Information Technology (IT)
Traditional - Manage Corporate Accounting Data & Information
Transitional - Analytics (forensic, observable, predictive)
New / Evolving - Real-time (system control, observable prediction)
Operational Technology (OT)
Traditional - Machine Control
- Process and Flow Control
- Remote Monitoring
Source: Mark Reynolds, compilation
O&G
Systems
Engineer

5. 4
What is all of the Jibber-Jabber about IoT?
Simply put this is the concept of basically connecting any device with an on
and off switch to the Internet (and/or to each other). This includes
everything from cell phones, coffee makers, washing machines,
headphones, lamps, wearable devices and almost anything else you can
think of. This also applies to components of machines, for example a jet
engine of an airplane or the drill of an oil rig.
Source: Mark Reynolds, compilation
A Simple Explanation Of 'The Internet Of Things‘ https://www.linkedin.com/pulse/simple-explanation-internet-things-mohammad-parsa-rozbahani

6. 5
What is all of the Jibber-Jabber about IoT?
Connecting
Sensors
Terminals
Collecting
Interfaces
Standards
Accessing
Presentations
Ops Centers
Analyzing
Trends
Comparisons
Predictions
Integrating
Systems
Collaborations
Automations
Source: Mark Reynolds, compilation

7. 6
When will IOT Become a Game Changer?
2.5% 13.5% 34% 34% 16%
http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp 2015

8. 7
Where is IoT on the Gartner Hype Cycle?
Source: Gartner's 2014 Hype Cycle for Emerging Technologies Maps the Journey to Digital Business, August 11, 2014
http://www.gartner.com/newsroom/id/2819918

9. 8
How will Systems Engineering & Data Science Contribute?
Source: http://www.oralytics.com/2012/06/data-science-is
http://www.hanyang.ac.kr/code_html/Y3YABD/introEng/img/2.jpg
http://www.baynote.com/2013/06/whats-the-difference-between-a-data-scientist-an-engineer-and-an-analyst-actually-quite-a-lot/
Systems Engineering
is Multidisciplinary

10. 9
How will Systems Engineering & Data Science Contribute?
Source: http://www.oralytics.com/2012/06/data-science-is
http://www.hanyang.ac.kr/code_html/Y3YABD/introEng/img/2.jpg
http://www.baynote.com/2013/06/whats-the-difference-between-a-data-scientist-an-engineer-and-an-analyst-actually-quite-a-lot/
Multidisciplinary, but Different Disciplines

11. 10
How will Systems Engineering & Data Science Contribute?
Source: http://www.oralytics.com/2012/06/data-science-is
http://www.hanyang.ac.kr/code_html/Y3YABD/introEng/img/2.jpg
http://www.baynote.com/2013/06/whats-the-difference-between-a-data-scientist-an-engineer-and-an-analyst-actually-quite-a-lot/
System Engineer / Data Engineer / Data Scientist?
• Experienced, interdisciplinary engineer with a decent understanding of O&G
• Rock star software engineer with a decent understanding of statistics
• Provide the platform upon which the data can be modeled
• Core value lies in ability to [design &] prepare the data pipeline
• Understanding of … distributed computing and database
• Decent understanding of algorithms – O&G, Electronics, Software, Systems
O&G Systems – Data Engineer

12. 11
How does the O&G Systems – Data Engineer contribute?
O&G
Systems–Data
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-Data Engineering
Source: Mark Reynolds, compilation

13. 12
How do we Approach IoT in the 4th Paradigm?
Data
Modeling
• O&G is where we found it
Paradigm 1:
Empirical
• O&G is where we expect it
Paradigm 2:
Theoretical
• O&G is where we estimate it
Paradigm 3:
Computational
• O&G is where we infer it
Paradigm 4:
Data Exploration
Source: Mark Reynolds, compilation

14. 13
How do we Approach IoT in the 4th Paradigm?
Data
Modeling
Data
Acquisition &
Modelling
Collaboration
& Visualization
Analysis & Data
Mining
Dissemination
& Sharing
Archiving &
Preserving
Source: Mark Reynolds, compilation

15. 14
How do we Approach IoT in the 4th Paradigm?
Data
Modeling
Data Sources
•Spatial
•Temporal
•Asynchronous
•Real-Time
Field
Processing
•Signal Processing
•Exception Alerts
•Autonomous
•Streaming
24/7 Centers
•Data Centralization
•Field Operations
•Proactive
•Forensic
•Closed-Loop
Plan-
ning
•Analytics
•Improvements
•Systems
Source: Mark Reynolds, compilation

16. 15
How do we Approach IoT in the 4th Paradigm?
Data
Modeling
Source: Mark Reynolds, compilation
Logging
• Static
• Forensic
• Autonomous
• Assigned
Monitoring
• Streaming
• Real-Time
• Configurable
• Encompassing
IoT
• Streaming
• Interconnected
• Managed
• Pervasive

17. 16
What are the Challenges for Industrial IoT?
Computation
Real-Time
High Performance
Scalability
Communication
Time Synchronization
Determinism
Interoperability
Control
Adaptive Control
Design Methodology
Models of Computation
Computation
Heterogeneous Processing
Advanced Sensing
Modularity
Communication
Bandwidth
& Latency
Synchronization
Security
Design Approach
Complexity
Abstraction
Simulation
Source: National Instruments
http://www.slideshare.net/abuayd/talk-on-industrial-internet-of-things-intelligent-systems-tech-forum-2014-public
The Industrial IOT System
The Challenges

18. 17
What are Challenges in Learning Organizations?
The Learning
Organization
Personal
Mastery
Mental
Models
Building
Shared
Vision
Team
Learning
Systems
Thinking
Source: 1990, Peter M Senge
The Fifth Discipline, Doubleday/Currency, ISBN 0-385-26094-6
Collaborate
•Team Collaboration
•rather than
•Silos and Handoffs
Add Value
•Maximizing ROI
•rather than
•ROP
Orchestrate
•Orchestrating the Services
•rather than
•Delineating Jobs and Tasks
Responsive
•Planning to respond to change
•rather than
•responding to change in plans

19. 18
What are Challenges in Learning Organizations?
The Learning
Organization
Personal
Mastery
Mental
Models
Building
Shared
Vision
Team
Learning
Systems
Thinking
Source: 1990, Peter M Senge
The Fifth Discipline, Doubleday/Currency, ISBN 0-385-26094-6
Collaborate
•Team Collaboration
•rather than
•Silos and Handoffs
Add Value
•Maximizing ROI
•rather than
•ROP
Orchestrate
•Orchestrating the Services
•rather than
•Delineating Jobs and Tasks
Responsive
•Planning to respond to change
•rather than
•responding to change in plans
Learning to be Effective,
Not just Efficient

20. 19
How has Industry Requirements changed?
Previously Acceptable
• Proprietary
• Manual Rounds
• Schedule Based Maintenance
• Human Databases
• Limited Visibility
Today’s Demands
• Open Architecture
• Continuous Monitoring
• Predictive Maintenance
• Intelligent Advisors
• Advance Sensor Fusion
Source: National Instruments
http://www.slideshare.net/abuayd/talk-on-industrial-internet-of-things-intelligent-systems-tech-forum-2014-public

21. 20
Questions?

22. 21
Mark Reynolds
Mark Reynolds Vitae
• Southwestern Energy
• Lone Star College
• Intent Driven Designs
• Scan Systems
• Sikorsky Aircraft
• General Dynamics
• Southwestern Energy Email
– Mark_Reynolds@swn.com
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