Informasjonsstyring som

muliggjører for digitalisering

av verdikjedenKvalitet og Risikodagene 2017

Kjetil Rønning, Information Management & Security Manager

About Aker BP

4The Aker BP merger announced 10 June 2016, merger completed 30 September, integration completed 1 December

OUR VISION

Creating the leading offshore independent E&P company

Det norske has proven to be one of the most

successful E&P independents through

innovation, consistent performance and M&A

Solid performance through hands-on asset

focus and continuous improvement

Ability to turn around even top quartile assets

Flexible and fast moving organization

Independent-like business practices

BP has been one of the pioneers of the

E&P industry globally and is a well

respected company with significant

resources

Fully “Integrated capacity” from research

to sales

Advanced technological capabilities

Pioneers in frontier regions

Strong industry relationships

Aker has over the last decades built a

unique oil service hub and world class

supply chain capabilities

World class service capacity from Aker

companies

Deep sector knowledge and track record

of long-term value creation

Proven M&A capabilities

Strong industry relationships

5

CORPORATE STRATEGY

Visible organic growth from existing portfolio

Strong production base of operated assets

• ~80% liquids / ~20% gas

Organic growth opportunities

• New developments in areas with proven potential

• IOR potential in producing assets

• Near field and frontier exploration

Unique portfolio with potential to reach production

above ~270 mboepd from 2023 (12% CAGR from 2016)

from existing discoveries

High quality development projects with low break even

Illustrative production potential, mboepd net

0

50

100

150

200

250

300

2017 2018 2019 2020 2021 2022 2023 2024 2025

* Including phase 2

Alvheim

Boa

Boa infills 2017

Bøyla

Gina Krog

Hanz

Hod

Ivar Aasen

Johan Sverdrup*

Oda

Skarv

Tambar/Tambar East

Ula

Valhall

Vilje

Viper-Kobra

Volund

Volund infills 2017

Sanctioned Non-sanctioned

Alvheim area infills/sidetracks

Caterpillar

Garantiana

Ivar Aasen upsides

Krafla/Askja

North of Alvheim

Snadd

Storklakken

Tambar upsides

Ula upsides

Valhall upsidesNew field developments

Upsides and tie-ins to existing hubs

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Solid footprint covering entire NCS

* Phase 1, estimated break even price updated February 2017

Skarv

Alvheim

Ivar Aasen

Johan Sverdrup

Ula/Tambar

Valhall/Hod

Alvheim

High production efficiency and low operating cost

Ivar Aasen

First oil December 2016

Johan Sverdrup

World class development with break even price below 20 USD/bbl*

Skarv

Solid base performance and upside potential

Ula/Tambar

Late life production with significant upside potential

Valhall/Hod

1 billion barrels produced, ambition to produce additional 500 mmbbls

7

AKER BP STRATEGY AND THINKING

Aker BP aims to build the benchmark offshore E&P company

... by building the benchmark E&P company

together with our suppliers

Use the downturn to create a company for

the future...

Deliver on existing projects

Realize value of resource inventory

Integrate acquisitions

Execute

Deliver on improvement agenda

Strengthen improvement capabilities

Develop new improvement initiatives

Improve

Be opportunistic and exploit market

opportunities

Selective growth that is value accretive

Secure new exploration acreage

Grow

Reorganize the value chain by strategic

partnerships and alliances

Digitize the E&P value chain

Value chain based on shared LEAN

understanding, toolbox and culture

Flexible business model ready for

growth and volatility

Information Management in Aker BP

9

Information Management in Aker BP

The main value of a «fit for purpose» information

management, is to enable an optimal information flow

throughout the enterprise’s value chain, and ensure the

right information, with the right quality, at the right time,

to the right decision maker, in a sustainable way

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Information Management in Aker BP

Defining,

implementing,

enforcing and

supporting ownership

Information Governance Enterprise ArchitectureInformation Management

Core Processes

Information Management

servicerInformation Security

Core processes to

define how to manage

information and it’s

life-cycle

Develop and manage

enterprise architecture,

ensure unified

approach to

architecture work and

manage company BI

work

Policy, specifications,

threat evaluations,

protection worthy

information,

awareness campaigns

etc.

Document control,

Asset Life Cycle

Information etc.

Digitalization in Aker BP

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New digital technologies are re-shaping the world

Big data & analytics

Instant analysis of large data

sets to identify new patterns

Cloud computing/storage

Highly scalable, variable-cost

storage & processing on demand

Collaborative technology

platforms

Employee engagement and

collaboration enabled by digital

platforms and communities

3D scanning

Analyses of real-world object or

environment to collect data on its shape /

appearance

Additive manufacturing

Print objects & parts on demand with

increasing precision, and range of

materials

Mobile connectivity & AR

Virtual telepresence to remove the need

for on-site humans and omnipresent

mobile devices

Unmanned aerial vehicles

Autonomous, low-cost vehicles

able to perform complex tasks

and remove human presence

Sensors

Low cost, low power, connected

sensors capturing spatial and

environment information

Cyber security

Protecting system integrity is a "must-

have"

Robotics & automation

Intelligent robots take on

complex assignments

Real-time communication

and tracking

Every asset, equipment,

employee always connected

Virtual reality

Interact more naturally with

digital devices and services

13

End-state – «How does digital E&P success look like?»

