1. Enabling Integration of Core Work Processes in Upstream Oil and Gas
Kaare Finbak & Pål Rylandsholm
Det Norske Veritas,
Ray Verhoeff, OSIsoft

2. OLF = Norwegian Oil Industry Association
Topics Covered
Integrated Information Platform (IIP) project
Background
The new operation concept Integrated Operations (IO)
OLF’s strategy for Quality Information
Purpose and deliverables
Objectives
Deliverables
Take-up process
OLF’s Daily Production Reporting project
OSIsoft RtPM for Production Data Exchange in Upstream Oil & Gas IO
New concept
Large potential
IIP
Research project
Integrated Information Platform for reservoir and production systems
OLF = Norwegian Oil Industry Association
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3. DNV - Det Norske Veritas
Independent foundation
Objective: To “Safeguard life, property, and the environment”
Established in 1864 in Norway
Top 3 certification body world-wide
Top 4 ship classification society world-wide
Global representation
6095 employees
DNV has per a total of 6,095 employees, including long-term subcontractors and employees in wholly-owned companies, in close to 300 offices in about 100 countries.
Independent 3d party – certification and classification
DNV’s four business areas
Maritime
Certification
Technology Services
Consulting
In addition, there is DNV Software, an independent business unit.
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4. DNV – Information Quality Management
Business Information Services
Requirements
Governance
Architecture
Information Quality Assessment and Rating
Information Training and Education
Standards
Information Models & Data Standards
Test Center
Compliance to Standards (Software)
Validation according to Standards (Data)
Independent Data and Information Hosting
IQM: New business area in DNV.
Markets: Oil & Gas, Defense and Public Sector
Business Information Services
Information Requirements – Identifying Core Data
Information Governance
Information Architecture
Information Quality Assessment and Rating
Information Maturity Assessment
Information Quality Plan
Information Training and Education
Standards Training for Management and Experts
Information Models & Data Standards
Integration of Industrial Data (ISO 15926)
Product Life Cycle Support (ISO )
Structured Data (S1000D)
Other Information Models and Standards
Test Center
Software Compliance According to Standards
Validation of Populated Data Sets According to Standards
Independent Data and Information Hosting
Data Hosting and Management of Information Resources
Managing risk by managing information
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5. According to OLF, IO increases revenue and reduces costs
Trondheim
Expert
center
Expert
center
Bergen
Vendor’s onshore operation centre
Stavanger
Aberdeen
Control room
Fiber cable
Real time data
Expert center
Operator’s onshore
operation centre
Source: OLF, 2005
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6. OLF predicts that IO will be implemented in two main steps
Automatic optimization
IO Generation 2
Integrated operation centers of operators and vendors
Heavily instrumented facilities
Heavy automation and multi-domain optimization of processes
Vendor
Operator
Intelligent facilities
Real-time
pipeline
Vendor
Real-time
collaboration rooms
Reservoir & production management
IO Generation 1
Integrated onshore and offshore centers
Intra-domain optimization of work processes
Drilling & completion
Traditional
facilities
Operation & maintenance
Source: OLF, 2005
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7. OLF intends to establish an information pipeline that supports both IO generations
Automatic
optimization
Vendor
Web portals
Processes
Web services
Field data
Health, safety, environment
Drilling & completion
Reservoir & production management
Operation & maintenance
Operator
Schemas for automatic
exchange of data
Vendor
Terminology
Taxonomy
Ontology
Semantic
oil & gas web
Source: OLF, 2005
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8. Terminology, taxonomy and ontology?
Reservoir & production optimization
Services
Well monitoring
Reservoir monitoring
Production monitoring
XML
HSE
Drilling
Completion
Reservoir
Production
Operation
Maintenance
Terminologies
Taxonomies
Terminology: A set of terms representing the system of concepts of a particular subject field.
Taxonomy: A hierarchical classification of things. Almost anything, animate objects, inanimate objects, places, and events, may be classified according to some taxonomic scheme. Ontology: Is typically a hierarchical data structure containing all the relevant entities and their relationships and rules within that domain.
