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Improving Data Collection Efficiency:
Strategies For Quickly Gathering & Prioritizing
Data Points To Gain The Correct Fidelity Of Data
To Do Calculations & Run Models On
Rapid Data Collection & Storage
Results Driven Analytics Techniques
& Optimized Data Management
Infrastructure – Oil & Gas
SEPTEMBER24-25,2019| HOUSTON,TEXAS
#PIWorld ©2019 OSIsoft, LLC
AGENDA Introduction
Layers of Analytics and Efficiency
Data Collection Efficiency;Data and Integration of Modeling Software – Phillips 66
Effective Transfer of well site data in real-timeOperations & Advanced Analytics at the Well Site – Shell
Allocate the right data, to the right teams, at the right time for improved decision making
Advanced Analytics & ML in the Cloud – TransCanada/AWS
Layers of Analytics - Process Operations
#PIWorld ©2019 OSIsoft, LLC
Data Collection, Gathering and Processing Efficiency
Build Templates w/Initial Analysis
Expressions w/SMEs
Map Tags & Metadata
- Auto tag creation
- SQL sources
- Table Lookup
Visualize & Evaluate Anomalies
Exception Basis
Tune Anomaly Expressions &
BackfillTrack KPIs & Value
Use Cases
Create PI AF “Digital Twins”:
3 PI Vision Templates
Best Practices in
Integration of Modeling
Software with PI AF
©2019 OSIsoft, LLC
Data Flow
6
High Fidelity Historical Process Data
PI AF Used to perform Plan vs Actual (PvA) comparisons
Historized process data and model
results
RDBMS
Simulation model data
PI Vision used to provide self serve access to contextualized
operational intelligence.
7
Project Approach
Strong SME InvolvementThe Key to PI AF success!Represent sites and make key business decisions:
Hierarchy, nomenclature, UOM, analytics, displaysDefine unit-to-unit differences
Validate solutionTrain end-users
Align on an upfront design – forward looking vs specific project
Use robust processes for communication, testing, documentation
PI AF Expert/Partner collaboration – RoviSys and OSIsoft
PI AF Template-based Solution
• Leveraging the power of PI AF Templates of many flavors:Elements, Analyses, Event Frames
• Many commonalities across unit types
• Unit-to-unit variations captured
• Not just physical assets• Product Streams, Yields, etc.
• Dynamic and centrally managed design
• Standardized design library for deployment
• Adaptable design, can evolve with business needs
• Iterative approach to continuously improve the solution
8
9
• Hierarchy captures physical asset relationship
• Process, calculated, and modeled data side-by-side
• Each PI Tag mapped once at major unit level
• Hierarchy enables use of substitution parameters
• Only 10% process data tags with non-standard naming
• PI AF Table lookups and substitution parameters reduced 90% of manual attribute data source mapping
• Scalable and dynamic for long-term sustainability of solution
• Forward-looking Data Infrastructure• Supports current initiative
• Lays groundwork for future solutions
PI AF Hierarchy Design
PI AF Hierarchy Design
10
• Hierarchy captures physical asset relationship
• Process, calculated, and modeled data side-by-side
• Each PI Tag mapped once at major unit level
• Hierarchy enables use of substitution parameters
• Only 10% process data tags with non-standard naming
• PI AF Table lookups and substitution parameters reduced 90% of manual attribute data source mapping
• Scalable and dynamic for long-term sustainability of solution
• Forward-looking Data Infrastructure• Supports current initiative
• Lays groundwork for future solutions
11
• Hierarchy captures physical asset relationship
• Process, calculated, and modeled data side-by-side
• Each PI Tag mapped once at major unit level
• Hierarchy enables use of substitution parameters
• Only 10% process data tags with non-standard naming
• PI AF Table lookups and substitution parameters reduced 90% of manual attribute data source mapping
• Scalable and dynamic for long-term sustainability of solution
• Forward-looking Data Infrastructure• Supports current initiative
• Lays groundwork for future solutions
PI AF Hierarchy Design
Scalable PI Vision Displays
• “Reports” PI AF Hierarchy branch created to reference critical values for displays
• Consistent for every instance across the enterprise
• All display values are tied to AF Element Template attributes
• PI Vision automatically enables Asset Relative Displays
• Create each screen once per unit type Element Template and it applies to all instances in the AF Hierarchy
• Standardized view of real-time data and KPIs
• No need to manage each person’s “version of the truth”
12
RESULTSCHALLENGE SOLUTION
Integrating PI System data with model data and comparing to actuals
Integrate modeling data with the PI System to provide high fidelity, quality, rich dataset for trending, analysis, monitoring, optimization
