data as a critical asset for integrity managementdata management and integration 1160 –managing...
TRANSCRIPT
Data as a Critical Asset for Integrity Management
Esri Petroleum GIS Conference 2019 – May 15-16
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• Pipeline Infrastructure Dynamics & the Role of Data
• The Triad of Systems (WMS, GIS, DMS)
• Data as a Critical Asset
• Recommended Roadmap for Data Management
• Conclusions
Table of Contents
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Pipeline Infrastructure Dynamics
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Growing global O&G demand
NA Gas: Increased volumes:
1.5X by 2035, 2X BCF by 2050
Slower construction growth
Maintenance of existing assets
and life extension is critical
O&M optimization & data
driven prioritization required
Existing Infrastructure New Pipelines
2015 -2035
Miles of Transmission 300,000 ~ 15,000
Miles of Gathering Lines 400,000 ~150,000Gas Processing (BCF / Day) 83 ~40
Storage 9,000 ~250
Quadrennial Energy Review; Energy Transmission, Storage, and Distribution
Infrastructure, April 2015, White House Task Force
North American Midstream Infrastructure Through 2035: Leaning Into Headwinds,
Prepared by ICF International for the INGAA Foundation, April 12, 2016
Energy Demand
Bill
ion
to
e
2018 BP Energy Outlook
Nat GasGlobal
US Energy Investment Growth
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API TR 1178: guidelines to empower informed
decisions
Goal: highest degree of data quality possible
• Efficient use of resources
• Easy access/ security
• Communication across systems (enable analytics)
PHMSA: “ The ability to integrate and analyze (…)
data from many sources is essential for sustaining
performance and a proactive IM program.”
Completes framework set by API RP’s 1160, 1163,
1173 and 1176
Data Management and Integration
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1160 – Managing System Integrity for Liquid Lines / 1163 – In-Line Inspection Systems Qualification / 1173 – Pipeline Safety
Management Systems / 1176 – Recommended Practice for Assessment and Management of Cracking in Pipelines
Data Silo
Data Silo
Data Silo
Data Silo
Asset Integrity Management
Asset Performance Management
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Accuracy: represents reality
Completeness: all needed data is available
Consistency: free of internal conflicts
Precision: exact as needed
Granularity: right level of detail
Timeliness: current and retained until needed
Integrity: structurally sound (topology)
➢Asset integrity: “is the ability to perform its
required function effectively and efficiently
over its entire life cycle”
Data Quality & Integrity: What is it?
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Data“Records”
Data“Digital Asset”
Asset
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Currently, the 3 main systems operate as silos:
• Work Management (Maximo)
• GIS (Esri)
Data Management (in-house, SCADA)
Data grows significantly with more frequency
and resolution… “big data” era
Digital integration now more affordable
Systems providers enable integration capabilities
“One version of the truth” becomes a critical skill
for any enterprise management system
The Triad of Systems
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Assets Number of
records
System Estimated Data
size for ~ 10K miles
Compressor stations 100 Historian / SCADA 20 MB
Measurement stations 4,000 Historian / SCADA 1 TB
Regulatory stations 1,200 Historian / SCADA 300
Valves 16,000 GIS 6 TB
Pipe segments 90,000 GIS 45 TB
Main valve segments 12,500 GIS 6 TB
Dynamic segments 69,000 Risk SoftwareAggregated with
other assets
Inspections (ILI) 3,500 GIS 1 TB
Anomalies from ILI 2,000,000 GIS 1.5 TB
Closed interval survey
inspection1,000 GIS
Aggregated with
other assets
Closed interval survey readings 4,500,000 GISAggregated with
other assets
Work orders 1,000 WMS 350 MB
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The Triad of Systems
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Desktop, Mobility, Dashboards
Application Integration / interoperability framework
Application Modules
Data Management
Inte
gra
tio
n F
ram
ew
ork
CustomerApplications
DataFiles
PODSMetaOperational
Data
FileSystemManagement
Compute&Storage
DocumentData
DataAccessFramework
Enterprise
Systems
SCADAHISTORIAN
CapitalProjects
Financials
AssetRegistry
WorkOrders
GIS
Records
Governance and
Procedures
Maps,
Geotagging
Centerline
Records
Integrity
Mgmt..
