Presented at Houston Hadoop Meetup by Kenneth Smith and Wade Salazar: Hortonworks upstream use cases.

1. 1 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Powering Data Driven
Transformations
Hortonworks in Oil & Gas

2. 2 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
DATA AT RESTDATA IN MOTION
ACTIONABLE
INTELLIGENCE
Modern Data Applications
PERISHABLE
INSIGHTS
HISTORICAL
INSIGHTS
INTERNET
OF
ANYTHING
Hortonworks
DataFlow
Hortonworks
Data Platform
Hortonworks Delivers
Connected Data Platforms…
Capturing perishable
insights from data in motion
Ensuring rich, historical insights on
data at rest

3. 3 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Field Data Capture Office or Datacenter
Hortonworks Industrial Data Analytics Platform – In Practice
WITSML
Files / Other Unstructured Data
Video
IoT Gateways
PLC / RTU
SCADA, DCS, Historians
Central HDP Cluster
Hive
Central HDF Cluster
NiFi
Kafka
Storm
Streaming
Options
HBase Solr
YARN
HDFS
Location 1
NiFi
Location n
NiFi
Data Center
Data Ingestion Framework
End users
DATA IN MOTION – HDF DATA AT REST – HDP
HDF Edge (MiNiFi + NiFi)
§ Reliable collection
§ Small footprint
§ Edge processing
§ Data provenance
§ Integrates with core
policies
HDF Core (NiFi with Streaming)
§ Processing at larger scale
§ Distributed stream processing
HDP
§ Security and data governance
§ Monitoring, management, operations
§ Applications
§ Analytics
Structured Data Sets

4. 4 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Oil & Gas Industry
Selected Use Cases

5. 5 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Cyber
Security
Analytics
G&G
Analytics
Yield
Analytics
Defect
Detection
Assess
Physical
Threats
Chemicals
and Refinery
R&D
Product
Design
M & A
Competitive
Analysis
Geo
Asset
Supply Chain
Pipeline
Surveillance
Leased
Sites
Business Unit
Leak
Detection
Mfg Process Customers
Basin
Records
Mgmt
Legacy
Offloads
Historical
Archive
Device
Data
Ingest
Rapid
Reporting
Digital
Protection
Well Planning
Real-Time
Operations
Risk Modeling IoT
Pre-Drill
Analytics
Route
Optimization
Reduce QHSE
Incidents
Trading
Surveillance
Equipment
Predictions
Equipment
Predictions
EDW
Archive
Data
as a Service
eDiscovery
Connected
Well
Seismic
Analytics
Public
Data Capture

6. 6 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
What
à Storing years worth of log files from all of their wells was very costly in legacy O&G systems and their EDW
à Analysts didn’t have access to log data stored in legacy systems and couldn’t use common analytic applications to perform data
science, build forecast models, predictive use-cases, etc.
à Existing platforms didn’t have the functionality to combine log data with data from other systems like auction history,
production data, seismic data, geolocation & perforation data.
Why
à Active archive broadens access to well log data which is otherwise only available to specialized software
à Serves as a foundational data set for future use cases where log data can be easily joined as part of other well and formation
analysis or data science
à Acceleration of geological and geophysical workflows and process automation
How
à Using HDP analysis can now store all of their historical log files at a fraction of the cost in addition joining that to well data from
other systems
à Analysts now have all log files in a single location with the ability to build “synthetic log files” comprised of data from
multiple sources and perform analytics on combined data sets from siloed applications.
Why Hortonworks?
Data Discovery
Blog post: http://hortonworks.com/blog/big-data-on-a-budget-in-oil-gas/
LAS Active Archive & Analytics

7. 7 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Field Data Capture Office or Datacenter
LAS Active Archive & Analytics – Reference Architecture
WITSML
Files / Other Unstructured Data
Video
IoT Gateways
PLC / RTU
SCADA, DCS, Historians
Central HDP Cluster
Hive
Central HDF Cluster
NiFi
Kafka
Storm
Streaming
Options
HBase Solr
YARN
HDFS
Location 1
NiFi
Location n
NiFi
Data Center
Data Ingestion Framework
End users
DATA IN MOTION – HDF DATA AT REST – HDP
HDF Edge (MiNiFi + NiFi)
§ Reliable collection
§ Small footprint
§ Edge processing
§ Data provenance
§ Integrates with core
policies
HDF Core (NiFi with Streaming)
§ Processing at larger scale
§ Distributed stream processing
HDP
§ Security and data governance
§ Monitoring, management, operations
§ Applications
§ Analytics
Structured Data Sets

8. 8 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Blog post: http://hortonworks.com/blog/industrial-iot-offshore-drilling-solution-delivered-less-90-days/
Real-time Drilling & Production
Why Hortonworks?
Data Discovery
What
à Stream critical telemetry of drilling, completions and production process into big data platform
à Drilling typically done in remote parts of the world, where connectivity is intermittent, latent and provide minimal bandwidth.
à Typical remote monitoring technologies do not perform well in these conditions, therefore large volumes of data end up
stranded and out of reach for analyst and support teams
Why
à Remote drilling operations operate reactively and suffer from unnecessary downtime, equipment failures, efficiency losses, and
safety risks.
à Provides Industrial Control System datasets in format comprehensible to traditional analytical techniques
à BSEE (the governing body for offshore drilling in the U.S.) proposed new regulations that require offshore drillers to monitor
safety critical equipment in real-time and archive the data at an offshore facility
How
à Hortonworks and Kepware delivered an Industry IIoT Solution in less than 90 days for acquiring and storing time series
measurements and related safety equipment data from an operated drill ship using Kepware IoT Gateway, HDF & HDP.
à Key data consumption patterns planned include KPI dashboards, condition-based monitoring and maintenance, event-based
surveillance, and traditional BI reporting; ensuring safer more efficient offshore operations.