Ontologies
Project
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9. Automatic optimization Intelligent facilities
The IIP project delivers required terminologies, taxonomies and ontologies
Automatic optimization
Generation 2
Complete ontologies supporting automated reasoning or inference of data using logical rules
Taxonomies for multiple domains
Intelligent facilities
Oil & gas
ontology
Real-time
collaboration rooms
Generation 1
Terminologies for single domains
The basis for XML schemas for automatic transferal of data between applications in same domain
Traditional
facilities
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10. The project targets key business domains
Develops terminologies based on solid business knowledge
Input from project participants
Other projects specifications
Domain specific standards
Prepares approval of the terminologies by international standardization bodies
ISO and W3C
POSC Caesar and POSC
Addresses short term …
Terminologies and XML schemas for real-time exchange of data
… as well as long term business needs
Taxonomy and ontology supporting optimization of processes across domains
Production
Drilling
Geometry and topology
Reservoir characterization
Condition monitoring
Equipment
Safety and Automation System
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11. Deliverables will be available on the Internet
Publicly available from during Q2 2006
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12. Visualization http://ht.vestforsk.no/demo/production/index.html Terms
Definition
Demo. Way of browsing simple hierarchical structures – hyperbolic tree
Click and “pull” to browse structure
Search
Definitions
Demo available on:
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13. The project is supported by many key players
Oil companies: Hydro and Statoil
Vendors/engineering: FMC, National Oilwell Varco, Poseidon
Consulting/IT: Capgemini, Oilcamp, Amitec
Specialists/Research: Force, DNV, NTNU
Assosiations/Organisations: OLF, POSC, POSC Caesar
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14. Project schedule and budget
Total current budget:
24 MNOK (3 MEUR)
Project Duration: –
The project is partly funded by The Norwegian Research Council program PETROMAX and by the project participants.
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15. OLF’s Daily Production Reporting project
One of several fast-track take-up projects initiated by OLF

16. Daily Production Report - Project details
Scope: Develop ontology and common XML schemas for daily production report
Participants: All major operating companies on the Norwegian Continental Shelf
IIP contribution: Terminology and standard XML
Pilots: Åsgard and Valhall
Implementation: Started January 1, 2006
Situation before: Daily production reports on different formats
Scope: Develop a common XML-based standard for reporting of daily activity and production data
Participants: Statoil, ENI, ESSO, Shell, BP, Petoro, DNV, ConocoPhilips, Hydro
Pilot planned delivered in August this year and implementation in LW during autumn 2005.
Benefits: Standardised and efficient partner reporting and follow-up
Source: OLF, 2005
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17. Daily Production Report - System overview
ISO
15926
Operator
LicenseWeb
Authorities, operator & partners
Internal prod. data system
License Web
Excel reports
Std. reports
Non-std. reports
XML
file
Prod.
report
XML
file
Valhall
Åsgard
Benefits: Efficient exchange of production data and daily production reporting
Source: OLF, 2005
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18. A Daily Production Report
XML based on standard XSD
Standard report
Source: OLF, 2005
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19. OSIsoft RtPM And The IIP Project
Provides terminologies, taxonomies and ontologies to be used for real-time optimization of reservoir and production for heavily instrumented oil and gas fields
Provides framework for collecting, structuring, storing and analyzing real-time field data from heavily instrumented oil and gas fields
May enable
Reliable real-time information pipeline supporting G1 and G2 integrated operations
Copyright © 2006 OSIsoft, Inc. Company Confidential. All rights reserved.

20. OSIsoft RtPM in Upstream
About the upstream business…
Problems & Solutions
Exchanging data
The ProdML Initiative
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21. Priorities in Upstream
Cambridge Energy Research Associates (CERA) polled leading E&P firms in 2006:
“Total Asset Awareness”
better sensor technology
better in-field communication systems
advanced data mgmt solutions
Visualization & Analytics
automated model updating
improved visualization
system-wide optimization (both surface and subsurface)
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22. OSIsoft in Production & Refining
37% of the world’s refined products are monitored by PI
Installed in 26% of the world’s refineries
15% -20% of the world’s oil fields are monitored by PI
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23. OSIsoft RtPM in Upstream
Green field, brown field, offshore
Production is a complex business…
Few free flowing wells
Most done by injection of steam or gas
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24. Controller or Casing Choke
Injection
Production
Controller or Casing Choke
Wing & Master Valve
Flowline Choke 10 11 20 12 25 26 27 21 22 13 3
Separator 14 15 4 16 5
Compressor 1
From Well
Compressor 2 23
To Well
Production Header 24
Gas Header
Compressor 3
From Well
Gas Lift Valve
Talk about distribution of pressure in well, compressor, separator, etc.