Improved KPI monitoring, optimization, and model usage resulting in improved economic performance
• PI SDK to load high fidelity data in model• PI RDBMS: interface to bring in modeling data back
into the PI System • PI AF: templatize and standardize process data,
calculations, and analytics• PI Vision: standard KPI, economic, summary displays
• Different tools/spreadsheets with different data available
• Quality and consistency of monitoring varies• Level of effort to maintain
1
• Improved performance
• Data transparency
• Empowerment of SMEs with self serve access to model effectiveness
Best Practices in Integration of Modeling
Software with PI AF
Shell - A business perspectiveof Real-Time Operations and
Advanced Analytics
PI System Center of Excellence
@osisoft #OSIsoftUC © Copyright 2017 OSIsoft, LLC
PI Systems(Super Collective)
ConsumersLegacy
Application
Advanced Analytics
SmartPerform
Engineering Hub
Smart Apps
Smart Foundation
Real-Time Architecture within Shell
Enterprise
Foundation
Platforms
Enterprise
Structure
Visual
Components
Public
ServicesCalculationsEvents Scheduling
Standard
Asset
Structure
SMM
MatLab
Quest
Alteryx
Orchestration
EDWhAlarm
Mgmt
MatLab
T-CAT
PI AFPI AF PI AF
PI AF
SmartConnect
EngineeringHub
PTM
NGT
@osisoft #OSIsoftUC © Copyright 2017 OSIsoft, LLC
Leveraging the PI System at the heart of our Digitalization Roadmap
More integration between our core Digital Oilfield tools (PETEX, EC, etc) and the PI System
Leverage the real-time analytics and automation capabilities from within the PI System
Explore Opportunities for Machine Learning,AI & Advanced Analytics sitting on top of the PI System
Safe and Optimised
production
Improved Productivity Improved Availabilityand
Reliability
Integration with Digital Oilfield Tools• PI System integration with Digital Oilfield
(DoF) tools helped our Production Engineers increase production in 1st year of deployment
• Change Management and focus on improving ways of working is key to make this work!
Case Study: Impact of compressor suction pressures on well performance
GAP model predicted a loss of 500boe/d due to 10 psig increase inseparator pressure
Compressor-turbine system performance was evaluated using process simulation model
Review of Engine wash frequency
Frequent anti-foulant injection incompressor
More integration between our core Digital Oilfield tools (PETEX, EC, etc)and the PI System
Leverage the real-time analytics and automation capabilities from within the PI System
Explore Opportunities for Machine Learning, AI & Advanced Analytics sitting on top of the PI System
Real-time Analytics andAutomation Use PI Data Archive and PI AF to start replacing some of the manual processes with automated tools and workflows,
giving engineers and operations teams the data they need in the right way at the right time => need to get data faster out of the PI System
Automation increases productivity and helps Engineers spend more time on translating data into meaningfulinformation and valuable decisions
Significant Productivitygain
More integration between our core Digital Oilfield tools (PETEX, EC, etc)and the PI System
Leverage the real-time analytics and automation capabilities from within the PI System
Explore Opportunities for Machine Learning, AI & Advanced Analytics sitting on top of the PI System
Advanced Analytics, Machine Learning &AI
• Real-time analytics for equipment and operations is providingsignificant bottom line value
• Multiple predictive analytics underway to predict compressors and valvesfailure
• Reduce cost and increase uptime – Compressors trips / failure is one of the top Shell Operating Ventures Bad actors
Valves example:
• Valves maintenance mostly time-based:
• Too late => unscheduled deferment, HSSE risk
• Too early => scheduled deferment and cost
• Moving to condition-based maintenancewill help reduce OPEX and deferment
• There are thousands of valves in Shell,this is where Machine Learning comes in…. More integration
between our core Digital Oilfield tools (PETEX, EC, etc)and the PI System
Leverage the real-time analytics and automation capabilities from within the PI System
Explore Opportunities for Machine Learning, AI & Advanced Analytics sitting on top of the PI System
Asset A
2015 control valve incident
led to $ 6 MM value loss.
There are over 20.000
valves installed, how can
this be prevented in the
future?
USERS CONFERENCE 2017 #OSIsoftUCosisoft@
Analytics framework
© Copyright 2017 OSIsoft, LLC#OSIsoftUCosisoft@
Building Analytics capabilities in Shell
USERS CONFERENCE 2017 @osisoft #OSIsoftUC © Copyright 2017 OSIsoft, LLC
Makingthe most of existing data
Predictive Asset Maintenance
Shell Global Solutions International B.V.
