1. Corvelle Drives Concepts to Completion How Visual Analytics adds value to PPDM Datastores 1

2. Corvelle Drives Concepts to Completion Yogi Schulz Biography  Partner in Corvelle Consulting  Information technology related management consulting  Microsoft Canada columnist & CBC Radio guest  PPDM Association board member  Industry presenter: – Project World - 6 years – PMI – SAC - 3 years – PMI - Information Systems SIG - 2 years – PPDM Association - several years 2

3. Corvelle Drives Concepts to Completion Finding PPDM is like Finding Waldo 3

4. Corvelle Drives Concepts to Completion Where is PPDM? 4 Visual Analytics

5. Corvelle Drives Concepts to Completion Only the Presentation Layer is visible to end-users 5 Sophisticated Visual Analytics is useless without superior data

6. Corvelle Drives Concepts to Completion PPDM Growing Complexity, Growing Value 6 71,000 2,700

7. Corvelle Drives Concepts to Completion 7 When is your oil company moving to PPDM? You can’t keep storing all your big data under our bed!

8. Corvelle Drives Concepts to Completion Oil & Gas Data Warehouse Context Diagram Monthly Proprietary well data Monthly Public well data Data warehouse Daily Production data Monthly Financial data Monthly Public Frac data Monthly CAPEX Forecast data 8

9. Corvelle Drives Concepts to Completion Visual Analytics Application Context Diagram 9 Data warehouse Visual Analytics application GraphsTablesExportsReports VA app Summary data VA app Configuration data VA app Update

10. Corvelle Drives Concepts to Completion Visual Analytics 10 A picture is worth a thousand rows of data graph

11. Corvelle Drives Concepts to Completion Questionable Analysis Goals 11

12. Corvelle Drives Concepts to Completion Visual Analytics Definition Visual analytics combines automated analysis techniques with interactive visualizations to enable: – Effective understanding – Reproducible reasoning – Defensible decision-making in the context of large and complex data sets 12

13. Corvelle Drives Concepts to Completion Visual Analytics Goal  Synthesize information and derive insight from massive, dynamic, ambiguous, and often conflicting data  Detect the expected and discover the unexpected  Provide timely, defensible, and understandable assessments  Communicate assessments effectively for action 13

14. Corvelle Drives Concepts to Completion Producing Property Profitability Analysis 14

15. Corvelle Drives Concepts to Completion Optimizing Frac Design 15 More production

16. Corvelle Drives Concepts to Completion 16... And here we have our data visualization team. Dave is our pie chart specialist, Lenny is into bar graphs, and Spence is our scatterplot designer.

17. Corvelle Drives Concepts to Completion What is well downtime costing your company? Lost Production Actual Production 17

18. Corvelle Drives Concepts to Completion Daily Production Variance 18

19. Corvelle Drives Concepts to Completion 19 Big data will overwhelm our organization like this flaming asteroid! Don’t worry, I’ll call Bruce Willis!

20. Corvelle Drives Concepts to Completion Well Type Curve Analysis 20

21. Corvelle Drives Concepts to Completion Comparison of Actuals Sales to Estimates 21 Actual Sales far exceed Estimates Estimates far exceed Actual Sales

22. Corvelle Drives Concepts to Completion Recommendations  Improve your data management processes  Identify operational problem  Select visual analytics software package  Pilot software package for problem  Build on pilot success 22

23. Corvelle Drives Concepts to Completion Questions & Discussion 23 Can you help us implement visual analytics for PPDM? Please fill out evaluation form

24. Corvelle Drives Concepts to Completion How Visual Analytics adds value to PPDM Datastores Corvelle Consulting 300, 400 - 5 Ave. S. W. Calgary, Alberta T2P 0L6 Phone: (403) 249-5255 E-mail: YogiSchulz@corvelle.com Web: www.corvelle.com Yogi Schulz Partner of Corvelle Consulting Information technology related management consulting Microsoft Canada columnist & CBC Radio host Industry presenter Former PPDM Association board member 24

25. Corvelle Drives Concepts to Completion Bibliography  Do you need big data for big results? – http://www.corvelle.com/do-you-need-big-data-for-big- results/ http://www.corvelle.com/do-you-need-big-data-for-big- results/  Business Intelligence – experiencing more hype than value? – http://www.corvelle.com/business-intelligence- experiencing-more-hype-than-value/ http://www.corvelle.com/business-intelligence- experiencing-more-hype-than-value/  Is data modelling really dead? – http://www.corvelle.com/is-data-modelling-really-dead/ http://www.corvelle.com/is-data-modelling-really-dead/  Why you need visual analytics – http://www.corvelle.com/resources/articles/it-world- canada/why-you-need-visual-analytics/ http://www.corvelle.com/resources/articles/it-world- canada/why-you-need-visual-analytics/ 25

26. Corvelle Drives Concepts to Completion Value of Visual Analytics  Make data-driven decisions “very frequently”  Make decisions “much faster” than market peers  Execute decisions as intended “most of the time” 26

27. Corvelle Drives Concepts to Completion Digital Oil Field Survey  Upstream companies struggle with adequately managing information for analytical purposes  Data is typically stored within applications in nonstandard formats  Data is trapped within organizational silos  Real-time data from field sensors is managed independently by various organizational entities  Making progress in analytics requires action across multiple organizational silos 27