9. 9 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Field Data Capture Office or Datacenter
Real-time Drilling & Production – Reference Architecture
WITSML
Files / Other Unstructured Data
Video
IoT Gateways
PLC / RTU
SCADA, DCS, Historians
Central HDP Cluster
Hive
Central HDF Cluster
NiFi
Kafka
Storm
Streaming
Options
HBase Solr
YARN
HDFS
Location 1
NiFi
Location n
NiFi
Data Center
Data Ingestion Framework
End users
DATA IN MOTION – HDF DATA AT REST – HDP
HDF Edge (MiNiFi + NiFi)
§ Reliable collection
§ Small footprint
§ Edge processing
§ Data provenance
§ Integrates with core
policies
HDF Core (NiFi with Streaming)
§ Processing at larger scale
§ Distributed stream processing
HDP
§ Security and data governance
§ Monitoring, management, operations
§ Applications
§ Analytics
Structured Data Sets

10. 10 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
What
à Model based failure prevention based on equipment telemetry and asset patterns
à Every form of artificial lift is prone to failure when subjected to different types of reservoir conditions
à Problems like scale, low static bottom hole pressure, overload and rod string failure are the result of machines encountering
gas, sand, H2S and CO2 corrosion and other subsurface conditions
Why
à Increased production through fewer unplanned well interventions
à Decreased unplanned downtime and cost for recovering failed equipment from downhole
How
à Collect streaming data using HDF, store all current and historical patterns of data usage including failure histories
à NOTE: this can be developed manually or through partner like OspreyData
Why Hortonworks?
Predictive Analytics
Production Optimization

11. 11 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Field Data Capture Office or Datacenter
Production Optimization – Reference Architecture
WITSML
Files / Other Unstructured Data
Video
IoT Gateways
PLC / RTU
SCADA, DCS, Historians
Central HDP Cluster
Hive
Central HDF Cluster
NiFi
Kafka
Storm
Streaming
Options
HBase Solr
YARN
HDFS
Location 1
NiFi
Location n
NiFi
Data Center
Data Ingestion Framework
End users
DATA IN MOTION – HDF DATA AT REST – HDP
HDF Edge (MiNiFi + NiFi)
§ Reliable collection
§ Small footprint
§ Edge processing
§ Data provenance
§ Integrates with core
policies
HDF Core (NiFi with Streaming)
§ Processing at larger scale
§ Distributed stream processing
HDP
§ Security and data governance
§ Monitoring, management, operations
§ Applications
§ Analytics
Structured Data Sets

12. 12 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Single View of an Asset
Why Hortonworks?
Single View / Data Discovery
What
à Data sources and applications used by asset team resided in silos with limited visibility across OT & IT systems.
à Operations team having to rely on IT to generate reports from enterprise systems that weren’t timely and required manual data
integration using spreadsheets
à Extract data from relational data stores that underpin line of business apps (Wellview, OFM etc)
Why
à Provide a single environment for exploring current and historical conditions, KPIs and well economics
à Using the solution the asset team has been able to identify potential well failures 4X-5X faster than before
How
à Using HDP and a common visualization application, the 360 View solution was built in three months combining OT data sources
like SCADA, maintenance logs, & unstructured data (text files, emails) with ERP data, geospatial, and external data from
midstream partners, and weather data.
à The solution is fairly self-service that can be modified by the operations team with limited involvement from IT.

13. 13 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Field Data Capture Office or Datacenter
Single View of an Asset – Reference Architecture
WITSML
Files / Other Unstructured Data
Video
IoT Gateways
PLC / RTU
SCADA, DCS, Historians
Central HDP Cluster
Hive
Central HDF Cluster
NiFi
Kafka
Storm
Streaming
Options
HBase Solr
YARN
HDFS
Location 1
NiFi
Location n
NiFi
Data Center
Data Ingestion Framework
End users
DATA IN MOTION – HDF DATA AT REST – HDP
HDF Edge (MiNiFi + NiFi)
§ Reliable collection
§ Small footprint
§ Edge processing
§ Data provenance
§ Integrates with core
policies
HDF Core (NiFi with Streaming)
§ Processing at larger scale
§ Distributed stream processing
HDP
§ Security and data governance
§ Monitoring, management, operations
§ Applications
§ Analytics
Structured Data Sets

14. 14 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
About Hortonworks
Customer Momentum
à ~1400 customers (as of October 2016)
à ~400 customers added in 2015
à Publicly traded on NASDAQ: HDP
The Leader in Connected Data Platforms
à Hortonworks Data Flow for data in motion
à Hortonworks Data Platform for data at rest
à Powering new modern data applications
Partner for Customer Success
à Leader in open-source community, focused
on innovation to meet enterprise needs
à Unrivaled support subscriptions
Founded in 2011
Original 24 Architects, Developers,
Operators of Hadoop from Yahoo!
1000+
E M P L O Y E E S
1500+
E C O S Y S T E M
PA R T N E R S