How to start and scale your digitalisation capabilities. Business cases, technology and methods with a industrial focus from the E&P Business.

1. Digitalisering

2. 2
Bouvet
Trondheim
Bergen
Haugesund
Stavanger
Kristiansand
Arendal
Skien
Sandefjord
OsloSandvika
Malmø
Ørebro Stockholm
88
ansatte
Bouvet Nord
430
ansatte
Bouvet Øst
33
ansatte
Sesam
89
ansatte
Bouvet Sverige
55
ansatte
Bouvet Sør
321
ansatte
Bouvet Rogaland
65
ansatte
Bouvet Bergen
20
ansatte
Konsernledelse
og ansatte

3. Digitalization – Industri 4.0

4. Human-machine
Interface, (AR,VR, MR)
Mobildevices
and wearables
Smart sensors
and IoT
Data Science, Machine
Learning, Autonomous
agents & BOTS
Industry 4.0
3D Printing & Laired
Manufactoring
Partner & Customer
interactions – Service
orientation and integration
Big Data & Cloud
Computing
”Digital Twin” for
physical systems
Key drivers

5. ERP
Todays challenge
Design Machines
Maintenance
FinanceCompliance
Logistics
SCADAPDMS
QMS Project Mngt.
Scheduling
- Disconnected systems, processes and information

6. Jobb proaktivt med sikkerhet gjennom å kunne predikere
hendelser basert på data fra ulike kilder.
Reduser ulykker4.0
Effektiviser prosesser i styringssystemet ved å utnytte IT
verktøyene man faktisk arbeider i for å sikre etterlevelse på best
mulig måte.
Forenkle styring og etterlevelse
4.0
Maksimer effektiv arbeidstid for offshore arbeidere ved å gi
dem tilgang til arbeidsordre, videotelefoni, sensorer, prosedyrer
og tegninger fra arbeidsstedet.
Gi folk offshore en ex-sertifisert pad
4.0 4.0
Robotisering av administrative
DIGITALISERING
Kom i gang
Jobb proaktivt med sikkerhet gjennom å kunne predikere
hendelser basert på data fra ulike kilder.
Reduser ulykker4.0
Effektiviser prosesser i styringssystemet ved å utnytte IT
verktøyene man faktisk arbeider i for å sikre etterlevelse på best
mulig måte.
Forenkle styring og etterlevelse
4.0
Maksimer effektiv arbeidstid for offshore arbeidere ved å gi
dem tilgang til arbeidsordre, videotelefoni, sensorer, prosedyrer
og tegninger fra arbeidsstedet.
Gi folk offshore en ex-sertifisert pad
4.0 4.0
Sett opp en rimelig software-robot til å utføre rutine-preget
oppgaver på tvers av applikasjoner.
Robotisering av administrative
rutineoppgaver
4.0
Sikre avtaler, APIer og datautvekslingsformater som gjør det mulig
å etablere en felles applikasjonsuavhengig datakatalog for selskapet
kjerneinformasjon som kan deles.
Frigjør nøkkelinformasjon
Finn sammenhenger mellom prosesstekniske forhold og
degradering av rør, pumper, varmevekslere, tanker for
å optimalisere vedlikehold.
Utvid preventivt vedlikehold
Bruk dedikerte IT Business Analyster for å samarbeide tett med roller
som; prosesseier, systemeier, superbrukere og fageksperter for å sikre
at IT systemene konfig
u
r eres for å støtte forretningen optimalt.
Forbedre bruk av eksisterende
applikasjoner
English version; https://www.linkedin.com/pulse/low-hanging-digitalization-fruits-oil-gas-business-danielsen/

7. Analytic Evolution
Descriptive
What happened?
Helps understand how
things are going
Diagnostic
Why did it happened?
Helps understand
unique drives
Predictive
What could happen?
Forecast future
events and results
Prescriptive
How to make it happen?
Analysis that suggest a
prescribed action
Cognitive
Artificial Intelligence
System makes action
based on own decision

8. Technical data platform blueprint
Discipline Expert System data
Data Hub /Set
Exploratory Analysis
Data Science
Apps /Applications Cognitive Service
r
ERP and mainframe system data
Industrial IOT Streaming Data
r
r
r

9. Create an open 3rd party ecosystem
Snorre
Troll
Oseberg

10. Data Lake
Functions
Analysis Services
Data
Warehouse
r
SQL
Data Factory
Data Science
Azure ML
Power BI
Data hub Analytics
Source data
Azure platform industrial example
Discipline Expert System data
IoT HubIndustrial IOT Streaming Data
Stream Analytics
r
ERP and mainframe system data
Data Lake
Analytics
Data Catalogue
Navtive code (C#,
Java, PL/SQL, etc)
Navtive code (C#,
Java, PL/SQL, etc)
Navtive code (C#,
Java, PL/SQL, etc)
C#
C#
C# C#
U-SQL T-SQL
T-SQL
T-SQL, DAX
DAX, M
Phyton, R
Phyton, R
Structured DataUnstructured Data
Global KPI & Advanced
Analytic Catalogue

11. Sensors
PLCs
Server
IoT hub Stream
Analytics
Power BI
Azure
Functions
Data Lake
Store
Sensors
Narrowband
IOT
Sensor to Azure architecture

12. Build and test Business ideas
Minimal Viable Product

13. Ideate!

14. Scale!

15. 1. Any digitalisation initiative should be business- and use-case driven, with a clear customer
focus, ensuring sponsorship and value creation.
2. Information, data and business rules should be legally yours and technically enabled to flow
freely across applications and analytic tools to ensure company data ownership, flexibility
and technical pragmatism.
3. Your technical platform should be modular to support fit-for-purpose configurations
ensuring no provider can monopolise; your data, your key business rules, or enforce "evil"
licensing models or exclude valuable technology options.
4. Any data & analytic service or applications developed to support your core business
processes, should be owned by you and use life-cycle principles and industry best practices.
This enables you to change between in-house vs hired personnel/service model over time.
Use open API´s and build a library of re-usable micro services accompanied by a well
managed enterprise information library.
5. Balance the need to protect your custom applications and analytic data as trade secrets, with
the fruits from sharing them with your industry to bringing down cost, risk and
environmental impact.
6. Analytic services related to your core business should only be acquired after strategic
assessments, and be provided using defined input/outputs with a company owned simplified
analytic engines running in parallel as reference models.
Digitalize fast and keep your core business
These are core principles developed in
collaboration with our clients and
partners that we strive to adhere to.

16. Good Luck!
Jan Eivind Danielsen