28. Corvelle Drives Concepts to Completion Opportunities from Superior Information Management  Improving utilization of existing data sets  Reinterpreting to identify closely missed targets  Identifying potential candidates from existing datasets  Reusing seismic pre-stack data archives  Reusing well datasets for: – well log re-processing – petrophysical analysis 28

29. Corvelle Drives Concepts to Completion Visual analytics is about: A. Displaying PPDM data as pretty pictures B. Using overly complex terms as a way of charging more for software licenses C. Representing data for analysis and insights in ways that resonate D. Over analyzing data to avoid reaching any actionable conclusions 29

30. Corvelle Drives Concepts to Completion PPDM is valuable because: A. It brings us together in a great mountain setting B. It offers terrific careers in information technology C. It improves productivity through improved data accessibility, accuracy and reliability D. It keeps software developers employed E. Improves communication among prickly explorationists and IT professionals 30

31. Corvelle Drives Concepts to Completion What is the difference between visual analytics and business intelligence? A. Very little; marketers prefer visual analytics because it sounds more sophisticated B. Less and less; visual analytics and business intelligence are merging into a unified platform C. A lot; visual analytics produces interesting, insightful, colorful graphs while business intelligence produces boring rows and columns D. Vast differences; visual analytics is for visual right-brain thinkers while business intelligence is for kinesthetic left-brain thinkers 31

32. Corvelle Drives Concepts to Completion How do production engineers really produce more oil & gas? A. Eavesdrop on their peers at Starbucks for ideas B. Rely on field operations to do a better job C. Diligently monitor wells and pursue optimization opportunities D. Harass their IS staff for better systems and PPDM data 32

33. Corvelle Drives Concepts to Completion What is the difference between a data mart and a data warehouse? A. A PPDM data warehouse typically contains multiple PPDM data marts B. A PPDM data mart typically contains multiple PPDM data warehouses C. One of the few topics that Bill Inmon and Ralph Kimball agree on D. I don’t know; ask your local DBA 33

34. Corvelle Drives Concepts to Completion How are data marts linked in a data warehouse? A. Very carefully B. With binder twine C. Not at all D. Using foreign key relationships E. Programmatically 34

35. Corvelle Drives Concepts to Completion Visual Analytics Software Packages Selection Criteria  Visual exploration  Augmentation of human perception  Visual expressiveness  Automatic visualization  Visual perspective shifting  Visual perspective linking  Collaborative visualization 35

36. Corvelle Drives Concepts to Completion Value of Visual Analytics  Eliminate guesswork  Answer business questions better & faster  Produce key business metrics consistently  Build insight into customers & problems  Learn how to streamline operations  Improve efficiency  Learn what your true costs are  See where your business has been, where it is now and where it is going 36

37. Corvelle Drives Concepts to Completion Value of Standards  Data can be exchanged in a seamless manner between systems, between companies and with regulators  Geoscientists and engineers no longer waste time resolving data quality lapses  When incidents occur, you have immediate access to trusted data 37

38. Corvelle Drives Concepts to Completion 38

39. Corvelle Drives Concepts to Completion Duplicate 39

40. Corvelle Drives Concepts to Completion 40 How’s the big data project coming along, Hoskins?

41. Corvelle Drives Concepts to Completion How to Write a Resume 41 Do you have any expertise in SQL? Doesn’t matter Write: “Expert in NoSQL”.

42. Corvelle Drives Concepts to Completion 42 Having all this PPDM-managed data available for our wells is great, but I think I need a degree in data analytics to sort it all out.

43. Corvelle Drives Concepts to Completion Bulking Up the Data Management Staff 43 Let me introduce you to James, our data steward, Bill, our data custodian and “Moose”, our data bodyguard.

44. Corvelle Drives Concepts to Completion 44

45. Corvelle Drives Concepts to Completion Making Big Data Actionable 45

46. Corvelle Drives Concepts to Completion Business Value of Analytics Reactive Hindsight vs. Proactive Foresight 46

47. Corvelle Drives Concepts to Completion Data Volumes Growing each Year 47

48. Corvelle Drives Concepts to Completion 48 My doctor says my hair loss is caused by me worrying about data loss!

49. Corvelle Drives Concepts to Completion 49 Trust me. Our cloud security is so good, even you won’t be able to access your data!

50. Corvelle Drives Concepts to Completion 50 Any chance I could get better, faster, cheaper visual analytics instead?

51. Corvelle Drives Concepts to Completion 51 We have a nice-looking trend line here. I want thank the entire team for contributing this data, including Gerald, for the outlier.

52. Corvelle Drives Concepts to Completion Factors in Seismic Data Growth  New algorithms  Multi-component datasets  Fold increases from 40 to 400  Bin grids decreased 110’ to 82.5’ on a side  Process at 2ms rather than 4ms 52

53. Corvelle Drives Concepts to Completion PPDM Value Proposition  Controls information technology costs  Improves productivity through improved data accessibility, accuracy and reliability  Increases fraction of available software that can be utilized  Improves consistency of communication among explorationists and IT professionals 53 Profitable, productive wells

54. Corvelle Drives Concepts to Completion About PPDM Driving better business decisions through E&P data management standards Through the PPDM Association, petroleum data experts gather together worldwide in a collaborative, round table approach to engineer: – business driven – pragmatic data management standards that meet industry needs 54