How Visual Analytics adds value to PPDM Datastores

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

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

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

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

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

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

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

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

Visual Analytics Application Context Diagram VA app Configuration data Graphs Data warehouse VA app Update Visual Analytics application VA app Summary data Tables Corvelle Drives Concepts to Completion Reports Exports 9

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

Questionable Analysis Goals Corvelle Drives Concepts to Completion 11

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 Corvelle Drives Concepts to Completion 12

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

Producing Property Profitability Analysis Corvelle Drives Concepts to Completion 14

Optimizing Frac Design More production Corvelle Drives Concepts to Completion 15

. . . 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. Corvelle Drives Concepts to Completion 16

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

Daily Production Variance Corvelle Drives Concepts to Completion 18

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

Well Type Curve Analysis Corvelle Drives Concepts to Completion 20

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

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

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

How Visual Analytics adds value to PPDM Datastores Yogi Schulz Partner of Corvelle Consulting Information technology related management consulting Microsoft Canada columnist & CBC Radio host Industry presenter Former PPDM Association board member Corvelle Drives Concepts to Completion Corvelle Consulting 300, 400 - 5 Ave. S. W. Calgary, Alberta T 2 P 0 L 6 Phone: (403) 249 -5255 E-mail: Yogi. Schulz@corvelle. com Web: www. corvelle. com 24

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

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

Digital Oil Field Survey q Upstream companies struggle with adequately q q 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 Corvelle Drives Concepts to Completion 27

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

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 Corvelle Drives Concepts to Completion 29

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

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 Corvelle Drives Concepts to Completion 31

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 Corvelle Drives Concepts to Completion 32

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 Corvelle Drives Concepts to Completion 33

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 Corvelle Drives Concepts to Completion 34

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

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

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

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Duplicate Corvelle Drives Concepts to Completion 39

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

How to Write a Resume Do you have any expertise in SQL? Doesn’t matter Write: “Expert in No. SQL”. Corvelle Drives Concepts to Completion 41

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. Corvelle Drives Concepts to Completion 42

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

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Making Big Data Actionable Corvelle Drives Concepts to Completion 45

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

Data Volumes Growing each Year Corvelle Drives Concepts to Completion 47

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

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

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

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

Factors in Seismic Data Growth q New algorithms q Multi-component datasets q Fold increases from 40 to 400 q Bin grids decreased 110’ to 82. 5’ on a side q Process at 2 ms rather than 4 ms Corvelle Drives Concepts to Completion 52

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

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 Corvelle Drives Concepts to Completion 54