Frequent testing to determine flow characteristics and response to pressure
To Well
Tubing
Valve
Choke
Measurement #
Casing
Packer 1
Perforations
Gas Lift Well 1 2
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25. Upstream Data Management Problems
Frequently changing flow network configurations
Hard-to-measure data
“3 phase” flow meters rare
Data reconciliation and estimation needed
Back-allocation
Optimization
Reporting must be accurate
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26. Interaction of Applications
“Chaining” of applications needed in the field
Measured data feeds estimated algorithms
Estimated feeds enter back-allocation algorithm
Allocated data fed to modeling software
Modeling software drives optimization …
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27. Solutions abound Many vendors offer analytical solutions
Data exists, but from a variety of sources
This suggests a data exchange standard!
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28. Full Production Facility
This shows that a real facility is much more complex than a single well. Flows between process units are many and can be shut in to redirect flows or to shut down a well for testing. Knowledge of the flow network is important to the applications generating simulated results.
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29. Rendering in XML <unit> <name>A</name> <flow>
<name>…</name>
<kind> … </kind>
<port>
<direction>inlet</direction>
<temp> … </temp>
<pres> … </pres>
<product>
<period>
<dTimStart> etc.
<volume></volume>
</period>
</product>
</port>
</flow>
</unit>
This fragment does not represent actual ProdML XML. The point here is that XML is always populated by repeating groups of elements. Each element has repeating subgroups to hold component data as so forth. This is a hierarchy. My point is that in order to emit XML like this, it helps if you organize your data in an infrastructure that supports both network and hierarchical organization.
Now, where have you heard this before? Yes! The Foundation project.
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30. “Foundation” Foundation is… A flexible enterprise asset model
Relationships between the assets:
Hierarchical
Flow network
Not just one relationship
Access to:
PI data
Relational and web service data
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31. ProdML
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32. ProdML Members Oil Companies Software Companies Standards Organization
BP, Chevron, ExxonMobil, Shell, Statoil
Software Companies
Halliburton, Invensys, OSIsoft, Petroleum Experts, Schlumberger, Sense Intellifield, TietoEnator, Weatherford
Standards Organization
Petroleum Open Standards Consortium (POSC)
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33. Sources
Wellhead Information Transfer Standard Markup Language (WITSML)
W3C
ISO 15926
OPC UA
WITSML: ProdML is an evolution of concepts defined by WITSML. One of the features being added is the notion of data at a point in a process coming from more than one source: measured, simulated, allocated, etc.
W3C: strong interest in the consortium to implement web services strictly to industry standards.
ISO 15926: does a superior job of defining the characteristics of physical production equipment. Originally designed to exchange equipment specifications between companies building production facilities and companies operating them. ProdML is not projected to require this level of detail at this time. It is more focused on the material flows between production units.
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34. ProdML Use Cases: The Flows
Optimal allocation of lift gas, current time only
Flow #2
Evaluate model, compare with actual performance, notify if different, current time only
Flow #3
Similar to Flow #2, but use historical data
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35. ProdML Flow #2
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36. OSIsoft Implementation of ProdML
Data Out
Data In
Model Out
Model In
ProdML Data
Web Services
Foundation Asset Database
Foundation SDK
ProdML Network Model
Web Services
Foundation SDK
PI Data Reference
PI Archive
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37. Summary Data flows in upstream production management are complex
Many vendors contribute to solution
Standards-based data exchange makes collaboration possible
OSIsoft RtPM is the infrastructure for ProdML support
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38. .. the end
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