Speaker: Troy Ruths, CEO, Ruths.ai

1. Petro.ai:
Big Data, Data
Science & Chat
Unite in Oil & Gas
Troy Ruths
CEO, Ruths.ai

2. Quick Intro
• Raised in Indonesia
• PhD in CS (Genetics)
• Founded Ruths.ai
• Data Science company
• 14 and growing fast

3. Ruths.ai Sprint System
We ONLY WORK for 90 minutes. We ONLY RELAX for 30 minutes.
• 40% more team productivity
• Everyone is happier
• We go home to our families
09:00-10:30
11:00-12:30
13:30-15:00
15:30-17:00

5. Energy is all around us…and underneath us

7. Two of the most impactful new technologies revolutionizing our economy
hail from Texas: horizontal drilling and hydraulic fracturing.
Silicon Valley disruption in the heart of Texas
1 Trillion BBLs Recoverable > $60 Trillion Market
Cloud, Social, Content = $2.3 Trillion,
< 6% of Unconventional US Market

8. Vision
Our vision is to create intelligent software that serves as a thinking
partner, trusted and accessible to all, in solving the world’s energy
challenges.
We do this with data science and analytics.

9. It’s not easy work
Explore Plan Drill Complete Produce
SpatialTemporal
High-
Frequency
Hierarchical
NetworkTreatments
Cyber
Physical
Uncertainty
Data
Quality
Human
Input
Interpretations

10. Ruths.ai Platform
• Browse library
• Launch workflow
• Load in private data
• Save or share results

11. Analytics…powered by MongoDB
Document Model Chat Data Science

12. Real-time Drilling

13. Why MongoDB?
Modeling
Performance
Ease of
Use
• WYSISYG Data Model
• Powerful Libraries
• Flexible Indexes
• Real-time Speed
• Scalability
• Low TCO
• Administration
• Tool Ecosystem
It’s the only NoSQL database a
SQL person can set up and run

14. Document Model
• We used .Net Library (C#) with strong data types
• Best practices for document types: spatial, time series
• Designing:
• Transactional History model,
• User personas, and
• Group Security on Documents

15. C# .Net Library… is Awesome
Algorithm Data IO Jobs

16. Design: Geo Spatial
• MongoDB provides full spatial index and aggregation
support
• Documents can contain GeoJSON objects:
• Points
• Lines
• Polygons
• Searches can find intersections or closest features
• Performance beats most spatial libraries

17. Design: Time Series
• MongoDB supports time index and aggregation
• Documents can store dates as:
• Milliseconds since the Epoch (1/1/1970)
• ISODate()
• String, “2017-02-08”
• High frequency data is typically filtered and aggregated on
ingestion

18. Transactions
• Keep robust activity log
• All user/server actions are kept with _id
• Any document (created, updated deleted) holds activity log id
• Produce robust audit trails of modifications by whom, when
Root Document
• createdActivityId
• lastUpdatedActivityId
• deletedActivityId
• dataTypes[]

19. Scalable Development Environment
Data Science
Restful API
NoSQL
ChatOps
End users can query, run calculations,
and stay up to date with a powerful
natural language engine
Immediately integrate with applications
or existing workflows with an easy-to-
use standards based API
Access to the latest data science
algorithms and techniques.
Extensible schema with the world’s
#1 backend.
Marketplace
Plugged in to the world’s largest oil and
gas analytics/workflow app store.

20. Chat
• Converse with any data types stored in
Petro.ai
• Run calculations
• Launch visuals and update models

21. Demo

22. Data Integration: Single View
• Well Header
• Well Production
• Well Forecast
• Type Curve
• Well Log
• Seismic
• Horizons/Grids
• Leases
• Wellbore Trajectory
• Stage Completion
• MV Models

23. MongoDB and Big Data
• Petro.ai can act as your big
data platform or talk with
existing big data
infrastructure.
• Spark with MongoDB
for calculations
• MapR in MongoDB for big
basics

24. Questions?