USERS CONFERENCE 2017 13@osisoft #OSIsoftUC © Copyright 2017 OSIsoft, LLC
Carbon Capture & Storage
USERS CONFERENCE 2017 12@osisoft #OSIsoftUC © Copyright 2017 OSIsoft, LLC
TransCanada's Journey
to Advanced Analytics
©2019 OSIsoft, LLC
Building a Foundation for Data Analytics
• Starting with the Basics
• Data Culture
• OTAnalytics
• Self Serve, Human Analytics
• Understanding Data as an Asset
• The world’s most valuable resource
• Create “pipelines” to collect, store and utilize that resource
• Take advantage of AF, Vision to create value
• Building Cross-functional Teams
• Subject Matter Experts
• Engineers and Data Scientists
#PIWorld ©2019 OSIsoft, LLC
Leveraging our Analytics Foundation
Reliability AnalysisPlatform Measurement Insights &Analytics
#PIWorld ©2019 OSIsoft, LLC
RESULTSCHALLENGE SOLUTION
TransCanada
Manage and take action on anomalies identified by AF analyses and document findings
Redesign AF using modular approach and develop a custom platform to augment PI Asset Framework
• Modular AF redesign
• Developed web platform to manageanomalies and findings
• Ability to train and retrain statistical models
• Over 100% increase in findings from
AF redesign
• 2018: over 250 corrective actions
taken
• Significantly reduced time to
implement assets• Prioritization of anomalies
• Anomaly Management
• Take advantage of statistical models
• Document Findings
• Improve asset implementation time in AF
#PIWorld ©2019 OSIsoft, LLC
RELIABILITY ANALYSIS PLATFORM
RESULTSCHALLENGE SOLUTION
TransCanada
Get more value out of our PI System by expanding beyond Compression assets and into Gas Measurement
Create a new AF structure and asset templates for full measurement system.
Improved measurement health andproblem discovery time significantlyreduced.
• Building existing knowledge into analyses
• Custom event frame and finding management
• Adding new measurement assetsinto existing Vision platform
• Able to more readily pinpoint when
problems begin
• Measurement data in PI more easily
consumable by business users
• Centralized equipment diagnostic data
interpretation
• Improve measurementaccuracy
• Provide insights into measurement equipment health
• Take advantage of PI Vision
MEASUREMENT INSIGHTS &ANALYTICS
#PIWorld ©2019 OSIsoft, LLC
Evolving to Advanced Analytics withAWS
Gas Day Forecasting
• Challenge
• Objectives
• Navigating the Sea of Data
• Feeding the Machine
• PI Integrator for Business Analytics
• Automating the Demand Forecast
• Consuming the Results
• What else?
#PIWorld ©2019 OSIsoft, LLC
Evolving to Advanced Analytics withAWS
#PIWorld ©2019 OSIsoft, LLC
Challenge
• Commercial operating decisions are currently made based on daily demand forecast.
• More accurate forecasting provides for optimal use of our assetsand more flexibility for our customers.
• Current method of forecasting does not take full advantage ofhistorical measurement, weather and load demand data.
• Scalable model to support full system load
Evolving to Advanced Analytics withAWS
Objectives
• Fully utilize our data to produce more accurate forecasts by modeling systemperformance against historic conditions.
• Utilize AWS to minimize up-front investment and on-going costs.
• Leverage key technology partnerships to prove out the concept in rapid fire fashion. Fail Fast, Succeed Faster.
#PIWorld ©2019 OSIsoft, LLC
Evolving to Advanced Analytics withAWS
Third
Party
Data
Metered
Flow Data
Commercial
Data
Weather
Data
PI Asset
Framework
Navigating the Sea of Data
#PIWorld ©2019 OSIsoft, LLC
Evolving to Advanced Analytics withAWS
S3 Machine
LearningKinesis SageMaker
Feeding the Machine
PI Integrator for
Business
Analytics
#PIWorld ©2019 OSIsoft, LLC
Evolving to Advanced Analytics withAWS
Automating the Demand Forecast
SageMaker Amazon API
GatewayLambda
Custom Data
Reference
#PIWorld ©2019 OSIsoft, LLC
Evolving to Advanced Analytics withAWS
PI Asset
Framework
Custom Data
Reference
Consuming the Results
PI Vision
#PIWorld ©2019 OSIsoft, LLC
Evolving to Advanced Analytics withAWS
What else?
Lost and Unaccounted ForGas Gas Measurement VolumeEstimation
#PIWorld ©2019 OSIsoft, LLC
Perspectives, Best Practices, & Lessons Learned
• Layers of Analytics Approach• Use tools already available• Enable self-serve analytics & visualization• Asset Framework, Vision
• Data Quality• Poor quality data is a damaged asset
• Bad results reduce confidence
• Feature Engineering• Can be done in AF andhistorized• Increase the value of your asset
• The Value of Experimentation• Data Science is experimental
• Be Agile
#PIWorld ©2019 OSIsoft, LLC
#PIWorld ©2019 OSIsoft, LLC
Best Practice Data, Infrastructure and Modeling Summary
Build Templates w/Initial Analysis
Expressions w/SMEs
Map Tags & Metadata
- Auto tag creation
- SQL sources
- Table Lookup
Visualize & Evaluate
Anomalies
Exception Basis
Tune Anomaly Expressions &
BackfillTrack KPIs &
Value Use Cases
Create PI AF “Digital Twins”:
3 PI Vision Templates
Modeling
Data
Infrastructure
Best Practice Process Summary
#PIWorld ©2019 OSIsoft, LLC
• Build an Analytics Foundation
• Start simple
• Data as an Asset
• Cross-functional teams
• Leverage the Foundation
• Build platforms with tools on hand
• Enable users to create analytics and visualize data
• Evolve with rapid prototyping
• Agile, Proof of Concept projects
• Fail fast, succeed faster