Planning,
Compliance
Work
Mgmt.,
Financials
3rd Party (Corrosion, CIS,
CP, ILI)
3rd Party (Risk
assessment)
In-House(Engineering,
Safety and Reliability)
Best Case Today Goal
DMS
WMS
GIS
Fu
ll In
teg
ratio
n
Business Processes
Analytics, Applications
Decisions, KPIs
Outcomes
Data Alignment
Attribute Coincidence
Situational Context
Enabled Analytics
Digital Twin(predictive, optimized)
Lev
el o
f M
atu
rity
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Data Management needs to be a strategic
decision (same as asset management)
Prioritization of data efforts must be driven
from “Use Cases” not “Data Sources”
Data confidence must be a factor in
decision-support outputs
Governance & roles are critical to success
Benefits of treating data as an asset:
• Auditability / Traceability
• Easier data corrections, less human error
• Improved resource utilization
• Security / Scalability
Managing Data as a Critical Asset
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Use Case – Data Driven Approach
Use case 1(e.g. Risk
Assessment)
Data Data Technology Analytics
• Available Data Sets
• New Data Sets
• Manual Integration
• Digital Integration
• Digitization
• Data Validation /
Feedback
• Analytic Models
• Machine Learning
• Process Automation
Default Approach
Use case 1(e.g. Risk
Assessment)
Data
Technology
• Assumptions
• Standards
• Defaults
• Models
• Reports
• Decision Execution
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Roadmap for Effective Data Management
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?
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Roadmap for Effective Data Management
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Maturity
Assessment
• Current state
• Gap assessment
• Goal setting
Data Governance (Owners, policies, systems, MOC)
Data
Management &
Integration
• Centerline
alignment
• Integration of SME
knowledge
• Confidence /
quality
• Data models &
standards (PODS,
APDM, UPDM)
Systems &
Platforms
Integration
• Use-case based
integration of
systems
• WMS + GIS
• Enhance data
models
Business
Process
Optimization
• Define business
outcomes & goals
• Process
optimization /
automation
• Data analytics
• Machine learning
As-Built
Contextual data (Geo, operations, value chain)
In-Service
Context
Operational (ILI, field)TVC updates
Construction & manufacturing
Da
ta
Data Attributes
Data
Validation
• TVC
• Migration
• Conditioning
Process
Validation
• Process outcome
• Inputs,
Stakeholders, data
requirements,
frequency
• Policies and
procedures
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Roadmap for Effective Data Management
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Use case example: Alaska Pipeline Operator, Compliance Management
• Process & Data
• Manual process, ad hoc
updates
• Multi-tab XLS repository
• Data Management
& Integration• From XLS to Maximo
App
• System Integration • Field mobility app integrated to
Maximo.
• Esri Insights Dashboard and KPI’s
• Process Optimization • Guaranteed, up-to-date,
measurable compliance
• Outcome
• Minimize non compliance
segments
• Optimize field / office work
• Effective support for Reg audits
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Pipeline infrastructure demand growth continues
Safe asset lifecycle extension critical
Data needs to be treated as an asset: data integrity
Data & Business process integration supports safer and
more efficient operations:
• Airline industry shows incident reduction after data
and proactive management efforts
• Pipelines have increased technology and data
volumes... safety records still not trending better
Data management is a journey, requires governance,
roles, goals and continuous improvement mindset
Conclusion
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PHMSA Incidents 1997-2016
Fatal Airliner Accidents per Year 1946-2017
RCA / QMS‘70’s
Data & Biz Process
Integration‘80’s
“Proactive” management
‘90’s
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Q&A
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Contact Information
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Tracy Thorleifson
G2 Integrated Solutions
Mauricio Palomino
G2 Integrated Solutions