9

UWHP- minimum offshore manning/hours over the year

Highly automated onshore control and monitoring, characterized by

high plant availability/up-time, no unplanned shutdowns, high and

optimized production

Automatic and highly advanced plant integrity monitoring and control

Analytic based optimization of production, drilling and well.

Predictive maintenance of plant and equipment

Robotic based maintenance offshore

Campaign based maintenance – walk to work based

Autonomous drilling

Autonomous real time optimized production

Highly automated engineering & design, manufacturing and fabrication.

Operation based on «Twin-reality»- augmented reality

Virtual simulation of first oil before investment decision

Highly automated subsurface modeling and insight

14

Digital framework with six "E&P value chain data & workflow clusters", each with a set of digital building blocks defined

Exploration &

Subsurface Project development

Business

development

1:1 Virtual

Plant design

Digital

construction

Operation & Abandonment

Digital

operation

Simulated

mod. and

optimization

Simulated

abandonment

21 3 4

«Virtual First Oil»

Automated

data

acquisition

Automated

due

diligence

Buy licenses

& assets

Commercial

Resources

Concept

selection & PDO

Final investment

decision

First

Oil

Virtual Field

developer

Digital

Access

Digital

Evaluation

Back-office and support6

Enablers: Operating model and organization, Systems and Technology Platform, Strategic partnerships

Well delivery5

Automation

Autonomous

drilling & completion

Mobility and Self service

Automated well

design and planning

Digitalization needs to address business challenges both within clusters, but more importantly across clusters

Information Management and Digitalization

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Information Management and the Digitalisation transformation

Unstructured Data

• Free text (pdf, word etc.), images, videos, animations, audio, etc.

Subsurface and seismic models and large data sets.

• Part of the unstructured data, but significant amount of E&P data

Industrial Internet of Things (IIoT) data

• Sensor data from process plants, drilling processes, wells and equipment /

components. Often real-time time series data or historical time series data with

very different frequency / sampling eg. measurements, status and events.

Other structured business data

• HR data, maintenance databases, engineering databases, purchasing and

logistics etc.

Meta data

• Topology, relationships etc.

Typical types of data in E&P ecosystem:

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Ongoing initiative to harmonize and process orient the management system

Ongoing Lean adoption, including focus on flow optimization over resource

optimization

Optimization of processes in a flow optimization mind-set

= optimization of transforming input to output

Value containers in end to end processes is often information objects

(decision note, work order, 3D model, seismic model etc.)

Identifying information objects (input and output) as part of ongoing initiative

Outcome:

• Increased focus on information objects as value carrier in processes –

important for optimizing process efficiency (partially achieved)

• Input to information architecture mapping and identifying business critical

information

• Despite increase in IT tools over many years, work-flow input and output

are still usually unstructured information

Information management and business processes

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Defines information needs of the enterprise.

Provides basis for a common understanding of critical information

across process and business areas.

Selected approach based on establishing an information catalogue

Purpose of information architecture

• Define information requirements

• Ensure information is defined once, have one owner and one

official source

• Guide integration work

• Align information investments with business strategy.

• Establishing a common vocabulary and shared throuth of business

entities and the information attributes (characteristics) that matter

about these entities.

Information architecture

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Countless number of initiatives, all affecting the architecture at

some point, in some way. Needs to be managed (transition

architectures etc.)

The architecture work needs to take into consideration the

enterprise environment (vendors, partners etc), not only within

organization.

Fail Fast and an MVP approach requires a comprehension of

the total

• Comprehend the outline of the elephant, to understand what

piece to start with

• Some things needs to be done right the first time

Usually to little focus and to little competency on enterprise

perspective → Sub-optimisation

Information architecture and digitalization - experiences

«Eat the elephant

i pieces»

Minimum

Viable

Products

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Common business data used across multiple systems,

applications, and/or processes.

• Sample: Employee, Vendor, Well, Asset, Work order

Main challenges with Master Data Management

Maintaining local copy’s or variants instead of going to a

common source

• Master data becomes duplicated, non-standardized,

inconsistent, etc

• Costly and often manual processes

• Limited opportunity to perform analytics, automated

reporting etc

Ownership not clarified and/or data not maintained

• Quality issues

• Sub-optimised

• Not available to others

Well managed master data essential for digitalisation

and big data (sharing, integration, automation etc.)

Master data Management

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Information Management and Big Data - experiences

Big data is a great opportunity to unlock the power of “hidden” data, but;

If you don’t know what you are aiming for, you will most likely not hit target

→ define your Big Data objectives and your future state

Information has a life-cycle also when it is stored in a lake

→ consider the information lifecycle an plan for stewardship from the

beginning

Context is crucial to understand your data

→ manage your metadata

The data you find, might not be what you think it is

→ Validate your data ingestion

Security in a Big Data setting might end up a nightmare

→ make conscious choices when you design your security approach

To conclude: Main difference between managing Big Data and traditional

information management, is perhaps the misperception that that you don’t

need to manage Big Data

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“Don’t let your Data Lake turn into a Data Swamp”

Kiran Donepudi - Data Lake or Data Swamp, 01.12.16

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Information ownership and stewardship

• Define

• Training

• Tools and processes

• Support

Master Data tools and processes

Enrich the information architecture/catalogue

(data source, confidentiality level, retention requirements etc.)

Governance on Big Data

• Information stewards-ship

• Architecture board

• Security architecture

Focus going forward

“Now this is not the end. It is not even the beginning of the end.

But it is, perhaps, the end of the beginning.”

Winston Churchill